FORMULATION, DEVELOPMENT AND EVALUATION …...DELIVERY SYSTEM OF SELECTED DRUGS A Thesis submitted...

FORMULATION, DEVELOPMENT AND

EVALUATION OF SELF NANOEMULSIFYING DRUG

DELIVERY SYSTEM OF SELECTED DRUGS

A Thesis submitted to Gujarat Technological University

for the Award of

Doctor of Philosophy in

Pharmacy

By

Vijaykumar Laxmanbhai Ghori

[Enrollment No.: 119997290055]

Under supervision of

Dr. Dasharath M. Patel

GUJARAT TECHNOLOGICAL UNIVERSITY AHMEDABAD

June 2019

iii

DECLARATION

I declare that the thesis entitled, “FORMULATION, DEVELOPMENT AND

EVALUATION OF SELF NANOEMULSIFYING DRUG DELIVERY SYSTEM OF

SELECTED DRUGS”, submitted by me for the degree of Doctor of Philosophy is the

record of research work carried out by me during the period from July 2011 to December

2018 under the supervision of Dr. Dasharath M. Patel and Dr. Abdelwahab Omri and

this has not formed the basis for the award of any degree, diploma, associateship,

fellowship, titles in this or any other University or other institution of higher learning.

I further declare that the material obtained from other sources has been duly acknowledged

in the thesis. I shall be solely responsible for any plagiarism or other irregularities, if

noticed in the thesis.

Signature of the Research Scholar: ………………… Date: ….………………

Name of Research Scholar: Mr. Vijay L. Ghori

Place: Bhavnagar, Gujarat, India.

iv

CERTIFICATE

I certify that the work incorporated in the thesis “FORMULATION, DEVELOPMENT

AND EVALUATION OF SELF NANOEMULSIFYING DRUG DELIVERY

SYSTEM OF SELECTED DRUGS” submitted by Mr. Vijay L. Ghori was carried out

by the candidate under my supervision/guidance. To the best of my knowledge: (i) the

candidate has not submitted the same research work to any other institution for any

degree/diploma, Associateship, Fellowship or other similar titles (ii) the thesis submitted is

a record of original research work done by the Research Scholar during the period of study

under my supervision, and (iii) the thesis represents independent research work on the part

of the Research Scholar.

Signature of Supervisor: ……………………………… Date: ………………

Name of Supervisor: Dr. Dasharath M. Patel

Place: Gandhinagar

v

Course-work Completion Certificate

This is to certify that Mr. Vijay L. Ghori enrolment no. 119997290055 is a PhD scholar

enrolled for PhD program in the branch Pharmacy (Pharmaceutics) of Gujarat

Technological University, Ahmedabad.

He/She has successfully completed the PhD course work for the partial requirement for the

award of PhD Degree. His/ Her performance in the course work is as follows-

Grade Obtained in Research Methodology

(PH001)

Grade Obtained in Self Study Course

(Core Subject)

(PH002)

BC BB

Supervisor’s Sign


vi

Originality Report Certificate

It is certified that PhD Thesis titled “FORMULATION, DEVELOPMENT AND

EVALUATION OF SELF NANOEMULSIFYING DRUG DELIVERY SYSTEM OF

SELECTED DRUGS” by Mr. Vijay L. Ghori has been examined by us. We undertake

the following:

a. Thesis has significant new work / knowledge as compared already published or are

under consideration to be published elsewhere. No sentence, equation, diagram, table,

paragraph or section has been copied verbatim from previous work unless it is placed

under quotation marks and duly referenced.

b. The work presented is original and own work of the author (i.e. there is no plagiarism).

No ideas, processes, results or words of others have been presented as Author own work.

c. There is no fabrication of data or results which have been compiled / analysed.

d. There is no falsification by manipulating research materials, equipment or processes, or

changing or omitting data or results such that the research is not accurately represented in

the research record.

e.The thesis has been checked using Turnitin (copy of originality report attached) and

found within limits as per GTU Plagiarism Policy and instructions issued from time to time

(i.e. permitted similarity index <=25%).

Signature of the Research Scholar: ___________ Date:

Name of Research Scholar: Mr. Vijay L. Ghori

Place: Bhavanagar

Signature of Supervisor: _____________ Date:

Name of Supervisor: Dr. Dasharath M. Patel

Place: Gandhinagar

vii

REPORT OF SIMILARITY DOWNLOADED FROM

“TURNITIN” DATABASE

viii

[Vijay L. Ghori] [Dr. D. M. PATEL]

ix

PhD THESIS Non-Exclusive License to

GUJARAT TECHNOLOGICAL UNIVERSITY

In consideration of being a PhD Research Scholar at GTU and in the interests of the

facilitation of research at GTU and elsewhere, I, Vijay L. Ghori having Enrollment No.

119997290055 hereby grant a non-exclusive, royalty free and perpetual license to GTU on

the following terms:

a) GTU is permitted to archive, reproduce and distribute my thesis, in whole or in part,

and/or my abstract, in whole or in part (referred to collectively as the “Work”) anywhere in

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authority of their “Thesis Non-Exclusive License”;

d) The Universal Copyright Notice (©) shall appear on all copies made under the authority

of this license;

e) I undertake to submit my thesis, through my University, to any Library and Archives.

Any abstract submitted with the thesis will be considered to form part of the thesis.

f) I represent that my thesis is my original work, does not infringe any rights of others,

including privacy rights, and that I have the right to make the grant conferred by this non-

exclusive license.

g) If third party copyrighted material was included in my thesis for which, under the terms

of the Copyright Act, written permission from the copyright owners is required, I have

obtained such permission from the copyright owners to do the acts mentioned in paragraph

(a) above for the full term of copyright protection.

x

h) I retain copyright ownership and moral rights in my thesis, and may deal with the

copyright in my thesis, in any way consistent with rights granted by me to my University

in this non-exclusive license.

i) I further promise to inform any person to whom I may hereafter assign or license my

copyright in my thesis of the rights granted by me to my University in this non-exclusive

license.

j) I am aware of and agree to accept the conditions and regulations of PhD including all

policy matters related to authorship and plagiarism.

Signature of the Research Scholar: _____________Date:

Name of Research Scholar: Vijay L. Ghori

Place: Bhavnagar

Signature of Supervisor: _____________________ Date:

Name of Supervisor: Dr. Dasharath. M. Patel

Place: Gandhinagar

xi

Thesis Approval Form

The viva-voce of the PhD Thesis submitted by Mr. Vijay L .Ghori

(Enrollment No.119997290055) entitled “FORMULATION, DEVELOPMENT

AND EVALUATION OF SELF NANOEMULSIFYING DRUG DELIVERY

SYSTEM OF SELECTED DRUGS” was conducted

on............................................................ …………………...............(day and

date) at Gujarat Technological University.

(Please tick any one of the following option) The performance of the candidate was satisfactory. We recommend that he/she be awarded the PhD degree. Any further modifications in research work recommended by the panel after 3 months from the date of first viva-voce upon request of the Supervisor or request of Independent Research Scholar after which viva-voce can be re-conducted by the same panel again. The performance of the candidate was unsatisfactory. We recommend that he/she should not be awarded the PhD degree.

---------------------------------------------------

-----------------------------------------------------

Name and Signature of Supervisor with Seal 1) (External Examiner 1) Name and Signature ---------------------------------------------------

-------------------------------------------------------

2) (External Examiner 2)Name and Signature

3) (External Examiner 3) Name and Signature

xii

ABSTRACT Submitted by

Vijay L. Ghori

[Enrollment No.: 119997290055]

Under supervision of


BCS Class-II drugs have poor oral bioavailability due to its limited aqueous solubility.

Lercanidipine HCL, an antihypertensive orally administered drug belongs to a group of

medicines called Calcium Channel Blockers of the third generation as well as Cinacalcet

HCL, a calcimimetic orally administered drug with poor aqueous solubility were selected

as drug candidates for the research work. In this study, an attempt was made to develop a

self nanoemulsifying drug delivery system (SNEDDS) to enhance oral bioavailability of

selected drugs. Received complimentary samples of selected drugs were subjected for

identification and compatibility study by FTIR. Based on solubility in different solvents

and their combinations, oil, surfactant, and co-surfactant were identified for both drugs

separately. SNEDDS were prepared using a pseudo-ternary phase diagram method.

Various parameters like dispersion time, globule size and drug diffusion etc. were screened

for 32 full factorial design. The optimized batch was selected on the basis of arbitrary

criteria using Design Expert software. The data were statistically analysed by ANOVA,

model equations were generated and contour plots as well as 3D surface plots were

constructed for each response. The optimized formulations of selected drugs were

evaluated by various parameters like globule size, polydispersity index, zeta potential, drug

content and in-vitro diffusion study. Optimized formulations were subjected to accelerated

stability study according to ICH guidelines. In vitro diffusion study was also carried out to

compare optimized SNEDDS with the available marketed conventional tablet. The results

of the present study revealed the prospective use of SNEDDS of poorly water-soluble drug

like Lercanidipine HCL and Cinacalcet HCL

xiii

ACKNOWLEDGEMENT

I offer flowers of gratitude to the almighty God for the benediction and grace & for being the source of strength throughout my life.

I acknowledge Gujarat Technological University for giving me the opportunity to proceed

with the research work and do the PhD.

With a deep sense of respect and gratitude, I would like to express my sincere thanks to my

esteemed guide, Dr. Dashrath M. Patel, Director- PG & Research, Arihant School of

Pharmacy & Bio-Research Institute, Adalaj, Gandhinagar,Gujarat, India for giving me the

opportunity to work in the field of nanotechnology. Without his perpetual encouragement,

constructive guidance, advice and support throughout my journey of the doctoral research.

I would never have succeeded in accomplishing the work. My sincere gratitude to my co-

guide, Dr. Abdelwahab Omri, Professor, Laurentian University, Canada for showing his

willingness to act as my international co-guide and providing his valuable insights,

prompt, timely and helpful guidance throughout as well as for the unmatched support

rendered at the time of publication of the articles too.

With great reverence, I take this opportunity to express my debt of gratitude to the DPC

(Doctoral Progress committee) members, Prof. Mukesh C. Gohel, Research Director and

Professor, Dept. of Pharmaceutics, Anand Pharmacy College and Dr. L. D. Patel.,

Ex-Principal Sharada school of pharmacy, Pethapur, Gandhinagar, for their critical

review, guidance and support for the work.

I wish to express my heartiest thanks to Honourable Vice Chancellor, Registrar and E.C

members of M.K. Bhavnagar University. Principal and staff members of Shantilal Shah

Pharmacy College , Bhavnagar and all staff members at M. K. Bhavnagar University,

Bhavnagar for providing me the infrastructural and other direct or indirect support for the

successful completion of research work. It would be remiss on my part if I don’t

acknowledge the help and support of all my friends and colleagues for their wonderful

xiv

company, unending inspirations, motivations, constant encouragement and technical

assistance throughout the research work.

I am also thankful to CSMCRI, Bhavnagar, Jenberkt Ltd, Shihor., Dept. of Physics,

Chemistry and Life sciences of M. K. Bhavnagar University and Special Thanks to

B. K. Mody Pharmacy College, Rajkot., Dept. of Chemistry, Katcch university for

providing me the technical and infrastructural support for carrying out various analysis.

I am immensely thankful to Zydus Cadila Ltd., Ahmedabad and Cipla Ltd, Mumbai, India

for providing the gift sample of drugs. My special thanks to Mr. Rakshit patel, Piramal

Health care, and Mr. Mehul barad, Jenberkt Ltd, for their technical support.

I would like to bid special thanks appreciation to Mr. Nipul Rajyaguru and to all office

staff of the college for their kind co-operation and assistance during the journey to this

stage.

I would also like to put in record my thanks to Honourable Vice Chancellor

Prof. (Dr.) Navin Sheth, Registrar, Research Coordinator and other Staff Members of

PhD section of GTU for their co-operative assistance and support.

At the outset I feel that I may not have reached this stage without the blessings, love &

care of my well wishers, loving parents and family members.

I express my sincere thanks and apology to all those who have contributed to the success of

this work & helped me in whatsoever manner during this work & whose name I might have

missed inadvertently or those who are like countless stars in numerous galaxies.

Thanks to one & all…

Vijay L. Ghori

xv

Dedicated to my Beloved

Family Members, Gurus

and The Supreme God

xvi

“Jay Shree Ganeshay Namah”

TABLE OF CONTENTS

xvii

TABLE OF CONTENTS

SECTION NO.

SUB SECTION TITLE PAGE

NO.

CHAPTER 1: INTRODUCTION

1.1 Introduction 01

1.2 Self Emulsifying Drug Delivery Systems 02

1.3 Lipid Nanoformulations: Design Approach 03

1.3.1 Commercially Available Pharmaceutical Products Formulated As SEDDS for Oral Administration 04

1.4 Lipid Formulation Classification System 05

1.4.1 Lipid Formulations 05

1.4.2 Types of Lipid Formulations: 06

1.5 Biopharmaceutical Classification 07

1.6 Self Nanoemulsifying Drug Delivery System 08

1.6.1 Advantages of Self Nano Emulsifying Drug Delivery System 10

1.6.2 Selection of Excipients In Self-Emulsifying Formulations 11

1.6.3 Lipids, Surfactants, and Co Surfactant Used In Commercial Formulations 12

1.6.4 Mechanism of SEDDS 13

1.7 Concept of Nanoemulsions within Lipid Based Formulation 15

1.7.1 SNEDDS within Lipid Formulation Classification Systems 15

1.7.2 Solidification of SNEDDS 15

1.7.3 Equilibrium Solubility of Diluted SNEDDS 16

1.7.4 Drug Release and The Justification of Dispersion Test For Nanoformulations 16

1.7.5 Mechanism of Drug Supersaturation: Role of SNEDDS 16

1.8 Lipid Digestion and Drug Absorption: Mechanism 16

TABLE OF CONTENTS

xviii

1.8.1 Lipid Metabolism 16

1.8.2 Drug Absorption 17

1.9 In Vitro In Vivo Correlation (IVIVC) for Lipid Nanoformulations 17

1.10 Summary of SNEDDS 18

1.11 Rationale for Lercanidipine HCL SNEDDS 18

1.12 Rationale for Cinacalcet HCL SNEDDS 19

1.13 Objectives of the Work 19

1.14 Profile of Selected Drugs 20

1.14.1 Profile of Lercanidipine HCL 20

1.14.2 Profile of Cinacalcet HCL 24

1.15 Profile of Excipients 27

1.16 References 32

CHAPTER 2 : REVIEW OF LITERATURE

2.1 SNEDDS Preparations 43

2.2 Patent Review of SNEDDS 47

2.3 References 51

CHAPTER 3: EXPERIMENTAL

3.1 List of Equipments Used for Research Work 54

3.2 List of Materials Used for The Research Work 55

3.3 Scanning and Calibration Curve of Selected Drugs 56

3.3.1 Preparation of Calibration Curve Preparation of Lercanidipine HCL 56

3.3.2 Preparation of Calibration Curve Preparation of Cinacalcet HCL 57

3.4 Solubility Study 59

3.5 Evaluation of Effective Oil, Surfactant and Co-Surfactant 59

TABLE OF CONTENTS

xix

3.6 Drug-Excipients Compatibility of SNEDDS Formulations 60

3.7 Evaluation Methods for SNEDDS Formulations 60

3.7.1 Refractive Index and Turbidimetric Evaluation 60

3.7.2 Measurement of Droplet Size, Polydispersity Index (PDI) and Zeta Potential 60

3.7.3 Drug Content 61

3.7.4 Effect of Dilution and Aqueous Phase Composition on Lercanidipine HCL and Cinacalcet HCL SNEDDS 61

3.7.5 Measurement of Viscosity of Lercanidipine HCL and Cinacalcet HCL SNEDDS 61

3.7.6 Measurement of pH Lercanidipine HCL and Cinacalcet HCL SNEDDS 61

3.7.7 Self-Emulsification and Precipitation Assessment 62

3.7.8 Centrifugation and Freeze– Thaw Cycle 62

3.7.9 In Vitro Diffusion Study 62

3.7.10 Stability Study of Lercanidipine HCL and Cinacalcet HCL SNEDDS 63

3.8 Data Analysis 63

3.9 References 63

CHAPTER 4: RESULT AND DISCUSSION

4.1 Result and Discussion for SNEDDS of Lercanidipine HCL 65

4.1.1 Identification of Drug 65

4.1.2 Scanning and Calibration Curve Preparation 66

4.1.3 Screening of Oil and Surfactant/Co-Surfactant for Lercanidipine HCL 69

4.14 Drug and Surfactant Compatibility Study 72

4.1.5 Pseudoternary Phase Diagram 74

4.1.6 Factorial Design for Optimization of Lercanidipine HCL SNEDDS 77

4.1.7 Effect of Dilution on SNEDDS of Lercanidipine HCL by Distilled Water 80

4.1.8 Viscosity , Refractive Index , % Transmittance and pH 81

TABLE OF CONTENTS

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4.1.9 Thermodynamic Stability 82

4.1.10 Particle Size Distribution (PSD) and Ζ-Potential Analysis 83

4.1.11 Polydispersibility Index (PDI) 86

4.1.12 In Vitro Diffusion Study 87

4.1.13 Optimization of Lercanidipine Hydrochloride SNEDDS Formulation 88

4.1.13.1 Experimental Design and Statistical Analysis for Dispersion Time 88

4.1.13.2 Various Schematic Diagram for Dispersion Time 92

4.1.13.3 Experimental Design and Statistical Analysis for Globule Size 94

4..1.13.4 Various Schematic Diagrams for Globule Size 98

4.1.13.5 Experimental Design and Statistical Analysis for Drug Release 100

4.1.13.6 Various Schematic Diagram for Release Time 104

4.1.13.7 Comparison of Full and reduced models for

Lercanidipine HCL 106

4.1.14 Desirability Range of Lercanidipine HCL 109

4.1.15 Stability study of Lercanidipine HCL SNEDDS 110

4.1.15.1 Change in Globule Size and Zeta Potential Upon Stability 111

4.1.15.2 Drug Content Determination Upon Stability 111

4.2 Result and Discussion for SNEDDS of Cinacalcet HCL

113

4.2.1 Identification of Cinacalcet HCL 113

4.2.2 Scanning and Calibration Curve Preparation 113

4.2.3 Screening of Oil and Surfactant/Co-Surfactant for Cinacalcet HCL 119

4.2.4 Drug and Surfactant Compatibility Study 121

4.2.5 Pseudoternary Phase Diagram 123

4.2.6 Factorial Design for Optimization of Cinacalcet HCL SNEDDS 125

TABLE OF CONTENTS

xxi

4.2.7 Effect of Dilution on SNEDDS of Cinacalcet HCL by Distilled Water 128

4.2.8 Viscosity , Refractive Index , % Transmittance and pH 129

4.2.9 Thermodynamic Stability 130

4.2.10 Particle Size Distribution (PSD) and Ζ-Potential Analysis 131

4.2.11 Polydispersibility Index (PDI) 134

4.2.12 In Vitro Diffusion Study of Cinacalcet HCL 134

4.2.13 Optimization of Cinacalcet HCL SNEDDS Formulation 136

4.2.13.1 Experimental Design and Statistical Analysis for Dispersion Time 136

4.2.13.2 Various Schematic Diagram for Dispersion Time 140

4.2.13.3 Experimental Design and Statistical Analysis for Globule Size 142

4..2.13.4 Various Schematic Diagrams for Globule Size 146

4.2.13.5 Experimental Design and Statistical Analysis for Drug Release 148

4.2.13.6 Various Schematic Diagram for Release Rate 151

4.2.13.7 Comparison of Full and reduced models for

Cinacalcet HCL 153

4.2.14 Desirability Range of Cinacalcet HCL 157

4.2.15 Stability Study of Cinacalcet HCL SNEDDS 158

4.2.15.1 Change in Globule Size and Zeta Potential Upon Stability 158

4.2.15.2 Drug Content Determination Upon Stability 159

4.3 References 160

CHAPTER 5 : SUMMARY AND CONCLUSION

5.1 Summary of The Work 161

5.2 Achievements with Respect to the Objectives 162

5.3 Major Contribution and Practical Implications of the Work to Society 163

TABLE OF CONTENTS

xxii

5.4 Recommendation for Future Research 164

5.5 Conclusion 164

5.6 References 166

CHAPTER 6 : LIST OF PUBLICATIONS

6.1 LIST OF PUBLICATIONS 167

LIST OF ABBREVIATIONS

xxiii


Abbreviation Full form

ANOVA Analysis of Variance

API Active Pharmaceutical Ingredient

AUC Area Under Curve

BCS Biopharmaceutical Classification System

CKD Chronic Kidney Disease

EE Entrapment Efficiency

FDA Food And Drug Administration

FTIR Fourier Transform Infrared Spectroscopy

GIT Gastrointestinal Tract

GIT Gastro Intestinal Tract

GRAS Generally Regarded As Safe

GS Globule Size

H Hour

HDL High Density Lipid

HLB Hydrophilic Lipophilic Balance

ICH International Conference on Harmonization

IUPAC International Union of Pure and Applied Chemistry

KBr Potassium Bromide

LCT Long Chain Triglyceride

LFCS Lipid Formulation Classification System

LOD Limit of Detection

LOQ Limit of Quantification

L-SNEDDS Liquid Self Nano Emulsifying Drug Delivery Systems


xxiv

MCT Medium Chain Triglyceride

ME Multiple Emulsion

Min Minute

MW Molecular Weight

O/W Oil-in-Water

PDI Polydispersity Index

PEG Polyethylene Glycol

PG Propylene Glycol

PTH parathyroid hormone

PSD Particle Size Distribution

q.s Quantity Sufficient

RH Relative Humidity

RP-HPLC Reverse Phase High Performance Liquid Chromatography

RPM Rotation Per Minute

SEDDS Self Emulsifying Drug Delivery System

SMEDDS Self Micro Emulsifying Drug Delivery System

Smix Surfactant and Cosurfactants Mixture

SNEDDS Self Nano Emulsifying Drug Delivery System

S-SMEDDS Solid Selfmicroemulsifying Drug Delivery System

S-SNEDDS Solid Self Nano Emulsifying Drug Delivery Systems

UV Ultra Violet

ZP Zeta Potential

LIST OF SYMBOLS

xxv

LIST OF SYMBOLS

% Percent

± Positive or Negative

°C Degree Celcius

0F Degree Fahrenheit

cm Centimeter

g Gram

h Hour

mg Milligram

ml Millilitre

mV Millivolts

ng Nanogram

nm Nanometer

pH Concentration of Hydronium ion

Pka Degree of ionization

Q Amount of drug released

R Linear correlation coefficient

s Second

T Time

Δ Difference

λ max Wave length of maximum absorption

LIST OF FIGURES

xxvi

LIST OF FIGURES

FIGURE NO. TITLE PAGE NO.

4.1 Scanning of Lercanidipine HCL in Methanol 66

4.2 Calibration Plot of Lercanidipine HCL in Methanol 67

4.3 Scanning of Lercanidipine HCL in Phosphate Buffer 69

4.4 Calibration Plot of Lercanidipine HCL in Phosphate Buffer 69

4.5 Solubility Chart of Lercanidipine HCL in Various Solvents 72

4.6.A FTIR of Lercanidipine HCL 73

4.6.B FTIR of Lercanidipine HCL with Excipients 73

4.7 Overlay FTIR of Lercanidpine HCL and Lercanidpine HCL with Excipients 73

4.8 Pseudoternary Phase Diagrams of Capmul MCM (Oil), Polysorbate 20/ Transcutol P (S/Cos) 75

4.9 Particle Size Distribution of Lercanidipine HCL Formulation 85

4.10 Zeta Potential of Lercanidipine SNEDDS 85

4.11 Release Profile for Formulations LS-1 To LS-7 of Lercanidipine HCL SNEDDS 87

4.12 Comparison of Release Profile of Various SNEDDS Formulations with Pure Drug and Marketed Tablet Formulation 87

4.13 Predicted Vs Actual Dispersion Time Plot of Lercanidipine HCL SNEDDS 92

4.14 Contour plot of interaction of Capmul MCM and Polysorbate 20: Transcutol P Ratio on Dispersion Time 93

4.15 Response surface Plot of Interaction of Capmul MCM and Polysorbate 20: Transcutol P Ratio on Dispersion Time 93

4.16 Predicted Vs Actual Globule Size plot of Lercanidipine HCL SNEDDS 98

4.17 Contour plot of Interaction of Capmul MCM and Polysorbate 20: Transcutol P Ratio on Globule size 99

4.18 Response Surface Plot of Interaction of Capmul MCM and Polysorbate 20: Transcutol P (1:1) Ratio on Globule Size 99

4.19 Predicted Vs Actual % Release Plot of Lercanidipine HCL SNEDDS 104

4.20 Contour Plot of Interaction of Capmul MCM and Polysorbate 20: Transcutol P Ratio on % Release 105

LIST OF FIGURES

xxvii

4.21 Response Surface Plot of Interaction of Capmul MCM and Polysorbate 20: Transcutol P Ratio on % Release 105

4.22 Overlay Plot of Lercanidipine HCL

110

4.23 Desirability of Lercanidipine HCL 110

4.24 Scanning of Cinacalcet HCL in methanol 114

4.25 Calibration Curve of Cinacalcet HCL In Methanol 115

4.26 Calibration Curve of Cinacalcet HCL by HPLC 118

4.27 HPLC Chromatogram of Cinacalcet HCL in Dissolution Medium 118

4.28 Solubility chart of Cinacalcet HCL in various solvent 121

4.29.A FTIR of Cinacalcet HCL 121

4.29.B FTIR of Cinacalcet HCL with Excipients 121

4.30 Overlay FTIR of Cinacalcet HCL and Cinacalcet HCL with Excipients 122

4.31 Pseudoternary Phase Diagrams of Capmul MCM (Oil), Polysorbate 20/ Transcutol P (S/Cos) 123

4.32 Particle Size Distribution of Cinacalcet HCL SNEDDS Formulation 132

4.33 Zeta Potential of Cinacalcet HCL SNEDDS 133

4.34 Release Profile for Formulations C1to C9 of Cinacalcet HCL SNEDDS 135

4.35 Comparison of Release Profile of Various SNEDDS Formulation With Pure Drug and Marketed Tablet Formulation 136

4.36 Predicted Vs Actual Dispersion Time Plot of Cinacalcet HCL SNEDDS 140

4.37 Contour Plot of Interaction of Capmul MCM and Polysorbate 80: PEG 400 Ratio on Dispersion Time 141

4.38 Response Surface Plot of Interaction of Capmul MCM and Polysorbate 80: PEG 400 Ratio on Dispersion Time 141

4.39 Predicted Vs Actual Globule Size Plot of Cinacalcet HCL SNEDDS 146

4.40 Contour Plot of Interaction of Capmul MCM and Polysorbate 80: PEG 400 Ratio on Globule Size 146

4.41 Response Surface Plot of Interaction of Capmul MCM and Polysorbate 80: PEG 400 Ratio on Globule Size 147

4.42 Predicted Vs Actual % Release Plot of Cinacalcet HCL SNEDDS 151

LIST OF FIGURES

xxviii

4.43 Contour Plot of Interaction of Capmul MCM and Polysorbate 80: PEG 400 Ratio on % Release 152

4.44 Response Surface Plot of Interaction of Capmul MCM and Polysorbate 80: PEG 400 Ratio on % Release 152

4.45 Overlay Plot of Cinacalcet HCL

157

4.46 Desirability of Cinacalcet HCL 158

LIST OF TABLES

xxix

LIST OF TABLES

TABLE No. TITLE PAGE

No.

1.1 Compositions of Lipid Based Formulation 05

1.2 BCS Classification 07

1.3 Components Used for SNEDDS 09

1.4 Solubility of Polysorbate 80 in Various Solvents 28

1.5 Typical Properties of Polysorbate 80 28

1.6 Solubility of PEG 400 in Various Solvents 29

1.7 Typical Properties of PEG 400 30

1.8 Typical Properties of Transcutol P 30

1.9 Typical Properties of Capmul MCM 31

1.10 Typical Properties of Polysorbate 20 32

2.1 Patents of SNEDDS 47

3.1 List of Equipments Used for Research Work 54

3.2 List of Materials Used for Research Work 55

4.1 Identification of Lercanidipine HCL 65

4.2 Calibration Curve Data of Lercanidipine HCL in Methanol 67

4.3 Calibration Curve Data of Lercanidipine HCL in Phosphate Buffer 68

4.4 Solubility Study of Lercanidipine HCL in Various Vehicles (Oils, Surfactants, Co Surfactants and Distilled Water) 71

4.5 Calculation of HLB of Capmul MCM (Oil), Polysorbate 20/ Transcutol P (S/Cos)(1:1) 76

4.6 Preliminary Trials for Development of Lercanidipine HCL SNEDDS 77

4.7 Factors and Levels of Independent Variables in 32 Full Factorial Design for Formulation of Lercanidipine HCL SNEDDS 79

4.8 32 Full Factorial Design for Formulation of Lercanidipine HCL SNEDDS 79

LIST OF TABLES

xxx

4.9 Effect of Dilution On SNEDDS of Lercanidipine HCL by Distilled Water 80

4.10 Viscosity, Refractive Index and % transmittance of Various Lercanidipine Hydrochloride SNEDDS Formulations 81

4.11 Centrifugation and Freeze –Thaw Cycle Parameter of Lercanidipine SNEDDS 83

4.12 Particle Size Distribution of the Various Lercanidipine HCL SNEDDS Formulations 84

4.13 Observed Values of Dispersion Time of Lercanidipine HCL SNEDDS 89

4.14 Values of Coefficients for Polynomial Equations and r2 for Dispersion Time Response Variables of Lercanidipine HCL SNEDDS 90

4.15 Analysis of Variance for Response Surface - Quadratic Model of Dispersion Time 91

4.16 Optimized Values of Lercanidipine HCL SNEDDS Obtained by Applying Constraints on Variables and Responses 92

4.17 Observed Values of Lercanidipine HCL SNEDDS Obtained by Applying Constraints on Variables and Responses 94

4.18 Values of Coefficients for Polynomial Equations and r2 for Globule Size Response Variables of Lercanidipine HCL SNEDDS 95

4.19 Analysis of Variance for Response Surface - Quadratic Model of Globule 96

4.20 Optimized Values of Lercanidipine HCL SNEDDS Obtained by Applying Constraints on Variables and Responses 97

4.21 % Observed Drug Release of Lercanidipine HCL SNEDDS as per Full Factorial Design 100

4.22 Values of Coefficients for Polynomial Equations and r2 for Response Variables of Lercanidipine HCL SNEDDS 101

4.23 Analysis of Variance for Response Surface - Quadratic Model of % Release 102

4.24 Optimized Values Obtained by Applying Constraints on Variables and Responses 103

4.25 Comparison of Models for Lercanidipine HCL Dispersion Time 106

4.26 Comparison of Models for Lercanidipine HCL Globule Size 107

4.27 Comparison of Models for Lercanidipine HCL Release Rate 108

4.28 Globule Size Analysis upon Stability 111

4.29 Zeta Potential Analysis upon Stability 111

4.30 Drug Content Determination Analysis upon Stability 112

4.31 Identification of Cinacalcet HCL 113

4.32 Calibration curve data of Cinacalcet HCL in Methanol 115

LIST OF TABLES

xxxi

4.33 Calibration Curve Data of Cinacalcet HCL by HPLC 116

4.34 Linearity and Range 116

4.35 Observations for Linearity 117

4.36 Solubility Study of Cinacalcet HCL in Various Vehicles (Oils, Surfactants, Co Surfactants and Distilled Water) 120

4.37 Calculation of HLB of Capmul MCM (Oil), Polysorbate 280/PEG 400 (S/Cos)(2:1) 124

4.38 Preliminary Trials for Development of Cinacalcet HCL SNEDDS 126

4.39 Factors and Levels of Independent Variables in 32 Full Factorial Design for Formulation of Cinacalcet HCL SNEDDS

127

4.40 32 Full Factorial Design for Formulation of Cinacalcet HCL SNEDDS 127

4.41 Effect of Dilution on SNEDDS of Cinacalcet HCL by Distilled Water 128

4.42 Viscosity, Refractive index and % transmittance of Various Cinacalcet HCL SNEDDS Formulations 129

4.43 Centrifugation and Freeze –Thaw Cycle Parameter of Cinacalcet HCL SNEDDS 130

4.44 Particle Size Distribution of the Various Cinacalcet HCL SNEDDS Formulations 133

4.45 Observed Values of Dispersion Time of Cinacalcet HCL SNEDDS 137

4.46 Values of Coefficients for Polynomial Equations and r2 for Dispersion Time Response Variables of Cinacalcet HCL SNEDDS 138

4.47 Analysis of Variance for Response Surface - Quadratic Model of Dispersion Time 139

4.48 32 Full Factorial Design for Formulation of Cinacalcet HCL SNEDDS 143

4.49 Values of Coefficients for Polynomial Equations and r2 for Globule Size Response Variables of Cinacalcet HCL SNEDDS 144

4.50 Analysis of Variance for Response Surface - Quadratic Model of Globule Size 144


4.52 % Drug release of Cinacalcet HCL SNEDDS as per Full Factorial Design 148

4.53 Values of Coefficients for Polynomial Equations and r2 for Response Variables of Cinacalcet HCL SNEDDS 149

4.54 Analysis of Variance for Response Surface - Quadratic Model of % Release 150


4.56 Comparison of Full and Reduced Model for Cinacalcet HCL Dispersion 153

LIST OF TABLES

xxxii

4.57 Comparison of Full and Reduced Model for Cinacalcet HCL Globule Size 154

4.58 Comparison of Full and Reduced Model for Cinacalcet HCL Release Rate 156

4.59 Globule Size Analysis upon Stability 159

4.60 Zeta Potential Analysis upon Stability 159

4.61 Drug Content Determination Analysis upon Stability 159

CHAPTER 1

Introduction

1.1 Introduction

The formulation of poorly soluble drug candidates presents challenges for formulation

scientists in the pharmaceutical industry. Nearly 40% of raw chemical entities entering in

the pharmaceutical industry are poorly soluble or lipophilic compounds, which lead to,

high intra and inter subject variability, poor oral bioavailability and lack of dose

proportionality [1]. Scientists are putting efforts to enhance the oral bioavailability of such

drugs in order to increase their clinical efficacy [2].

As dissolution is the rate limiting step for oral drug delivery, low soluble drugs are

showing poor bioavailability [3]. Literature study reported various techniques such as solid

dispersions [4], complexation with cyclodextrin [5] and lipid based formulations [6], and

self-emulsifying drug delivery systems (SEDDS) [7] to overcome bioavailability problems.

SEDDS are found to be the prominent approach to improve solubility. SEDDS enhance

solubility and maintaining the drug in a dissolved state, lead to improve oral bioavailability

of poorly soluble drugs and transportation of drugs through Gastro intestinal tract [8].

Chapter 1 Introduction

2

1.2 Self Nano Emulsifying Drug Delivery Systems

Self Nano Emulsifying Drug Delivery System (SNEDDS) is heterogeneous dispersions of

two immiscible liquids having a mean droplet size in the nanometric scale (20–200 nm)[9].

Self nanoemulsifying drug delivery systems are able to self emulsify rapidly in

gastrointestinal fluids under the gentle agitation provided by the motion of the

gastrointestinal tract, making itself a unique formulation. They form fine O/W emulsions.

Little droplets of oil produced by SNEDDS dispersed in the G. I. fluids give large

interfacial area and thus the activity of pancreatic lipase increases to hydrolyze

triglycerides and result in a faster release of the drug.

Furthermore, in most cases surfactant helps in bioavailability enhancement for such

formulations by activation of different mechanisms, maintaining the drug in solution and,

thus, enhancing intestinal epithelial permeability at the same time. Moreover, irritation in

gut wall is reduced due to the more dissipated and more uniform distribution of drug into

oil droplets. In gain, lipid based drug delivery protects the drug from enzymatic or

chemical degradation and affects the oral bioavailability of drugs through various

mechanisms and lymphatic transport of lipophilic drugs promoted due to lipoproteins.

These formulation introduced into capsules at once, or converted into granules, pellets, and

powders using methods like molten granulation, adsorption on a solid support, spray

drying, spray chilling, melt extrusion, spheronization and supercritical fluid based methods

[10, 11]. For good bioavailability, enough aqueous solubility along with good intestinal

permeability is necessary for sufficient drug absorption. PWSDs (Poorly water soluble

drugs) are broadly connected with short and variable absorption and often affected by

diverse food intakes. It was reported that SNEDDS enhance absorption of poorly water

soluble drugs when administered orally [12, 13].

Various researchers have already documented that lipid based nanoformulations such as

SNEDDS is a better option for absorption enhancer for PWSDs when administered orally.

SEDDS are defined as isotropic mixtures of natural or synthetic oils, solid or liquid

surfactants or alternatively, one or more hydrophilic solvents and Co solvents/ surfactants

[14]. On mild agitation followed by dilution with aqueous media /gastrointestinal

(GI) fluids these systems can form fine oil in water (o/w) emulsions/ microemulsions/ self

microemulsifying drug delivery system (SMEDDS) /self-nanoemulsifying drug delivery


3

(SNEDDS) system. Fine oil droplets would pass rapidly from the stomach and promote a

wide distribution of the drug throughout the GI system, thereby minimizing the irritation

during extended contact between bulk drug substances and the gut wall. When compared

with emulsions, which are sensitive and metastable dispersed forms, SMEDDS are

physically stable formulations that are easy to manufacture. An additional advantage of

SMEDDS over simple oily solutions is that they provide a large interfacial area [15].

Indeed, in some selected cases, these arrangements have been successful, but they too

cause many other disadvantages. The main problem with micronization technique is

chemical and thermal stability. Many drugs may degrade and lose its natural action when

they are micronized by conventional method. Freeze drying or spray drying method have

high production cost, the traditional solvent method can be used instead; it is difficult to

deal with co precipitates with high viscosity. Complexation with cyclodextrins method is

not useful for drug substances which are not soluble in both aqueous and organic solvents.

The oral bioavailability of poorly water soluble drugs may be increased when administered

with a meal rich in fat. It increases recent interest in the formulation of poorly water

soluble drugs in the lipids. Lipid emulsions have all been used to enhance the oral

bioavailability but, more recently there have been much focus on the application of self

microemulsifying drug delivery systems [16].

1.3 Lipid Nanoformulations: Design Approach

Lipid excipients are diverse glycerides and drug is to be integrated in complex

nanoformulation like SMEDDS/SNEDDS, in the combination of oil, surfactant and or

cosolvent [17].

Mono, di or triglycerides or their derivatives are used in simple oil formulations and differ

in the content of medium or long chain fatty acids. Glyceride esters are water immiscible.

Fatty acid chain decides solving capacities for the drug. Many oils and surfactants which

are food grade materials, well tolerated by the body [18] may be used as parenteral

emulsion. [19]. These excipients have a history suggest that these excipients are used

widely in pharmaceuticals. Globule size of SNEDDS can decide the rate and extent of drug

release in vitro [20].


4

1.3.1 Commercially Available Pharmaceutical Products Formulated as SEDDS for

Oral Administration [21]

Accutane comprise of Isotretinoin developed by Hoffmann La Roche formulated with the

help of beeswax, butylated hydroxyl anisole, edetate disodium, hydrogenated soybean oil

flakes, hydrogenated vegetable oil, soybean oil, glycerine and parabens used for retinoid.

Sandimmune comprise of Cyclosporine A drug with excipients of corn oil, gelatine

(shell), linoleoyl macrogol glycerides, sorbitol for treatment of immunosuppressive agent

developed by Novartis.

Vesanoid is a brand developed by Hoffmann La Roche for leukemia containing Tretinoin

with beeswax, butylated hydroxyl anisole, edetate disodium, hydrogenated soybean oil

flakes, hydrogenated vegetable oils, soybean oil and glycerine.

Neoral brand developed in 1995 by Novartis as immunosuppressive agent having

Cyclosporine A with mono, di, triglycerides, polyoxyl 40 hydrogenated castor oil NF, DL-

tocopherol USP, gelatin NF, glycerol, iron oxide black, propylene glycol USP.

Ritonavir SEDDS formulated by Abbot Norvir in 1996 with butylated hydroxyl toluene,

ethyl alcohol, gelatin, iron oxide, oleic acid, polyoxyl 35 castor oil, and titanium dioxide in

1996 as antiretroviral agent

Saquinavir used as an antiretroviral agent with brand name Fortovase launched in 1997 by

Hoffmann La Roche with medium chain mono and diglycerides, povidone, DL alpha

tocopherol, gelatin, glycerine, red iron oxide, yellow iron oxide, and titanium dioxide

Cyclosporine A as an immunosuppressive agent with brand name Gengraf developed by

Abbot, containing alcohol USP absolute, FD&C Blue No. 2, gelatin NF, polyethylene

glycol NF, polyoxyl 35 castor oil NF, polysorbate 80 NF, propylene glycol USP, Sorbitan

monooleate NF, and titanium dioxide excipients.

Kaletra, A SEDDS from Abbott comprising of Lopinavir and Ritonavir with gelatin,

glycerin, oleic acid, polyoxyl 35 castor oil, propylene glycol, sorbitol and titanium dioxide.


5

Aptivus as antiretroviral agent from Boehringer containing Tipranavir with the help of

polyethylene glycol 400, vitamin E polyethylene glycol succinate, purified water, and

propylene glycol.

1.4 Lipid Formulation Classification System

1.4.1 Lipid Formulations

Numbers of different technologies are available to help with formulation challenges, just

according to Romanski and Bush, lipid based drug delivery systems (LBDDS) is one of the

most commercially successful drug development technologies in the industry and

experience helped make more than 50 poorly soluble new chemical entities.

TABLE 1.1: Compositions of Lipid Based Formulation [23]

Composition

Type I Type II Type III Type IV

Oil Oil SEDDS

III A SEDDS

III B SMEDDS Oil Free

Glycerides (TG, DG, MG) 100% 40-80% 40-80% < 20% -

Surfactants (HLB < 12) - 20-60% - - -

(HLB > 12) - - 20-40% 20-50% 20-80%

Hydrophilic co-solvents - - 0-40% 20-50% 0-80%

Particle size of dispersion (nm) Coarse 100-250 100-250 50-100 < 50

Lipid based formulations have an excellent ability to solubilize hydrophobic compounds as

well as the possibility of protection for unstable compounds. Lipids can be used to target

the lymphatic system, thus bypassing the liver and avoiding first-pass metabolism.


6

Although they offer many advantages, LBDDS require a great deal of expertise and

knowledge of both expressions. The lipids used in drug formulations are generally derived

from natural ingredients; part of the body’s natural diet and this may be one of the reasons

for lipid excipients are so well tolerated. Lipid formulations require specific knowhow and

expertise. There are a variety of ways in which lipids can be used.

There are a variety of ways in which lipids can be used. The different lipid drug delivery

systems include microemulsion, nanoemulsion dry emulsion. Lipid formulation

classification system (LFCS) was established by Pouton in 2000 [23]. The LFCS briefly

classifies lipid based formulations into four types according to their composition and the

potential effect of dilution and digestion on their ability to prevent drug precipitation, as

indicated in Table 1.1.

1.4.2 Types of Lipid Formulations

Type I formulations generally made up with solubilized drugs in triglycerides and/or

mixed glycerides or in an oil/water emulsion stabilized by small amount of emulsifiers.

Broadly speaking such formulations show poor initial aqueous dispersion and need

digestion by pancreatic lipase in digestive system. Type I formulations are dependable

choices for drugs with adequate oil solubility.

Type II formulations are known as SEDDS. Type II formulations are built up of Oils and

water insoluble surfactants. SEDDS formed without water-soluble ingredients. Advantage

of type II formulation hasn't lost solvent capacity on dispersion, but from turbid dispersion.

They are isotropic mixtures of lipids, surfactants (HLB<12), co-surfactant and the drug

formulating oil/water emulsions under gentle agitation subsequent dilution with aqueous

phases. Self emulsification takes place by surfactants more than 25% (w/w) concentration.

As effective inactive ingredients have not appeared in FDA list, A Type II system has

narrow scope [24, 25].

Type III formulations are having oils, surfactants, cosolvents (both water-insoluble and

water-soluble excipients). They formed SEDDS/SMEDDS formed with water-soluble

components. These formulations formed generally clear dispersion and absorb the drug

without digestion. The type III formulation may lose solvent capacity on dispersion and

digestion is somewhat difficult. It is made up of oils, hydrophilic surfactants (HLB>12)


7

and co solvents such as PEG, PG and ethanol. Type III formulations are subdivided into

Type IIIA and Type IIIB. Type IIIB consists of higher concentration of hydrophilic

surfactants and Co solvents and smaller quantity of oil content, as compared to Type IIIA.

Type IIIB formulations produces drug precipitation on dispersions [24]. Neoral®

(Novartis) cyclosporine formulation is an model of Type III formulation.

Type IV formulations comprised of water-soluble surfactants and cosolvents. Formulation

disperses typically to form a micellar solution. Formulation has good solvent capacity for

many drugs, but likely loss of solvent capacity on dispersion; may not be digestible. Type

IV systems are fixed up of pure surfactants /mixtures of surfactants and co-solvents and are

likely to result in precipitation of the drug e.g. Agenerase® (GlaxoSmithKline) [26].

1.5 Biopharmaceutical Classification Systems

TABLE 1.2: BCS Classification

Class I - high permeability, high solubility

Those drugs are well absorbed and their absorption rate is usually higher than excretion.

Class II - high permeability, low solubility

The bioavailability of those drugs is limited by their solvation rate. A correlation between

the in vivo bioavailability and the in vitro solvation can be found.

Class III - low permeability, high solubility

The absorption is limited by the permeation rate but the drug is solvated very fast. If the

formulation does not change the permeability or gastro-intestinal duration time, then class I

criteria can be applied.

Class IV - low permeability, low solubility

These compounds have a poor bioavailability. Usually they are not well absorbed over the

intestinal mucosa and a high variability is expected.


8

Biopharmaceutical Classification System (BCS) was introduced in 1995 for predicting the

intestinal drug absorption provided by the U.S. Food and Drug Administration (FDA).

BCS is a useful tool for formulation development from a biopharmaceutical point of view

[27]. On the basis of drug solubility and intestinal permeability BCS catalogue the drugs

into four categories, as Table 1.2 [28-29].

The FDA has provided criteria regarding the solubility and permeability class boundaries

used for this BCS classification [24]. A drug is considered highly soluble when the highest

dose, strength is soluble in 250 ml or less of aqueous media with a pH range of 1 to 7.5 at

37°C. Permeability: A drug is considered highly permeable when the extent of absorption

in human beings is determined to be 90% or more of an administered dose based on mass

balance determination or in comparison to an intravenous reference dose [26].

1.6 Self Nano Drug Delivery System

Self-nanoemulsifying Drug Delivery System (SNEDDS) consists of isotropic mixture of

oil, surfactants and co-surfactants and have ability to form fine oil-in-water (O/W) nano

emulsions under mild agitation followed aqueous media [30]. SNEDDS produce globules

of size less than 100nm under dispersion of water [35]. Recently self emulsifying drug

delivery systems (SEDDS) are developed to enhance the water solubility of poorly water

soluble drugs [31]. SNEDDS are prepared by using medium chain triglycerides oils and

nonionic surfactant [32]. Dissolution rate is the rate determining step for absorption, the

SNEDDS is important for formulations which enhance drug absorption [33]. The SNEDDS

is one of the stable nano emulsions which provide a large interfacial area for partitioning of

drug between oil and aqueous phase having a safer pace of drug dissolution and enhance

bioavailability of drug [34]. The SNEDDS is thermodynamically stable and transparent/

translucent non-ionized dispersion of (o/w) and (w/o) emulsion. The SNEDDS is also

known as nanoemulsion, miniemulsion, ultrafine emulsion and submicron emulsion [35].


9

Various Components used for SNEDDS showed in Table 1.3.

TABLE 1.3: Components Used for SNEDDS

Oils used for SNEDDS

Medium chain triglycerides (C8-C10) normally used are triglycerides of caprylic/capric

acid, palm seed oil and fractionated coconut oil. Captex 355, Miglyol 812, 810 and Capmul

MC are some examples of available proprietary name.

Long chain triglycerides (C14-C22) are vegetable oils are glyceride esters of mixed

unsaturated long‐ chain fatty acids, commonly known as triglycerides e.g. olive oil

soybean oil, sesame oil and maize oil and so on.

Mixed mono, di and triglycerides used for SNEDDS are novel semisynthetic medium

and long chain derivatives. Esters of propylene glycol and mixture of mono and

diglycerides of caprylic/capric acid. These are Imwitor 988, Maisene 351 and Imwitor 308

etc.

Polar oils used for development of SNEDDS excipients which are traditionally thought of

as hydrophobic surfactants, such as sorbitan fatty esters e.g. Span 80 and 85.

Nonionic Surfactant

Water insoluble nonionic surfactants are oleate esters, such as polyoxyethylene (25)

glyceryl trioleate, poly oxyethylene (20) sorbitan trioleate, and PEG 6 Sorbitan oleate are

commonly used in the pharmaceutical industries. Available in the markets as Polysorbate

85 and Tween 85.

Water Soluble Nonionic Surfactants

Water soluble nonionic surfactants are the popular castor oil derivatives with saturated

alkyl chains resulting from hydrogenation of materials derived from a vegetable oil.

Other derivatives phospholipids. Proprietary name include polysorbate 80 which are


10

predominantly ether ethoxylates and brand available of the water soluble oils are

Cremophor RH40,Tween 20, Cremophor EL Tween 80, poloxamer 407, various Labrasols,

Labrafac Labrafils and Gelucires etc.

Cosolvents

Cosolvent: The most popular water soluble cosolvents are propylene glycol, polyethylene

glycol, ethanol and glycerol. Others are diethylene glycol monoethyl ether, alcohol,

polyethylene glycol, propylene carbonate, tetrahydrofurfuryl etc. Marketed products are

PG, PEG 300, PEG 400, 600, Transcutol and Glycofurol etc.

Other Excipients

Other excipients used for SNEDDS are oil soluble antioxidants mainly α Tocopherol,

β carotene and butylated hydroxytoluene (BHT) and so on.

1.6.1 Advantages of Self Nano Emulsifying Drug Delivery System

SNEDDS have a much larger surface area than SMEDDS [36].

SNEDDS is a better formulation technology for enhancing bioavailability [37].

The ability of SNEDDS to dissolve lipophilic drugs in great quantities and their ability

to protect the drugs from hydrolysis as well as enzymatic degradation makes them ideal

formulation for parenteral transport [38].

The SNEDDS gives ultra-low interfacial tension and large o/w interracial areas [39].

SNEDDS are formulated in a diversity of dosage form such such as liquids, foams,

sprays creams, balms and gels and it is used as nanoemulsion in pharmaceutical field as

well as utilized in drug delivery system such as oral, topical and parenteral nutrition

[40].

Self Nanoemulsifying Drug Delivery System is used for the number of applications in

medical specialty, food, beverages, cosmetics and it is as well employed for perfume

and pharmaceutical industries [41].

SNEDDS are used to improve the solubility of some plant components like ellagic acid.

The in vitro drug release from ellagic acid SNEDDS was found to be higher compared


11

to ellagic acid suspension and complex, while ex vivo studies showed increased

permeation from SNEDDS compared to suspension. [42].

Self nanoemulsifying drug delivery systems turned out to exhibit comparatively high

mucus permeating properties. [43].

They can be used for liquid as well as solid dosage forms.

SNEDDS helped in improving Cmax and oral bioavailability or therapeutic result of

various hydrophobic drugs. The improvement in bioavailability can be useful into

reduction in the drug dose and dose-related side effects of many drugs, such as

antihypertensive, antidiabetic drugs etc.

1.6.2 Selection of Excipients in Self-Emulsifying Formulations

Pharmaceutical acceptability of excipients is really critical. There is a great restriction for

selection of excipients to be used. Early studies reported that the self emulsification

process is definite to the nature of the oil/surfactant pair, the surfactant concentration and

oil/surfactant ratio, the concentration and nature of co surfactant and surfactant/co-

surfactant ratio and the temperature also have specificity for self emulsification occurs.

These important parameters were further confirmed by the fact that only very specific

combinations of pharmaceutical excipients led to efficient self emulsifying systems.

Self-emulsification depends on to the oil/surfactant; the surfactant concentration and

oil/surfactant ratio; and the temperature at which self-emulsification occurs [44].

The surfactant has immense effect on the emulsification process, nano-emulsifying region

and the size of droplets. Some of the properties that are to be taken care of i.e HLB in oil,

viscosity and affinity to the oil phase. Surfactants are selected along the base of the

emulsifying ability and this is done by incorporation of oil and surfactants under warming

conditions and then diluted with deionized water to form isotropic mixtures. Once

equilibrium obtained, transmittance can be determined using a spectrophotometer and

droplet size, PDI measured by Zeta Sizer. The surfactant amount influences the droplet

size of the emulsion. Some of them may cause irritation in GI mucosa and skin at higher

concentrations. The acceptability of the elements for the specific path of government

activity should also be considered as this may have some adverse effects. They can be used

independently or in combination.


12

1.6.3 Lipids, Surfactants, and Co Surfactant Used in Commercial Formulations

Lipids/Oils:

The oil is prime excipients in the self emulsifying system because it can solubilise higher

amounts of the hydrophobic drug, helps in self- emulsification and increase the

transportaion of lipophilic drug via the intestinal lymphatic system and hence increase

the absorption from the digestive tract [25]. Very few products have reached the

pharmaceutical market space because of the non availability of sufficient data regarding

the physical chemistry of lipids and chemical and physical stability. Fatty acid chain length

of the lipid also affects drug absorption [45]. Poor ability to dissolve large amounts of

lipophilic drugs by the edible oils makes oil less preferred excipient of choice for the

development of SEDDS. Modified or hydrolyzed oil components used much because these

oils form good emulsification with most of surfactants approved and showed superior

drug solubility properties [46]. Novel semi synthetic medium chain derivatives, with

surfactant properties, are used instead of the triglyceride oils in the SEDDS [47].

The drug absorption affected by the lipid content in a formulation via solubilization in the

GIT and potentially by activation of GI lipid digestion consequential rise in secretion of

pancreatic juice and bile [48].

Surfactants:

Several excipients having surfactant properties may be used for the purpose of SEDDS,

non-ionic surfactants with high hydrophilic-lipophilic balance (HLB) suggested widely.

Normally emulsifiers are various solid or liquid ethoxylated polyglycolyzed glycerides and

Polysorbate 80. Natural surfactants are selected because they are believed to be more

dependable than the synthetic surfactants [49, 50]. Nevertheless, these excipients have a

determined self emulsification competence.

Nonionic surfactants are safer as they are less toxic than ionic surfactants but they may

lead to reversible changes in the permeability of the intestinal lumen [50]. Normally the

concentration ranges of surfactant between 30 and 60% w/w in order to form stable

SEDDS. It is rattling significant to find out the surfactant concentration properly because

large quantities of wetting agents may cause GI irritation. The surfactant involved in the

formulation of SEDDS should have a relatively high HLB and hydrophilicity so that


13

immediate formation of o/w droplets and/or rapid spreading of the expression in the

aqueous media can be achieved.

The droplet size depends on the absorption of the surfactant being used. In some events,

increasing the surfactant concentration could lead to droplets with smaller mean droplet

size as in the lawsuit of a variety of saturated C8-C10 polyglycolized glycerides. This

could be excused by the stabilization of the oil droplets as a consequence of the location of

the surfactant molecules at the petroleum-water interface. On the other hand, in some cases

the average droplet size may increase with increasing surfactant concentrations [52]. This

incident could be ascribed to the interracial disruption elicited by enhanced water

penetration into the oil droplets mediated by the increased surfactant concentration and

leading to ejection of oil droplets into the aqueous phase.

Co-surfactants:

Generally high concentrations of surfactants (more than 30% w/w) are needed for the

production of an optimum SEDDS. Propylene glycol, ethyl alcohol and polyethylene

glycol are appropriate solvents for oral formulation and they facilitate the fragment of

the large amount either of the hydrophilic surfactant or the drug in the lipid base.

conversely, alcohols and other volatile co-solvents have the drawback of evaporating

into the shields of the capsules in conventional SEDDS promoting drug precipitation

[25]. Hence formulations free from alcohol have been developed. More usually it has been

supposed that cosolvents could increase the solvent ability of the formulation for drugs.

Even so, to enhance the solvent capacity, the solvent must be there at elevated

concentration and this may cause drug precipitation when the formulation is dispersed in

water. A third reason for incorporation of cosolvents is to help dispersion of systems which

contain a high proportion of water soluble surfactants.

1.6.4 Mechanism of SEDDS

Self-emulsification mechanism is not yet well understood thoroughly. Reiss et al [53] has

indicated that self-emulsification occurs when the entropy change favouring dispersion is

larger than the vigor needed to increase the open region of the dispersion.


14

The free energy of a conventional emulsion formulation is a direct part of the vigour

needed to create a new surface between the petroleum and water phases. Following

equation described the thermodynamic relationship for the net free energy change.

∆G = ΣNiπri

Where ∆G - the free energy associated with the process;

N - The number of droplets

r - The radius of globules

σ- The interfacial energy

The two phases of emulsion to detach with time to reduce the interfacial area and

subsequently the emulsion is stabilized by emulgents which form a monolayer

of emulsion droplets, and hence reduces the interfacial energy, as well as providig

barrier to prevent coalescence.

On the other hand, emulsification occurs spontaneously with SEDDS, as the free energy

taken to form the emulsion is low, whether positive or negative [47]. In the emulsification

process, there should be trifling or no resistance against surface shearing for the interfacial

structure [54]. The water penetration into various liquid crystals or gel phases formed on

the airfoil of the droplet makes emulsification easy [55, 56]. The interface between the

lipid and aqueous continuous phases is formed when oil/non-ionic surfactant added to

water [55]. This is followed by solubilization within the oil phase. Dispersed liquid crystal

phase formed as a solution of aqueous penetration. Finally, everything that is in close

propinquity to the interface will be liquid crystal, the actual sum of which depends upon

the emulsifier concentration in the binary mixture. Hence, following gentle agitation of the

self-emulsifying system, water quickly penetrates into the aqueous cores leading to

interface disruption and droplet formation.

The liquid crystal interface formation produces surrounding the oil droplets, the SEDDS

become fairly stable. Moreover, the comportment of the drug may modify the emulsion

characteristics. However, the correlation between the liquid crystal formation and

spontaneous emulsification has still not been properly established [57-59].


15

1.7 Concept of Nanoemulsions within Lipid Based Formulation

Nanoemulsion system was produced almost four decades ago. In simple term,

nanoemulsions are the emulsions made up of globules having size in nano meter. SNEDDS

are usually well distributed, transparent and kinetically stable system for months. SNEDDS

can be made thermodynamically stable by appropriate selection of surfactants and the ratio

of oil/water/surfactant.

SNEDDS are comprised of components, mainly a simple mix of oils, surfactants and may

have co-solvents. SNEDDS develop nano sized globules while SMEDDS have the capacity

to form fine O/W micro sized emulsion upon gentle agitation in the G.I.Tract [60].

The structure developed by SNEDDS is the best system for oral dosage form, especially

for hydrophobic drugs with superior solubility in oil only or oil/surfactant. Upon dilution,

SMEDDS makes transparent micro sized emulsions while the transparent dispersion

system made by SNEDDS of oil and water made by surfactants, having droplet sizes in the

range of 20 and 250 nm and kinetically stable systems [61].

SNEDDS need high energy input for their preparation. SNEDDS can be projected by low

concentration of surfactant to oil ratio than SMEDDS.

1.7.1 SNEDDS within Lipid Formulation Classification Systems

Potion [62] has given the concept of a lipid formulation classification system (LFCS) into

Types I–IV. These four types of the lipid system were separated along the basis of

formulation compositions, drug precipitation, effects of lipid digestion aqueous

dispersibility. Type III systems are the most prominent system as they give SNEDDS

within the range from 0–250 nm particle sizes upon dispersion. Type III further subdivided

into IIIA and IIIB according to the hydrophilic content of the SNEDDS. SNEDDS of Type

IV system have high drug loading capacity.

1.7.2 Solidification of SNEDDS

The excipients normally used in SNEDDS are liquid at room temperature, and they are

well-suited to solid and semi solid dosage forms fit them for oral dosage formulation. The

interaction between SNEDDS and the scale of the capsule may result in brittleness or


16

softness of the scale makes a challenge for pharmaceutical industry [63]. In accession to

that, leaching and rancidity could be another major problem in formulating liquid filled

soft gelatine capsules. Thus, to tackle this limitation, SNEDDS should be changed into a

strong formulation. Liquid formulations could be changed into suitable free flowing fine

powder by adsorbing the SNEDDS on a suitable solid carrier as solid SNEDDS [64, 65].

1.7.3 Equilibrium Solubility of Diluted SNEDDS

For SNEDDS, drug loading capacity can be decided by drug solubility and is more when

the drug is highly lipophillic or when the product contains a concentration of surfactant or

co-solvent. The solubility of the SNEDDS may reduce when excipients are dispersed and

digested in the digestive system. To experience this fate of the drug on dispersion, its

solubility study in aqueous media done by dilution method. The shake flask method

adopted for the solubility study to limit the solubility of SNEDDS.

1.7.4 Drug Release and the Justification of Dispersion Test For Nanoformulations

In vitro drug release studies decide the ability of SNEDDS to disperse into various types of

media. It can guess how much drug will be in solution before it gets absorbed from GI tract

[66, 67].

1.7.5 Mechanism of Drug Supersaturation: Role of SNEDDS

SNEDDS, when entered in the gastric fluid of GI tract, due to the elevated amount of

surfactant/water soluble cosolvent generates supersaturation. Supersaturation in the gastric

fluid is an unwanted process therefore; SNEDDS should be prepared to minimize

supersaturation. SNEDDS, if created by major proportions of water soluble surfactants or

cosolvent produce supersaturation. In some cases, during digestion drug precipitation may

take place. In recent studies, precipitation inhibitors have been incorporated in SNEDDS to

inhibit the risk of precipitations [68].

1.8 Lipid digestion and drug absorption: Mechanism

1.8.1 Lipid Metabolism

Gastric lipase helps in the digestion of SNEDDS when it is initially dispersed in the

stomach. Gastric lipase has the ability to raise 15% of spare fatty acids from lipids [69].


17

Pancreatic lipase with its co-lipase completes the breakdown of lipid present in oral

formulation. Lipids in SNEDDS also stimulate secretion of endogenous biliary lipids in the

intestine, including bile salt, phospholipid and cholesterol from the gallbladder [69]. In the

presence of high level of bile salts, lipid digestion products are later transformed into

colloidal structures.

1.8.2 Drug Absorption

Adequate aqueous solubility and superior intestinal permeability assist in drug absorption,

which contributes to improvement in bioavailability of drugs. SNEDDS are better

absorption enhancer option for poorly water soluble drugs, when given orally [70].

Probable mechanisms for improving drug absorption from SNEDDS include:

Membrane fluidity improvement facilitates transcellular absorption

Larger surface area of SNEDDS globule, hydrolysis and the constitution of mixed

micelles, Paracellular transport by opening junction

Inhibition of P-gp and/or CYP450 to boost intracellular concentration and residence

time, and Stimulation of lipoprotein/chylomicron production.

This is may be a mechanism of absorption of drugs with log P values >6.0 [71, 72].

1.9 In Vitro - In Vivo Correlation (IVIVC) for Lipid Nanoformulations

In formulation development for the optimization of suitable formulations the IVIVCs play

an significant part. Optimization of formulation required modifications in composition,

apparatus, process and size of the batch. When such changes done, the in vivo

bioequivalence studies to be performed to demonstrate the similarity of the novel

formulation.

All the same, there are smaller numbers of IVIVC studies so far have been done for lipid

formulations. To prevail better in vitro and in vivo relationship, a great bit of drugs should

be considered along with human clinical data sets and complete characterizations of in

vitro and in vivo solubilization of PWSDs formulated in lipid.


18

1.10 Summary of SNEDDS

For drugs with reduced aqueous solubility, SNEDDS technology provides influential and

efficient answer to develop their solubility in the aqueous medium of the GI tract. The

most significant step in formulating the SNEDDS is choice of the most suitable oil,

surfactant and/or cosolvent so the SNEDDS must keep a balance and make compatibility

between the self emulsification efficiency, drug loading capacity, droplet size distribution,

in vitro dispersion/release profile. In summary, SNEDDS grant a strong formulation to

boost GI solubilization and to encourage drug absorption. If there is a successful IVIVC

made for lipid nanoformulations, assurance in the evolution of the SNEDDS and its tone is

likely to acquire more serious.

SNEDDS spread easily in the GI tract, and the motility of the stomach and the intestine

adds the agitation essential for self-emulsification. When SNEDDS compared with

emulsions which are responsive and metastable dispersed forms, SNEDDS are physically

stable formulations that are easy to produce. So, for hydrophobic drug compounds which

exhibit dissolution rate-limited absorption, these techniques may offer enhancement in the

rate and extent of absorption and result in more reproducible bioavailability.

1.11 Rationale for Lercanidipine HCL SNEDDS

Lercanidipine HCL is used in hypertension treatments [73]. The drug is administered

orally at a dose of 10–20 mg daily, reducing diastolic blood pressure appreciably [74].

After oral administration, Lercanidipine is completely and erratically absorbed from the

gastrointestinal tract. Nevertheless, absolute bioavailability is reduced to approximately

10% because of extensive first pass metabolism to its inactive metabolites [74]. The

literature suggests the mean half-lives of 2.8 and 4.4 h in humans after single dose

oral administration of 10 and 20 mg of Lercanidipine respectively [75]. These

pharmacokinetics parameters makes Lercanidipine a appropriate prospect for advance of

SNEDDS formulation to enhance oral bioavailability. Thus development of self-

emulsifying drug delivery systems will serve to enhance its aqueous solubility and also

produce better lymphatic transport that may result in more amount of drug entering into

systemic circulation, producing its oral bioavailability. Thus development of self-


19

emulsifying drug delivery systems will serve to improve its aqueous solubility and also

improves lymphatic transport that may result in more amount of drug entering into

systemic circulation, improving its oral bioavailability. SEDDS can be administered as a

unit dose by filling into hard gelatin capsules and sealing such that dosage uniformity can

be maintained [74].

1.12 Rationale for Cinacalcet HCL SNEDDS

Calcium receptor-active compounds are known in the artistic creation. One instance of a

calcium receptor-active compound is Cinacalcet HCL, which is described, for exemplar, in

U.S. Patent No. 6,001,884. Such calcium receptor-active compounds may be insoluble or

sparingly soluble in water, particularly in their nonionized state. For example, Cinacalcet

has solubility in water of less than about 1 µg/ml at neutral pH. The solubility of

Cinacalcet can reach approximately 1.6 mg/ml when the pH runs from around 3 to nearly

5. Nevertheless, when the pH is about 1, the solubility decreases to approximately 0.1

mg/milliliter. Such limited solubility can reduce the number of formulation and delivery

choices available for these calcium receptors-active compounds. Limited water solubility

can also result in low bioavailability of the compounds [76].

Cinacalcet HCL is a white to off-white, crystalline solid soluble in methanol or 95%

ethanol, but only slightly soluble in water. As such, the dissolution rate and bioavailability

of known cinacalcet formulations are not optimal. The effectiveness of Cinacalcet may be

enhanced if it could be formulated to be taken without food, thus decreasing the likelihood

of patient compliance problems. Furthermore a formulation that enhances the

bioavailability of cinacalcet would facilitate reduction of the dosage strength with the

possibility of achieving a better safety profile [77].

1.13 Objectives of the Work

The primary aim of this study is to prepare SNEDDS for oral solubility and

bioavailability enhancement of poorly water soluble drugs of Lercanidipine HCL

and Cinacalcet HCL.

To develop self-Nanoemulsifying drug delivery system (SNEDDS) of poorly

soluble BCS Class II drugs.


20

To choose the most suitable vehicle and to study pseudo ternary phase diagram

behavior to find a nanoemulsion area in SNEDDS containing drug.

To study physicochemical properties of self nano emulsifying drug delivery

system.

To enhance the solubility, diffusion rate of drugs using suitable vehicles and

excipients.

To compare the diffusion rate of optimized liquid SNEDDS with marketed

formulation.

To perform the stability study of the optimized SNEDDS formulation.

1.14 Profile of Selected Drugs

1.14.1 Profile of Lercanidipine HCL

High blood pressure is a major contributor to global ailment burden, occurring as an

dangerous supplement to aging populations [78, 79]. Lercanidipine is a lipophilic,

dihydropyridine calcium antagonist with a long receptor half-life. Its slow onset of natural

process helps to avoid reflex tachycardia associated with other dihydropyridines (DHPs).

Preclinical and preliminary clinical findings suggest Lercanidipine may have good effects

on coronary artery disease and left ventricular hypertrophy. The effectiveness and

tolerability profiles of Lercanidipine make it a desirable option for treating hypertension in

a wide scope of affected patients. Antihypertensive drugs are well known to prevent

cardiovascular morbidity and mortality. The major antihypertensive drug classes are

entirely effective at lowering blood pressure [80]. Calcium antagonists are a heterogeneous

group of established antihypertensive agents that is used in hypertension treatments [81].

The drug is administered orally at a dose of 10–20 mg daily, reducing significantly the

diastolic blood pressure [82]. After oral administration, Lercanidipine is completely and

erratically absorbed from the gastrointestinal tract [83].

Drug Name: Lercanidipine HCL

Physicochemical properties:

CAS Registry Number: 132866-11-6

Structure:


21

Appearance: Lercanidipine HCL (a crystalline form) is a yellow powder, soluble in

methanol and practically insoluble in water.

Description: Lercanidipine is a dihydropyridine derivative. It is a racemate due to the

presence of a chiral carbon atom at position 4 of the 1, 4- dihydropyridine ring.

Category: A calcium channel protein inhibitor

BCS class: Class II drug

IUPAC Name::5-O-[1-[3,3-diphenylpropyl(methyl)amino]-2-methylpropan-2-yl] 3-

O-methyl 2, 6-dimethyl- 4- (3-nitrophenyl)- 1, 4-dihydropyridine -3, 5 - dicarboxylate;

hydrochloride

Solubility: Soluble in DMSO (100 mM), ethanol (10 mM), water (partly), chloroform,

and methanol

Mol. Formula: C36H41N3O6 HCL

pKa Values: 8.4 (Predicted)

Melting Point:195-198 °C

Mol. Weight: 648.19

LogP (Base): 6.42 ALOGPS

Half-life: 8-10 h


22

Mechanism of Action:

It is a calcium antagonist of the dihydropyridine group and inhibits the transmembrane

influx of calcium into cardiac and smooth muscles. The mechanism of its antihypertensive

action is due to a direct relaxant effect on vascular smooth muscle thus lowering total

peripheral resistance

Pharmacodynamics:

Preclinical studies show Lercanidipine is highly selective for vascular tissue and produces

smooth muscle relaxation through competitive binding to L-type calcium channels. It is

highly lipophilic and is stored within cell membranes, which explains its slow onset of

action and persistent smooth muscle relaxant effect [81]. Lercanidipine (10 mg/day)

produces a smooth antihypertensive effect without unfavorable hemodynamic or

sympathetic effects [84].

Pharmacokinetics [85]:

Absorption

Lercanidipine is completely absorbed after oral administration. Peak plasma levels of

3.30ng/mL ± 2.09 SD and 7.66 ng/ml ± 5.90 s.d occur 1.5-3 hours after dosing with 10mg

and 20mg, respectively.

The absolute bioavailability of Lercanidipine is about 10%, because of high first pass

metabolism. The bioavailability increases 4-fold when Lercanidipine is ingested up to 2

hours after a high fat meal, and about 2-fold when used up directly after a carbohydrate-

rich repast. Consequently, Lercanidipine should be taken at least 15 minutes before a meal.

With oral administration, Lercanidipine exhibits non-linear kinetics. After 10, 20 or 40mg,

peak plasma concentrations observed were in the ratio 1:3:8 and areas under plasma

concentration-time curves in the ratio 1:4:18, showing a progressive intensity of first pass

metabolism. Accordingly, bioavailability increases as dosage increases.


23

Distribution

Distribution of Lercanidipine from plasma to tissues and organs is rapid and extensive.

Serum protein binding exceeds 98%. The level of free fraction of Lercanidipine increased

in patients with kidney or hepatic impairment

Metabolism

As for other dihydropyridine derivatives, Lercanidipine is extensively metabolized by

CYP3A4. It is predominantly converted to inactive metabolites; no parent drug is found in

the urine or feces. About 50% of the dose is excreted in the urine.

Elimination

The mean terminal elimination half-life of S and R enantiomers are 5.8 ± 2.5 and 7.7 ± 3.8

hours, respectively. No accumulation was seen upon repeated administration. The

therapeutic activity lasts for 24 hours, due to its high binding to lipid membranes.

Elderly patients

In elderly patients, the pharmacokinetic of Lercanidipine is similar to that observed in the

general population.

Hepatic Impairment

A study in patients with mild hepatic impairment (Child-Pugh class A) showed that the

pharmacokinetics behavior of the drug is similar to that observed in the general population.

No studies have been undertaken in patients with moderate or severe hepatic impairment.

Renal impairment

In patients with severe renal dysfunction (creatinine clearance < 12mL/min) or dialysis-

dependent patients, plasma levels were increased by about 70%. As a consequence, the

drug should be contraindicated in severe renal impairment.

Indications

Lercanidipine is indicated for the treatment of mild to moderate hypertension.


24

Contraindications

Hypersensitivity to any dihydropyridine or any ingredient of Lercanidipine HCL. Severe

hepatic impairment; severe renal impairment (creatinine clearance < 12 ml/min).

Concomitant treatment of Lercanidipine with cyclosporin should be avoided

Interactions with other Medicines

Lercanidipine has been safely administered with diuretics and ACE inhibitors. It may also

be administered safely with beta-blockers, which are eliminated unchanged (such as

atenolol). The recommended dose is 10mg once daily, at least 15 minutes before a meal.

The dose may be increased to 20mg once daily depending on the individual response.

1.14.2 Profile of Cinacalcet HCL

Cinacalcet HCL is used for the treatment of hypercalcemia in patients with parathyroid

carcinoma or for secondary hyperparathyroidism in patients with chronic kidney disease

who are on dialysis [86].

Name: Cinacalcet HCL

CAS number: 226256-56-0

Physicochemical properties [87]:

Description: The hydrochloride salt of Cinacalcet is a white to off-white, crystalline solid

and soluble in methanol or 95% ethanol and slightly soluble in water.

Chemical name: Cinacalcet hydrochloride; 364782-34-3; Cinacalcet HCL; Sensipar;

Mimpara; (R) -N-(1-(Naphthalen-1-yl) ethyl) -3-(3-(trifluoromethyl) phenyl) Propan-1-

amine hydrochloride.

IUPAC Name: N-[(1R) -1-naphthalene-1-ylethyl] -3-[3-(trifluoromethyl) phenyl] Propan-

1-amine; hydrochloride

Molecular formula: C22H23ClF3N

State: Solid


25

Molecular weight: 393.878 g/Mol

Solubility: In water, 9.2X10-2 mg/L at 25 deg C /Estimated/5.59e-05 mg/ml

pKa = 8.4 /Estimated/

Log P: 6.27 [88]

Structure:

Mechanism of Action:

Cinacalcet HCL is a type II calcimimetic drug with a novel mechanism of action [86, 89].

It binds to the transmembrane region of the calcium-sensing receptor, which leads to a

different structural configuration that is more sensitive to serum calcium. Unlike vitamin D

sterols, Cinacalcet does not increase serum calcium levels; as a result, adverse effects

associated with hypercalcemia can be averted. Cinacalcet HCL works on parathyroid

glands. It causes them to release less PTH (parathyroid hormone) and when the PTH level

goes down, less calcium and phosphorus are released from your bones [90].

Pharmacodynamics [86]:

Reduction in intact PTH levels correlated with the plasma Cinacalcet concentrations in

patients with chronic kidney disease. The intact PTH level occurs approximately 2 to 6

hours, post dose, corresponding with the maximum plasma concentration (Cmax) of

Cinacalcet. After steady-state Cinacalcet concentrations are reached (which occurs within

7 days of dose change), serum calcium concentrations remain constant over the dosing

interval in patients with CKD.


26

Pharmacokinetics [86]:

Absorption: After oral administration of Cinacalcet, it takes 2 to 6 h to attain the

maximum plasma concentration. Food affects both C max and the area under the curve

(AUC) affected by food.

Distribution: Distribution of Cinacalcet is consistent with the two-compartment

pharmacokinetic model. It takes 7 days to to acheived steady-state as the half-life is 30

to 40 hours.Distribution: Cinacalcet is highly protein bound. The volume of

distribution is 1000 L.

Metabolism: Cinacalcet is metabolized by CYP3A4, CYP2D6, and CYP1A2.

Excretion: 80% of the metabolites are excreted by renal.

Dosing and Administration [86]:

Secondary hyperparathyroidism in patients receiving hemodialysis

Suggested initial dose of Cinacalcet is 30 mg orally once daily. The dose can then be

gradually increased in 30 mg increments In the treatment of secondary

hyperparathyroidism suggested maximum daily dose is 180 mg/day. It is required to

check PTH levels for 1 to 4 weeks after dose initiation or dosage adjustment.

Parathyroid carcinoma

The proposed initial dose of Cinacalcet is 30 mg orally twice daily.

Special treatment populations

Pregnancy/lactation

Cinacalcet is classified as pregnancy category C.

Drug Interactions

Many drug interactions can potentially occur Since Cinacalcet is metabolized by

CYP3A4, CYP2D6, and CYP1A2. In cases of simultaneous therapy with medications

metabolized by CYP3A4 (e.g., erythromycin, ketoconazole and itraconazole, and), the


27

patient should be observed closely. Dosage adjustment may be necessary. Potent

inhibitors of CYP3A4 such as ketoconazole can increase the cinacalcet concentration

by 2.3 times.

Contraindications

Treatment initiation is contraindicated if serum calcium is less than the lower limit of

the normal range.

Dosage Forms:

Cinacalcet is commercially available as 30-mg, 60-mg, or 90-mg tablets.

1.15 Profile of Excipients

1.15.1 Polysorbate 80[91]:

CAS Registry number: 9005-65-6

Non-proprietary Name

BP: Polysorbate80

JP: Polysorbate80

Ph Eur: Polysorbate80

USP-NF: Polysorbate80

Synonym: Capmul POE-O; CremophorPS80; Crillet4; polyoxyethylene 20 oleate;

polysorbatum 80 and Tween80.

Empirical Formula: C64H124O26

Molecular weight: 1310 g/mol

Chemical names and CAS Registry Number: Polyoxyethylene 20 Sorbitan mono

oleate, [9005-65-6]

Functional Category: Dispersing agent ; emulsifying agent ; nonionic surfactant ;

solubilizing agent ; suspending agent ; wetting agent


28

Odor: Characteristic odor

Taste: Bitter taste

Colour and Physical form at 25 ˚ C: Yellow oily liquid

TABLE 1.4: Solubility of Polysorbate 80 in Various Solvents

Ingredient Solvents

Tween 80 Ethanol Mineral oil Vegetable oil Water

Soluble Insoluble Insoluble Soluble

Functional Category: Dispersing agent; emulsifying agent; nonionic surfactant;

solubilizing agent; suspending agent; wetting agent.

TABLE 1.5: Typical Properties of Polysorbate 80

HLB value Acid value

(%)

Hydroxyl

Value

Moisture

content

Specific Gravity at

25 ˚ C

Viscosity

(mPa s)

15.0 2.0 65-80 3.0 1.08 425

Incompatibilities:

Discoloration and / or precipitation occur with various substances, especially phenols,

tannins, tars, and tar like materials. The antimicrobial activity of paraben preservatives is

reduced in the presence of polysorbates.

Storage and stability:

Polysorbates are stable to electrolytes and weak acids and bases; gradual saponification

occurs with strong acids and bases. The oleic acid esters are sensitive to oxidation.

Polysorbates are hygroscopic and should be examined for water content prior to use and

dried if necessary. Also, in common with other polyoxyethylene surfactants, prolonged

storage can lead to the formation of peroxides. Polysorbates should be stored in a well-

closed container, protected from light, in a cool, dry place.


29

1.15.2 Polyethylene Glycol 400[91]:

Nonproprietary Names

BP: Macrogols ,JP: Macrogol400 ,PhEur: Macrogols ,USP-NF: Polyethylene Glycol

Synonyms: Carbowax; Carbowax Sentry; Lipoxol; Lutrol E; macrogola; PEG; Pluriol E

and polyoxyethylene glycol.

Empirical formula: HOCH2(CH2OCH2)8.7CH2OH

Molecular weight: 380-420 g/mol

Chemical Name and CAS Registry Number: α-Hydro-ω-hydroxypoly (oxy-1,2-

ethanediyl) , [25322-68-3]

Functional Category: Polyethylene glycols (PEGs) are widely used in a variety of

pharmaceutical formulations, emulsion stabilizers, parenteral, topical, ophthalmic, oral,

and rectal preparations.

Odor: characteristic

Taste: Bitter

Colour and Physical form at 25 ˚ C: Colourless liquid

TABLE 1.6: Solubility of PEG 400 in Various Solvents

Ingredient Solvents

PEG 400

Water Acetone Alcohols Benzene Glycerin Glycols

Soluble


30

TABLE 1.7: Typical Properties of PEG 400

HLB

value

Hydroxyl

Value

Freezing

point

Density pH (5% w/w

solution)

Viscosity

(mPa s)

16 264-300 4-8˚c 1.120 4.0-7.0 105-130

1.15.3 Transcutol P [92]:


Molecular weight: 134.17g/mol

Chemical Names: EP and USP NF: Purified diethylene glycol monoethyl ether

Functional Category: solubilizer, as oily vehicle

Odor: Faint

Colour and Physical form at 25 ˚ C: Colorless liquid.

TABLE 1.8: Typical Properties of Transcutol P

Water content Refractive index at 20 ˚C

<0.10% 1.426-1.428

Functional Category: A high purity solvent and solubilizer for poorly water soluble active

pharmaceutical ingredients. It is associated with improved drug penetration, permeation.

1.15.4 Capmul MCM [93]:


Molecular weight: 218.29g/mol


31

Chemical names and CAS Registry No.: Monoglyceride of capylic acid, [26402-26-2]

Functional Category: solubility, surfactant

Odor: Faint

Colour and Physical form at 25 ˚ C: Colorless liquid/semi solid.

TABLE 1.9: Typical Properties of Capmul MCM

Hydroxyl value Water content Saponification value Solubility

324-396 1.00% 252-308 mg KOH/g Slightly water soluble

Storage:

Keep away from heat and flame. Store in a dry area.

1.15.5 Polysorbate 20[91]:

Nonproprietary Name

BP: Polysorbate 20

JP: Polysorbate 20

Ph Eur: Polysorbate 20

USP-NF: Polysorbate 20

Synonym: PEG (20), sorbitan monolaurate, polyoxyethylenesorbitan monolaurate and

Tween20.


Molecular weight: 1,225 daltons

Chemical names and CAS Registry Number:

Polyoxyethylene (20) sorbitan monolaurate, [9005-64-5]

Functional Category: Dispersing agent ; emulsifying agent ; nonionic surfactant ;

solubilizing agent ; suspending agent ; wetting agent


32

Colour and Physical form at 25 ˚ C: Clear, yellow to yellow-green viscous liquid

Solubilities of Polysorbate 20 in various solvents:

Polysorbate 20 is miscible in water (100 mg/ml), yielding a clear, yellow solution.

It is also miscible with alcohol, dioxane, and ethyl acetate. It is practically insoluble in

liquid paraffin and fixed oils.

TABLE 1.10: Typical Properties of Polysorbate 20

HLB

value

Acid value

(%)

Hydroxyl

Value

Specific Gravity

at 25 ˚C

Viscosity

16.7 2.0 96 – 108 1.1 370-430 cps (250C, neat)

1.16 References

1. Humberstone, A. J., & Charman, W. N. (1997). Lipid-based vehicles for the oral

delivery of poorly water soluble drugs. Adv Drug Deliv Rev, 25 (1), 103-128., 0169-

409X

2. Aungst, B. J. (1993).Novel formulation strategies for improving oral bioavailability of

drugs with poor membrane permeation or presystemic metabolism. J Pharm Sci, 82(10),

979-987., ISSN:0022-3549.

3. Savjani, K. T., Gajjar, A. K., & Savjani, J. K. (2012). Drug Solubility: Importance and

Enhancement Techniques. ISRN Pharmaceutics, 2012, 10. ISSN: 2090-6153.

4. Weuts, I., Kempen, D., Decorte, A., Verreck, G., Peeters, J., Brewster, M., & Van den

Mooter, G. (2004). Phase behaviour analysis of solid dispersions of loperamide and two

structurally related compounds with the polymers PVP-K30 and PVP-VA64. European

Journal of Pharmaceutical Sciences, 22(5), 375-385., ISSN: 0928-0987


33

5. Ammar, H. O., Salama, H. A., Ghorab, M., & Mahmoud, A. A.(2006).Implication of

inclusion complexation of glimepiride in cyclodextrin–polymer systems on its

dissolution, stability and therapeutic efficacy. International Journal of Pharmaceutics,

320(1), 53-57., ISSN: 0378-5173.

6. Odeberg, J. M., Kaufmann, P., Kroon, K.-G., & Höglund, P. (2003). Lipid drug delivery

and rational formulation design for lipophilic drugs with low oral bioavailability,

applied to cyclosporine. European Journal of Pharmaceutical Sciences, 20(4), 375-

382., ISSN: 0928-0987.

7. Balakrishnan, P., Lee, B. J., Oh, D. H., Kim, J. O., Lee, Y. I., Kim, D. D., . . . Choi, H.

G. (2009).Enhanced oral bioavailability of Coenzyme Q10 by self-emulsifying drug

delivery systems. International Journal of Pharmaceutics, 374(1-2), 66-72.,

ISSN: 0378-5173.

8. Pouton, C. W. (2000). Lipid formulations for oral administration of drugs: non-

emulsifying, self-emulsifying and 'self-microemulsifying' drug delivery systems. Eur J

Pharm Sci, 11 Suppl 2, S93-98., ISSN: 0928-0987.

9. Rajendra C., Harish P. Jain A.K., Himesh S., Saraogi G.K.(2011). Preparation and

evaluation of the self-emulsifying drug delivery system containing atorvastatin

HMGCOA inhibitor. International Journal of Pharmacy and Pharmaceutical Sciences,

3 (3): 147-152., ISSN- 0975-1491.

10. Lipinski, C. A. (2000).Drug-like properties and the causes of poor solubility and poor

permeability. J Pharmacol Toxicol Methods, 44 (1), 235-249., ISSN: 1056-8719.

11. Ghose, A. K., Viswanadhan, V. N., & Wendoloski, J. J. (1999).A Knowledge-Based

Approach in Designing Combinatorial or Medicinal Chemistry Libraries for Drug

Discovery. 1. A Qualitative and Quantitative Characterization of Known Drug

Databases. Journal of Combinatorial Chemistry, 1 (1), 55-68., ISSN: 2156-8952.

12. Shahba, A. A. -W., Mohsin, K., & Alanazi, F. K. (2012). Novel Self-Nanoemulsifying

Drug Delivery Systems (SNEDDS) for Oral Delivery of Cinnarizine: Design,

Optimization, and In-Vitro Assessment. AAPS PharmSciTech, 13 (3), 967-977., ISSN:

1530-9932.


34

13. Sven S., Hassan B., Thilo S., Martin O. (2009). Self-Emulsifying Drug Delivery

Systems Facing the bioavailability challenge in drug delivery. Die Pharmazeutische

Industrie, 71(8):1409-1416., ISSN 0031-711X.

14. Gursoy, R. N., & Benita, S. (2004). Self-emulsifying drug delivery systems (SEDDS)

for improved oral delivery of lipophilic drugs. Biomed Pharmacother, 58 (3), 173-182.

ISSN: 0753-3322.

15. Stegemann, S., Leveiller, F., Franchi, D., de Jong, H., & Linden, H. (2007). When poor

solubility becomes an issue: from early stage to proof of concept. Eur J Pharm Sci,

31(5), 249-261., ISSN: 0928-0987.

16. Perlman, M. E., Midland, S. B., Gumkowski, M. J., Shah, T. S., Rodricks, C. M.,

Thornton-Manning, J., . . . Erhart, L. C. (2008). Development of a self-emulsifying

formulation that reduces the food effect for torcetrapib. Int J Pharm, 351(1-2), 15-22.,

ISSN: 0378-5173.

17. Mohsin, K., Long, M. A., & Pouton, C. W. (2009). Design of lipid-based formulations

for oral administration of poorly water-soluble drugs: precipitation of drug after

dispersion of formulations in aqueous solution. J Pharm Sci, 98(10), 3582-3595., ISSN:

0022-3549.

18. Duro, R., Souto, C., Gómez-Amoza, J. L., Martínez-Pacheco, R., & Concheiro, A.

(1999). Interfacial Adsorption of Polymers and Surfactants: Implications for the

Properties of Disperse Systems of Pharmaceutical Interest. Drug Development and

Industrial Pharmacy, 25 (7), 817-829., ISSN: 0363-9045.

19. Floyd, A. G. (1999).Top ten considerations in the development of parenteral emulsions.

Pharm Sci Technolo Today, 4 (2), 134-143., ISSN: 1461-5347.

20. Tarr, B.D. and Yalkowsky, S.H., (1989).Enhanced intestinal absorption of

cyclosporine in rats through the reduction of emulsion droplet size. Pharm Res 6: 40-

43., ISSN: 0724-8741.

21. Zanchetta B, Chaud MV, Santana MHA., (2015).Self-Emulsifying Drug Delivery


35

Systems (SEDDS) in Pharmaceutical Development. J Adv Chem Eng 5:130., ISSN:

2090-4568.

22. Mohsin, K., Long, M. A., & Pouton, C. W. (2009). Design of lipid-based formulations

for oral administration of poorly water-soluble drugs: precipitation of drug after

dispersion of formulations in aqueous solution. J Pharm Sci, 98(10), 3582-3595., ISSN:

0022-3549.

23. Pouton, C. W. (2006). Formulation of poorly water-soluble drugs for oral

administration: physicochemical and physiological issues and the lipid formulation

classification system. Eur J Pharm Sci, 29(3-4), 278-287., ISSN: 0928-0987.

24. Cuine, J. F., McEvoy, C. L., Charman, W. N., Pouton, C. W., Edwards, G. A.,

Benameur, H., & Porter, C. J. (2008).Evaluation of the impact of surfactant digestion on

the bioavailability of danazol after oral administration of lipidic self-emulsifying

formulations to dogs. J Pharm Sci, 97(2), 995-1012., ISSN: 0022-3549.

25. Gershanik, T., & Benita, S. (2000).Self-dispersing lipid formulations for improving oral

absorption of lipophilic drugs. European Journal of Pharmaceutics and

Biopharmaceutics, 50 (1), 179-188., ISSN: 0939-6411.

26. Strickley, R. G. (2004). Solubilizing excipients in oral and injectable formulations.

Pharm Res, 21 (2), 201-230. ISSN: 0724-8741.

27. Amidon, G. L., Lennernas, H., Shah, V. P., & Crison, J. R. (1995). A theoretical basis

for a biopharmaceutic drug classification: the correlation of in vitro drug product

dissolution and in vivo bioavailability. Pharm Res, 12 (3), 413-420., ISSN: 0724-8741.

28. Folkers G, van de Waterbeemd H, Lennernäs H, Artursson P, Mannhold R, Kubinyi H

(2003). Drug Bioavailability: Estimation of Solubility, Permeability, Absorption and

Bioavailability (Methods and Principles in Medicinal Chemistry). Weinheim: Wiley-

VCH., ISBN 3-527-30438-X.

29. Yu, L. X., Amidon, G. L., Polli, J. E., Zhao, H., Mehta, M. U., Conner, D. P., . . .

Hussain, A. S. (2002). Biopharmaceutics classification system: the scientific basis for

biowaiver extensions. Pharm Res, 19 (7), 921-925., ISSN: 0724-8741.


36

30. Girish C, Soni, Prajapati S, K, Nirvesh C. (2014) self nanoemulsion, advance form of

drug delivery system, World Journal of Pharmacy and Pharmaceutical Sciences, 3 (10),

410-436., ISSN 2278 – 4357.

31. Payal G., Pramod K., Sharma, N. K., Yogesh P., Jitendra G. (2014). Self Nano

Emulsifying Drug Delivery System: A Strategy To Improve Oral Bioavailability, World

Journal Of Pharmacy And Pharmaceutical Sciences, 3 (5), 506-512., ISSN 2278 –

4357.

32. Chandrasekhara Rao B, Vidyadhara S, Sasidhar R L C and Chowdary Y A.

(2014)design and evaluation of self-nanoemulsified drug delivery system (snedds) of

docetaxel by optimizing the particle size using response surface methodology, IAJPS, 1

(1), 35-45., ISSN:2349-7750.

33. Jeevana, J.B., & Sreelakshmi, K.(2011). Design and Evaluation of Self-

Nanoemulsifying Drug Delivery System of Flutamide. Journal of Young Pharmacists, 3

(1), 4–8., ISSN: 0975-1483.

34. Rajinikanth, P.S., Keat, N.W., Garg, S. (2012) Self-nanoemulsifying drug delivery

systems of valsartan: Preparation and in-vitro characterization. International Journal of

Drug Delivery, 4 (2), ISSN: 0975-0215.

35. Mangale M. R, Pathak S, Mene H. R, More B. (2015). A nanoemulsion, as

pharmaceutical overview. Int. J. Pharm. SCI. Rev. Res., 33 (1), 244-252., ISSN 0976 –

044X.

36. Ananya M, Murthy P N, Roja R., Sanjay D.(2013). Development of nanoemulsion as

carrier for transdermal delivery of valsartan. International Journal of Pharmaceutical

and Chemical Sciences, 2 (4), 1655-1665., ISSN: 2277-5005.

37. Sokolov Yu. V. (2014). Nanoemulsions as prospective drug delivery systems. News of

Pharmacy, 1 (77), 21-25., ISSN 1562-7241.

38. Jaiswal, M., Dudhe, R., & Sharma, P. K. (2015). Nanoemulsion: an advanced mode of

drug delivery system. 3 Biotech, 5(2), 123-127., ISSN : 2190-5738.


37

39. Chudasama A, Patel V, Nivsarkar M, Vasu K, Shishoo C.(2011). A novel lipid-based

oral drug delivery system of nevirapine. Int J Pharm Tech Res., 3(2):1159-1168., ISSN:

0974-4304.

40. Mahmoud, D. B., Shukr, M. H., & Bendas, E. R. (2014). In vitro and in vivo evaluation

of self-nanoemulsifying drug delivery systems of cilostazol for oral and parenteral

administration. Int J Pharm, 476(1-2), 60-69., ISSN 0378-5173.

41. Jiajia R., David J. M.(2012). Lemon oil solubilization in mixed surfactant solutions:

Rationalizing microemulsion and nanoemulsion formation. Food Hydrocolloids. 26(1),

268-276., ISSN:0268-005X.

42. Avachat, A. M., & Patel, V. G. (2015). Self nanoemulsifying drug delivery system of

stabilized ellagic acid-phospholipid complex with improved dissolution and

permeability. Saudi Pharm J, 23(3), 276-289., ISSN: 1319-0164.

43. Dunnhaupt, S., Kammona, O., Waldner, C., Kiparissides, C., & Bernkop-Schnurch, A.

(2015). Nano-carrier systems: Strategies to overcome the mucus gel barrier. Eur J

Pharm Biopharm, 96, 447-453., ISSN: 0939-6411.

44. Pouton, C. W. (1985). Self-emulsifying drug delivery systems: assessment of the

efficiency of emulsification. International Journal of Pharmaceutics, 27(2), 335-348.,

ISSN: 0378-5173.

45. Deckelbaum, R. J., Hamilton, J. A., Moser, A., Bengtsson-Olivecrona, G., Butbul, E.,

Carpentier, Y. A., . . . Olivecrona, T. (1990). Medium-chain versus long-chain

triacylglycerol emulsion hydrolysis by lipoprotein lipase and hepatic lipase:

implications for the mechanisms of lipase action. Biochemistry, 29(5), 1136-1142.,

ISSN: 0006-2960.

47. Hauss, D. J., Fogal, S. E., Ficorilli, J. V., Price, C. A., Roy, T., Jayaraj, A. A., & Keirns,

J. J. (1998). Lipid-based delivery systems for improving the bioavailability and

lymphatic transport of a poorly water-soluble LTB4 inhibitor. J Pharm Sci, 87(2), 164-

169., ISSN: 0022-3549.


38

48. Khoo, S.-M., Shackleford, D. M., Porter, C. J. H., Edwards, G. A., & Charman, W. N. J.

P. R. (2003). Intestinal Lymphatic Transport of Halofantrine Occurs After Oral

Administration of a Unit-Dose Lipid-Based Formulation to Fasted Dogs. 20(9), 1460-

1465., ISSN: 1573-904X.

49. Lawrence, M. J., & Rees, G. D. (2000). Microemulsion-based media as novel drug

delivery systems. Adv Drug Deliv Rev, 45(1), 89-121., ISSN: 0169-409X.

50. Kimura, M., Shizuki, M., Miyoshi, K., Sakai, T., Hidaka, H., Takamura, H., & Matoba,

T. (1994). Relationship between the Molecular Structures and Emulsification Properties

of Edible Oils. Bioscience, Biotechnology, and Biochemistry, 58(7), 1258-1261., ISSN:

0916-8451.

51. Holm, R., Porter, C.J.H., Müllertz, A. et al. (2002). Structured Triglyceride Vehicles

for Oral Delivery of Halofantrine: Examination of Intestinal Lymphatic Transport

and Bioavailability in Conscious Rats.Pharm Res., 19:1354–61. ISSN: 0724-8741.

52. Levy, M. Y., & Benita, S. (1990). Drug release from submicronized o/w emulsion: a

new in vitro kinetic evaluation model. International Journal of Pharmaceutics, 66(1),

29-37., ISSN: 0378-5173.

53. Reiss, H. (1975). Entropy-induced dispersion of bulk liquids. Journal of Colloid and

Interface Science, 53(1), 61-70., ISSN: 0021-9797.

54. Dabros, T., Yeung, A., Masliyah, J., & Czarnecki, J. (1999). Emulsification through

Area Contraction. Journal of Colloid and Interface Science, 210(1), 222-224.,

ISSN:0021-9797.

55. Wakerly, M. G., Pouton, C. W., Meakin, B. J., & Morton, F. S. (1986). Self-

Emulsification of Vegetable Oil-Nonionic Surfactant Mixtures. In Phenomena in Mixed

Surfactant Systems, American Chemical Society. (Vol. 311, pp. 242-255).,ISBN: 0-

8412-0975-8.

56. Rang, M. J., & Miller, C. A. (1999). Spontaneous Emulsification of Oils Containing

Hydrocarbon, Nonionic Surfactant, and Oleyl Alcohol. J Colloid Interface Sci, 209(1),

179-192., ISSN: 0021-9797.


39

57. Pouton, C. W. (1997). Formulation of self-emulsifying drug delivery systems. Adv Drug

Deliv Rev, 25(1), 47-58., ISSN: 0169-409X.

58. Craig, D. Q. M., Lievens, H. S. R., Pitt, K. G., & Storey, D. E. (1993). An investigation

into the physico-chemical properties of self-emulsifying systems using low frequency

dielectric spectroscopy, surface tension measurements and particle size analysis.

International Journal of Pharmaceutics, 96(1), 147-155.,ISSN: 0378-5173.

59. Pautot, S., Frisken, B. J., Cheng, J.-X., Xie, X. S., & Weitz, D. A. (2003). Spontaneous

Formation of Lipid Structures at Oil/Water/Lipid Interfaces. Langmuir, 19(24), 10281-

10287., ISSN: 0743-7463.

60. Singh, B., Bandopadhyay, S., Kapil, R., Singh, R., & Katare, O. (2009). Self-

emulsifying drug delivery systems (SEDDS): formulation development,

characterization, and applications. Crit Rev Ther Drug Carrier Syst, 26(5), 427-521.,

ISSN: 0743-4863.

61. Cherniakov, I., Domb, A. J., & Hoffman, A. (2015). Self-nano-emulsifying drug

delivery systems: an update of the biopharmaceutical aspects. Expert Opin Drug Deliv,

12(7), 1121-1133., ISSN: 1742-5247.

62. Pouton, C. W. (2000). Lipid formulations for oral administration of drugs: non-

emulsifying, self-emulsifying and 'self-microemulsifying' drug delivery systems. Eur J

Pharm Sci, 11 Suppl 2, S93-98., ISSN: 0928-0987.

63. Nazzal, S., & Khan, M. A. (2006). Controlled release of a self-emulsifying formulation

from a tablet dosage form: stability assessment and optimization of some processing

parameters. International Journal of Pharmaceutics, 315(1-2), 110-121., ISSN:0378-

5173.

64. Tang, B., Cheng, G., Gu, J. C., & Xu, C. H. (2008). Development of solid self-

emulsifying drug delivery systems: preparation techniques and dosage forms. Drug

Discov Today, 13(13-14), 606-612., ISSN: 1359-6446.

65. Ramasahayam, B., Eedara, B. B., Kandadi, P., Jukanti, R., & Bandari, S. (2015).

Development of isradipine loaded self-nano emulsifying powders for improved oral


40

delivery: in vitro and in vivo evaluation. Drug Dev Ind Pharm, 41(5), 753-763., ISSN:

0363-9045.

66. Dressman, J.B. and Klein, S., eds. (2005). Development of dissolution tests on the basis

of gastrointestinal physiology. Pharmaceutical Dissolution Testing, eds. Dressman, J.,

and Krämer, J.,Taylor and Francis: NY, USA. pp. 193–227.

67. Dressman, J.B., Alsenz, J., Schamp, K., and Beltz, K., eds.(2007) Characterizing release

from lipid based formulations. Oral Lipid based Formulations: Enhancing the

Bioavailability of Poorly Water‐ soluble Drugs, eds. Hauss, DJ., Informa Healthcare,

Inc.: NY,USA. pp. 242–245.

68. Thomas, N., Richter, K., Pedersen, T. B., Holm, R., Mullertz, A., & Rades, T. (2014).

In vitro lipolysis data does not adequately predict the in vivo performance of lipid-based

drug delivery systems containing fenofibrate. Aaps j, 16(3), 539-549., ISSN:1550-7416.

69. Porter, C. J., Trevaskis, N. L., & Charman, W. N. (2007). Lipids and lipid-based

formulations: optimizing the oral delivery of lipophilic drugs. Nat Rev Drug Discov,

6(3), 231-248.ISSN:1474-1776.

70. Kossena, G. A., Charman, W. N., Boyd, B. J. and Porter, C. J. (2005), Influence of the

intermediate digestion phases of common formulation lipids on the absorption of a

poorly water‐ soluble drug. J. Pharm. Sci., 94: 481- 492., ISSN: 0022-3549.

71. Humberstone, A. J., Porter, C. J. H., & Charman, W. N. (1996). A physicochemical

Basis for the Effect of Food on the Absolute Oral Bioavailability of Halofantrine. J

Pharm Sci, 85(5), 525-529., ISSN: 0022-3549.

72. Boyd, M., Risovic, V., Jull, P., Choo, E., & Wasan, K. M. (2004). A stepwise surgical

procedure to investigate the lymphatic transport of lipid-based oral drug formulations:

Cannulation of the mesenteric and thoracic lymph ducts within the rat. J Pharmacol

Toxicol Methods, 49(2), 115-120., ISSN: 1056-8719.

73. Guarneri, L., Angelico, P., Ibba, M., Poggesi, E., Taddei, C., Leonardi, A., & Testa, R.

(1996). Pharmacological in vitro studies of the new 1,4-dihydropyridine calcium

antagonist lercanidipine. Arzneimittelforschung, 46(1), 15-24., ISSN: 0004-4172


41

74. Bang, L. M., Chapman, T. M., & Goa, K. L. (2003). Lercanidipine : a review of its

efficacy in the management of hypertension. Drugs, 63(22), 2449-2472.,ISSN: 0012-

6667

75. Barchielli, M., Dolfini, E., Farina, P., Leoni, B., Targa, G., Vinaccia, V., & Tajana, A.

(1997). Clinical Pharmacokinetics of Lercanidipine. Journal of Cardiovascular

Pharmacology, 29, S1-S15., ISSN: 0160-2446

76. Francisco J. Alvarez, Glen Gary Lawrence, Hung-Ren H. Lin, Tzuchi R. Ju (2004)

Rapid dissolution formulation of cinacalcet HCL. European Patents EP1663182 B1

77. Deborah Neville, Scott Jenkins, David Manser (2011) WIPO patents, WO2011146583

A2.

78. Kostis, J. B. (2003).treatment of hypertension in older patients: an updated look at the

role of calcium antagonists. The American Journal of Geriatric Cardiology, 12: 319-

327. ISSN: 1076-7460.

79. Whitworth, J. A. (2003). World Health Organization (WHO)/International Society of

Hypertension (ISH) statement on management of hypertension. J Hypertens, 21(11),

1983-1992., ISSN: 0263-6352.

80. Cifkova, R., Erdine, S., Fagard, R., Farsang, C., Heagerty, A. M., Kiowski, W., . . .

Zanchetti, A. (2003). Practice guidelines for primary care physicians: 2003 ESH/ESC

hypertension guidelines. J Hypertens, 21(10), 1779-1786., ISSN: 0263-6352.

81. Guarneri, L., Angelico, P., Ibba, M., Poggesi, E., Taddei, C., Leonardi, A., & Testa, R.

(1996). Pharmacological in vitro studies of the new 1,4-dihydropyridine calcium

antagonist lercanidipine. Arzneimittelforschung, 46(1), 15-24., ISSN: 0004-4172.

82. Bang, L. M., Chapman, T. M., & Goa, K. L. (2003). Lercanidipine: a review of its

efficacy in the management of hypertension. Drugs, 63(22), 2449-2472., ISSN: 0012-

6667.

83. Barchielli, M., Dolfini, E., Farina, P., Leoni, B., Targa, G., Vinaccia, V., & Tajana, A.

(1997). Clinical Pharmacokinetics of Lercanidipine. Journal of Cardiovascular

Pharmacology, 29, S1-S15., ISSN: 0160-2446.


42

84. Omboni, S., Zanchetti, A., & Investigators, o. b. o. t. M. S. (1998). Antihypertensive

efficacy of lercanidipine at 2.5, 5 and 10 mg in mild to moderate essential hypertensives

assessed by clinic and ambulatory blood pressure measurements. 16(12), 1831-1838.,

ISSN: 0263-6352.

85. November 2013. Zanidip(R) package leaflet: information for the user[online], https://

www. medicines.org.uk/emc/files/pil.191.pdf. [Accessed 28August 2018].

86. May 2017. SENSIPAR® (cinacalcet) tablets, for oral use [online] https:// pi.amgen.com

/~/ media /amgen/repositorysites/pi-amgen-com/ sensipar/ sensipar_pi_hcp_

english.pdf. [Accessed 28August 2018].

87. Cinacalcet hydrochloride Product ingredient for Cinacalcet [online]

https://www.drugbank.ca/salts/DBSALT001463. [Accessed 28August 2018].

88. 20 may 2018.Showing metabocard for cinacalcet.(HMDB0015147). [ online ]. http://

www. hmdb.ca/metabolites/HMDB0015147. [Accessed 29 May, 2018].

89. Joy, M. S., Kshirsagar, A. V., & Franceschini, N. (2004). Calcimimetics and the

treatment of primary and secondary hyperparathyroidism. Ann Pharmacother, 38(11),

1871-1880., ISSN: 1060-0280.

90. Moe, S. M. (2008). Disorders involving calcium, phosphorus, and magnesium. Prim

Care, 35(2), 215-237, v-vi., ISSN: 0095-4543.

91. Raymond CR, Sheskey PJ, Quinn ME.(2009).Handbook of pharmaceutical excipients.

6th ed, Royal Pharmaceutical society of Great Britain publisher. London; Chicago:

Washington, DC.

92. [Online].www.gatteffosse.fr. [Accessed 28 August 2018].

93. [Online].www.abiteccorp.com. [Accessed 28 August 2018].

CHAPTER 2

Review of Literature

2.1 SNEDDS Preparations

Premjeet Singh Sandhu et al. [1] developed a nano-miceller drug delivery system of

tamoxifen narigenin having natural ingredients like polyunsaturated fatty acid (PUFA).

The optimized SNEDDS showed the complete drug release in 30 min and more than 80%

permeation in 45 transactions. It was also found that 4.5-6.5 fold uptake of SNEDDS using

Caco-2 cells. Cytotoxicity study on MCF-7 cells indicated significant results (P < 0.05).

The in vivo study in rate revealed 7.3 and 11.4-fold increase in Cmax and AUC of drug

absorption and 2-fold reduction in Tmax. In vivo study of the DMBA model showed a

reduced tumor size, and improved survival rate of the animals indicates its safety as well.

Jin Qian et al. [2] have formulated SNEDDS of myricetin in order to enhance poor

solubility and oral bioavailability. The bioavailability of myricetin is less than 10 %.

Various formulations produced in various excipients. The obtained SNEDDS with Capryol

90/ Cremophor RH 40/ PEG 400 4:3:3, Capryol 90/CremophorRH40/1, 2-propanediol

4:3:3, Capryol 90/Cremophor EL/Transcutol HP 4:3:3 and capryol 90/Cremephor RH

40/Transcutol HP 2:7:1, with droplet sizes less than 200 nm. SNEDDS had a fast release of

drug i.e. over 90% in 1 min, low cytotoxicity, and improved permeability and solubility.

Chapter 2 Review of Literature

44

Consequently, the oral bioavailabilities of SNEDDS of Myricetin were 5.13, 6.33, 4.69 and

2.53-fold for respective formulations.

Sarwar Beg et al. [3] invested Solid SNEDDS of olmesartan medoxomil by employing

porous carriers to enhance the oral bioavailability. Oleic acid, Tween 40 and Transcutol

HP as the lipid, surfactant and cosolvent used for formulation of L-SNEDDS). S-SNEDDS

formulations were prepared by adsorbing L-SNEDDS onto the porous carriers. Neusilin

US2 exhibited excellent flowability and compactibility. 2.6-fold drug release rate was

observed with optimized S-SNEDDS. In vivo studies in Wistar rats found 2.32 and 3.27-

fold enhancement in Cmax and AUC. In a nutshell, S-SNEDDS of olmesartan medoxomil

as one of the promising formulation strategies with distinctly improved biopharmaceutical

attributes.

Sabine et al [4] investigated SNEDDS for for oral gene delivery drug delivery. After

hydrophobic ion pairing a plasmid was incorporated into SNEDDS. The mean droplet size

was between 45.8 and 47.5 nm. Degradation studies via DNase I showed up to 8-fold

prolonged resistant time against enzymatic digestion compared to naked pDNA

and pDNA–lipid complexes. Transfection studies indicated a significantly improved

transfection compared to naked pDNA. Further, Transfection efficiency found at par with

transfection using Lipofectin® transfection reagent.

R. Nazari-Vanani et al [5] prepared SNEDDS Curcumin to enhance its bioavailability.

SNEDDS of curcumin developed by using ethyl oleate: tween 80: PEG 600, 50:40:10%

w/w respectively with 11.2-nm droplets. The results revealed a significant increment of

3.95 times in Cmax, and the curcumin bioavailability was increased by 194.2% in rats

compared to the pure curcumin. The development of the SNEDDS formulation had a better

potentiality as a possible alternative for curcumin administration.

Komal Parmar et al [6] developed S-SNEDDS for the delivery of Embelin, a poorly

water soluble herbal active ingredient. Box-Behnken experimental design was used to

optimize the formulation variable Capryol 90, Acrysol EL 135, PEG 400. Optimized L

SNEDDS were converted to S-SNEDDS by adsorption on the porous materials like Aerosil


45

200 and Neusilin and thereby compressed into tablets. Solid state characterization of S-

SNEDDS by DSC and Powder XRD. TEM analysis exhibited spherical globules. S-

SNEDDS of Embelin are found to be stable without any significant change in

physicochemical properties. Therefore, the present studies demonstrated dissolution

enhancement potential of porous carrier based S-SNEDDS for poorly water soluble herbal

active ingredient, Embelin.

Theodora Karamanidou et al [7] developed mucus permeating SNEDDS for oral insulin

delivery of hydrophobic ion pair of insulin/dimyristoyl phosphatidylglycerol. The

developed SNEDDS have droplet diameter in the range of 30–45 nm and loading of insulin

varied between 0.27 and 1.13 wt%. Significant part of the survey was that protein

protected from enzymatic degradation by intestinal enzymes, i.e. from trypsin and α-

chymotrypsin. The SNEDDS formulation exhibited increased mucus permeability and did

not affect by ionic strength. The formulation prevented an initial split open release of

insulin and was set up to be non-cytotoxic up to a 2 mg/milliliter. Insulin/dimyristoyl

phosphatidylglycerol SNEDDS could be seen as a promising scheme for the oral delivery

of insulin.

Rajendra Narayan Dash et al [8] developed a solid S-SNEDDS to improve the dissolution,

absorption and pharmacodynamic effects of glipizide. It was made by adding a polymeric

precipitation inhibitor i.e HPMC-E5 at 5% w/w to a liquid SNEDDS. Dilution of the liquid

S-SNEDDS generated a nanoemulsion with a mean droplet size of 28.0 nm. The liquid S-

SNEDDS was transformed into solid S-SNEDDS by calcium carbonate and talc. SEM

studies of solid S-SNEDDS proved the presence of molecularly dissolved glipizide. The

solid S-SNEDDS was found to be stable during accelerated stability studies. In-vivo

pharmacokinetic studies showed a significant (p < 0.001) increase in Cmax - 3.4-fold and

AUC0–12h - 2.7-fold of glipizide from solid S-SNEDDS as compared with the pure drug

Khaled Aboul Fotouh et al [9] invested SNEDDS of Candesartan Cilexetil is widely

practiced in the hypertension and heart failure. It helps to solve the problems of poor

aqueous solubility and enzymatic degradation in the small intestine. All screened

excipients were reported for their P-glycoprotein and CYP3A4 modulation activity.


46

Ternary and pseudo ternary diagrams were built to optimize the organization. Formulated

with Peppermint oil: Cremophor RH40 and Labrasol (55% w/w: 25% w/w: 20% w/w) was

chosen for optimized formulation. Its droplet size showed the robustness to different

dilution and its TEM photograph showed spherical particles without any apparent

aggregation even after 24 h. Optimized formulation of SNEDDS successfully controlled

the systolic blood pressure of hypertensive rats. These results indicate that, SNEDDS of

candesartan Cilexetil could be promising delivery systems with a rapid onset of action and

prolonged therapeutic effect.

Faiyaz Shakeel et al [10] prepared ultra fine, super SNEDDS of indomethacin to improve

its solubility and in vitro dissolution rate. Thermodynamically stable SNEDDS was

selected for self-nanoemulsification efficiency test. Selected formulations were

characterized in terms of the droplet size distribution, viscosity and refractive index and in

vitro dissolution/drug release studies. Optimized SNEDDS, in vitro drug release showed

98.4% release and much faster than marketed capsule. The results of solubility studies

showed around 4573 fold enhancement in solubility in SNEDDS formulation compared to

its aqueous solubility. These results revealed that SNEDDS of indomethacin could be

successfully applied in society to improve its solubility as well as in vitro dissolution rate.

Ana Maria Sierra Villar et al [11] formulated SNEDDS of gemfibrozil by QBD approach

for improvement of dissolution and oral absorption. Box–Behnken experimental design

was applied to optimize the formulation variables Cremophor® EL, Capmul® MCM-C8,

and lemon essential oil components were 32.43%, 29.73% and 21.62% respectively.

SNEDDS were assessed for turbidity, emulsification efficacy, globule size, PDI and drug

release. TEM demonstrated spherical droplet morphology. The SNEEDS release study was

compared to commercial tablets. Optimized SNEDDS formulation of gemfibrozil showed

a remarkable increase in dissolution rate compared to conventional tablets.

Youn Gee Seo et al [12] developed the potential SNEDDS to improve the bioavailability of

docetaxel and its chemotherapeutic effect. The SNEDDS was prepared by capryol 90,

labrasol, and transcutol HP using a ternary phase diagram. The liquid nano-emulsion was

spray-dried into solid SNEDDS using inert colloidal silica. Antitumor efficacy of


47

SNEDDS was compared with commercially available Taxotere®. The various

compositions of SNEDDS were screened and found optimal at a volume ratio of 10/75/15

for capryol 90, labrasol, and transcutol HP, respectively. High oral bioavailability of 17%

with SNEDDS compared to only 2.6% for pure docetaxel. Notably, SNEDDS also

exhibited an increased anti-tumor efficacy with a reduced toxicity when compared with

intravenous Taxotere®. SNEDDS could be a potent formulation for an oral dosage form of

docetaxel with better antitumor activity and reduced toxicity.

Spandana Inugala et al [13] prepared S-SNEDDS with Capmul MCM C8, Tween 80 and

Transcutol P to improve the dissolution and oral bioavailability of darunavir. L-SNEDDS

were developed by using rational blends of components with the good solubilizing ability

for darunavir which were selected based on solubility studies. The prepared L-SNEDDS

formulations were tested for rate of emulsification, clarity, phase separation,

thermodynamic stability, cloud point temperature, globule size and zeta potential. In

vitro drug release studies showed initial rapid release of about 13.3 ± 1.4% within 30 min

from L-SNEDDS followed by the slow, continuous release of entrapped drug and reached

a maximum of 62.6 ± 3.5% release at the end of 24 h. The globule size 144 ± 2.3 nm found

the formation of nanoemulsion from the optimized L-SNEDDS formulation and was

physically adsorbed onto neusilin US2. In vitro dissolution studies indicated faster

dissolution of darunavir from the developed S-SNEDDS with 3 times greater mean

dissolution rate compared to pure darunavir. Furthermore, in vivo pharmacokinetic studies

in Wistar rats resulted in enhanced values of peak drug concentration Cmax for L-SNEDDS

-2.98±0.19 μg/ml and S-SNEDDS -3.7 ± 0.28 μg/ml compared to pure darunavir -

1.57 ± 0.17 μg/ml.

2.2 Patent review of SNEDDS

Table 2.1: Patents of SNEDDS

01 Title Eutectic-Based Self-Nanoemulsified Drug Delivery System

Patent

No. US Patent Application No.: 20100166873A1

Approach It is a eutectic-based SNEDDS formulated from cremophor, medium

chain mono- and diglycerides, essential oils, and a poorly water soluble

https://www.sciencedirect.com/science/article/pii/S0928098715001402#!


48

drug, such as ubiquinone (CoQ10). The SNEDDS can be further brought

out in a solid dosage form by integrating into gun powder. The solid

SNEDDS contains a copolymer of vinylpyrrolidone and vinyl acetate -

Kollidon VA 64, maltodextrin, and microcrystalline cellulose -MCC.

02 Title Medicinal Composition for Enhanced Delivery of Triterpenes

Patent

No. US Patent Application No.: 20170281573

Approach

The patent is for self-emulsifying oral formulation for enhanced

absorption of poorly water soluble triterpenes, such as pentacyclic

triterpene acids, either in substantially pure form or as constituents of

herbal extracts.

03 Title Emulsion Formulations

Patent

No. US Patent Application No.: 20180021349A1

Approach

The present invention regarding SEDDS, SMEDDS and SNEDDS of

lipophilic drugs containing phytosterols and/or phytosterol fatty acid

esters. Farther, the present invention pertains to the testosterone

containing system for fast release, enhanced and extended absorption,

minimal food effect and unique pharmacokinetic profile.

04 Title Parenteral and Oral Formulations of Benzimidazoles

Patent


Approach

The patent related to systems comprising of a benzimidazole derivative,

e.g., mebendazole, an oil, a surfactant, a co surfactant and a dipolar

aprotic solvent in a microemulsion formulation in the lung via a

parenterally administerable microemulsion with droplet size of about 35

nm to less than 100 nm and for defining hemolytically safe

microemulsions of a benzimidazole derivative during a therapeutic

treatment via a parenterally administerable microemulsion with a

surfactant : co surfactant content by weight of about 6% to 48%.


49

05 Title Self-Micro/Nanoemulsifying Drug Carrying System for Oral Use of

Rosuvastatin

Patent

No. WIPO Patent Application No.: WO/2015/142307 A1

Approach

The subject of invention is about SMEDDS/SNEDDS as a pharmaceutical

carrier of rosuvastatin 20 mg for oral administration. This formulation can

be used in the pharmaceutical industry and used for the treatment of

dyslipidemia.

06 Title Lyophilized Nanoemulsion

Patent


Approach

This patent relates to a lyophilized nanoemulsion comprising at least one

lipid and at least one sucrose fatty acid ester, wherein said lipid and

sucrose fatty acid ester are present in a weight ratio of 1:1 to 5:1 to one

another to the nanoemulsion which can be prepared from the

lyophilized nanoemulsion by redispersion, and to a process for the

preparation of the lyophilized nanoemulsion.

07 Title Self-Emulsifying Drug Delivery System (SEDDS) for Ophthalmic Drug

Delivery

Patent

No. WIPO Patent Application No.: WO/2016/141098

Approach

This patent Provided herein are topical ophthalmic preparations which

comprise a non-aqueous, self-emulsifying system comprising of an oil, a

poorly water- soluble drug, and one or more surfactants which can

spontaneously give rise to either nanosized emulsions upon contact with

an aqueous phase and their use in formulating and delivering poorly water

soluble drugs.

08 Title Method for Producing Oil-in-Water Emulsions From Self- Emulsifying

Gel Concentrates

Patent

No. WIPO Patent Application WO / 2009/080005A1


50

Approach

This patent relates to the Preparation of Oil in Water Dispersions of self-

emulsifying gel concentrates without agitation, such as stirring, or in a

laminar flow field.

09 Title Self-Nanoemulsion of Poorly Soluble Drugs

Patent


Approach

The patents regarding the disclosure pertains to pharmaceutical

formulation comprising low aqueous solubility drug abiraterone, a

solubilizer propylene glycol monocaprylate, and optionally at least one

pharmaceutically acceptable excipient that form dispersions when

exposed to an aqueous environment.

10 Title Self-Emulsifying Compositions of Cb2 Receptor Modulators

Patent

No. WIPO US Patent Application No.: WO/2017/149392

Approach

Disclosed patents for stable self-emulsifying compositions comprising at

least one CB2 receptor modulator, a self-emulsifying vehicle and

optionally at least one antipsychotic agent for use in the treatment of

mental disorders, methods of preparing such compositions and methods of

treating mental disordersusing same. This is also stable self emulsifying

compositions comprising beta caryophyllene (BCP) or HO-308 as sole

active agent or in combination with humulene, an antipsychotic for use in

the treatment of schizophrenia, methods of making such compositions and

methods of treating schizophrenia rising BCP. The patent also relates to

stable self-emulsifying compositions comprising 4-0-methylhonokiol

(MH) as sole active agent or in combination with caryophyllene oxide,

and optionally at least one antipsychotic agent for use in the treatment of

tic disorders, methods of making such compositions and methods of

treating Tourette syndrome using MH.


51

2.3 References

1. Sandhu, P. S., Kumar, R., Beg, S., Jain, S., Kushwah, V., Katare, O. P., & Singh, B.

(2017). Natural lipids enriched self-nano-emulsifying systems for effective co-

delivery of tamoxifen and naringenin: Systematic approach for improved breast

cancer therapeutics. Nanomedicine : nanotechnology, biology, and medicine, 13(5),

1703-1713.,ISSN: 1549-9634.

2. Qian, J., Meng, H., Xin, L., Xia, M., Shen, H., Li, G., & Xie, Y. (2017). Self-

nanoemulsifying drug delivery systems of myricetin: Formulation development,

characterization, and in vitro and in vivo evaluation. Colloids Surf B Biointerfaces,

160, 101-109.ISSN:0927-7765.

3. Beg, S., Katare, O. P., Saini, S., Garg, B., Khurana, R. K., & Singh, B. (2016).

Solid self-nanoemulsifying systems of olmesartan medoxomil: Formulation

development, micromeritic characterization, in vitro and in vivo evaluation.

Powder Technology, 294, 93-104., ISSN: 0032-5910.

4. Hauptstein, S., Prüfert, F., & Bernkop-Schnürch, A. (2015). Self-nanoemulsifying

drug delivery systems as novel approach for pDNA drug delivery. International

Journal of Pharmaceutics, 487(1-2), 25-31., ISSN: 0378-5173.

5. Nazari-Vanani, R., Moezi, L., & Heli, H. (2017). In vivo evaluation of a self-

nanoemulsifying drug delivery system for curcumin. Biomed Pharmacother, 88,

715-720., ISSN: 0753-3322.

6. Parmar, K., Patel, J., & Sheth, N. (2015). Self nano-emulsifying drug delivery

system for Embelin: Design, characterization and in-vitro studies. Asian Journal of

Pharmaceutical Sciences, 10(5), 396-404., ISSN: 1818-0876.

7. Karamanidou, T., Karidi, K., Bourganis, V., Kontonikola, K., Kammona, O., &

Kiparissides, C. (2015). Effective incorporation of insulin in mucus permeating

self-nanoemulsifying drug delivery systems. Eur J Pharm Biopharm, 97(Pt A),

223-229., ISSN: 0939-6411.

8. Dash, R. N., Mohammed, H., Humaira, T., & Reddy, A. V. (2015). Solid

supersaturatable self-nanoemulsifying drug delivery systems for improved


52

dissolution, absorption and pharmacodynamic effects of glipizide. Journal of Drug

Delivery Science and Technology, 28, 28-36., ISSN: 1773-2247.

9. AboulFotouh, K., Allam, A. A., El-Badry, M., & El-Sayed, A. M. (2017).

Development and in vitro/in vivo performance of self-nanoemulsifying drug

delivery systems loaded with candesartan cilexetil. European Journal of

Pharmaceutical Sciences, 109, 503-513., ISSN: 0928-0987.

10. Shakeel, F., Haq, N., El-Badry, M., Alanazi, F. K., & Alsarra, I. A. (2013). Ultra

fine super self-nanoemulsifying drug delivery system (SNEDDS) enhanced

solubility and dissolution of indomethacin. Journal of Molecular Liquids, 180, 89-

94.ISSN: 0167-7322.

11. Villar, A. M., Naveros, B. C., Campmany, A. C., Trenchs, M. A., Rocabert, C. B.,

& Bellowa, L. H. (2012). Design and optimization of self-nanoemulsifying drug

delivery systems (SNEDDS) for enhanced dissolution of gemfibrozil. Int J Pharm,

431(1-2), 161-175., ISSN: 0378-5173.

12. Seo, Y. G., Kim, D. H., Ramasamy, T., Kim, J. H., Marasini, N., Oh, Y. K., . . .

Choi, H. G. (2013). Development of docetaxel-loaded solid self-nanoemulsifying

drug delivery system (SNEDDS) for enhanced chemotherapeutic effect. Int J

Pharm, 452(1-2), 412-420., ISSN: 0378-5173.

13. Inugala, S., Eedara, B. B., Sunkavalli, S., Dhurke, R., Kandadi, P., Jukanti, R., &

Bandari, S. (2015). Solid self-nanoemulsifying drug delivery system (S-SNEDDS)

of darunavir for improved dissolution and oral bioavailability: In vitro and in vivo

evaluation. Eur J Pharm Sci, 74, 1-10., ISSN: 0928-0987.

14. Mansoor A.K, Sami N (2010) Eutectic-Based Self-Nanoemulsified Drug Delivery

System, US Patent 0166873A1.

15. Joseph S. Michael W (2017) Medicinal Composition for Enhanced Delivery Of

Triterpenes, US Patent 0281573.

16. Om D, James S.B (2018) Emulsion Formulations, US Patent 0021349A1.


53

17. Diana S.C, Pranav G, Yulan Q, et al(2016) Parenteral and oral formulations of

benzimidazoles, US Patent 9259390.

18. Yesim H.K, Sebnem A(2015) Evren G, et al., Self-Micro/Nanoemulsifying Drug

Carrying System For Oral Use of Rosuvastatin, WO Patent 142307 A1.

19. Hanefeld, Andrea H, Martina S (2012) Simon G.,et al., Lyophilized nanoemulsion,

US Patent 8211948.

20. Yumna S, Chetan P.P (2016) Self-Emulsifying Drug Delivery System for

Ophthalmic Drug Delivery, WIPO WO Patent 141098.

21. Klaus K, Gerd W.D, Britta J (2009) Method For Producing Oil-In-Water

Emulsions From Self- Emulsifying Gel Concentrates. WIPO Patent 080005A1.

22. Dipen D, Siva R. K.V, Navnit H.S et al. (2016) Self-nanoemulsion of poorly

soluble drugs, U.S. Patent 9511078.

23. Sharon A (2017) Self-Emulsifying Compositions of Cb2 Receptor Modulators,

WIPO Patent 149392.

CHAPTER 3

Experimental

3.1 List of Equipments Used for Research Work

TABLE 3.1 : List of Equipments Used for Research Work

Sr. No. Equipments Model/ Make

1. Electronic Balance Mettler Toledo,India

2. Digital pH meter pH system 361 Systonics., India

3. Magnetic Stirrer Remi Equipments Pvt. Ltd., India

4. U.V Spectrophotometer Shimadzu UV 1800, Japan

5. HPLC Waters alliancese2695

6. Dissolution apparatus Elactrolab, India

7. Particle size analysier Nano particle Analyzer SZ-100, Horiba

8. FTIR spectrophotometer Perkin elmer, Spectrum GX, Germany

9. Centrifuge Remi lab instruments, India

Chapter 3 Experimental

55

3.2 List of Materials Used for the Research Work

TABLE 3.2 : List of Materials Used for Research Work

1 Lercanidipine HCL API Zydus Cadila, Ahmedabad, India

2 Cinacalcet HCL API Cipla Ltd., Mumbai, India

3 Capmul MCM - EP Oil Abitec Corp. Ltd., Mumbai, India

4 Capmul MCM Oil Abitec Corp. Ltd ., Mumbai, India

5 Capmul PG 12 EP/NF, Oil Abitec Corp. Ltd., Mumbai, India

6 Capmul GMO 50 EP/NF Oil Abitec Corp. Ltd., Mumbai, India

7 Capryol 90 Oil Gattefosse, France

8 Polyethylene Glycol 400 Co-surfactant S.D.Fine Chem Ltd., Mumbai, India

9 Labrasol Surfactant Gattefosse, France

10 Polysorbate-20 Co-surfactant Himedia Ltd., India

11 Polysorbate 80 Co-surfactant Himedia Ltd., India

12 Transcutol P Co-surfactant Gattefosse, France

13 Aconon MC8-2 Co-surfactant Abitec Corp. Ltd., Mumbai, India

14 Captex-355 EP/NF Co-surfactant Abitec Corp. Ltd .,Mumbai, India

15 Captex 200 P Co-surfactant Abitec Corp. Ltd., Mumbai, India

16 Aconon C 30 Co-surfactant Abitec Corp. Ltd., Mumbai, India

17 Aconon C 80 Co-surfactant Abitec Corp. Ltd., Mumbai, India

18 Pureco k 22 Oil Abitec Corp. Ltd., Mumbai, India

19 Captex 200 P Oil Abitec Corp. Ltd., Mumbai, India

20 Plurol oleique CC 497 Surfactant Gattefosse, France

21 Caproyl PG MC Surfactant Gattefosse, France

22 Lauroglycol Co-surfactant Gattefosse, France


56

23 Labrafil M2125 CS Surfactant Gattefosse, France

24 Acrysyol Co-surfactant Corel Pharma Chem., Ahmedabad

25 Q Pan 20 Surfactant Otto Chemie Pvt. Ltd., Mumbai

26 Safesol 218 Surfactant Nikko Chemicals Co. Ltd., Japan

3.3 Scanning and Calibration Curve Preparation of Selected Drugs

3.3.1 Preparation and calibration curve preparation of Lercanidipine HCL

Self nonoemulsifying drug delivery system for Lercanidipine HCL was prepared for oral

drug delivery. The analytical method used for the estimation of drug content from the

developed formulation based was on reported UV-spectrophotometric method. In the

present study the solvent used for estimation of drug content in the formulation was

methanol [1].

3.3.1.1 Scanning and calibration curve preparation of Lercanidipine HCL in

methanol

Preparation of Stock Solution:

Accurately weighed (10 mg) Lercanidipine HCL was transferred to 10 ml volumetric flask.

Little quantity of methanol was added to ensure complete dissolution of Lercanidipine

HCL and finally volume was made up to the mark with methanol (1 mg/ml).

Determination of Absorption maxima (λmax) of Lercanidipine HCL

0.1 ml of the stock solution was transferred to a 10 ml volumetric flask and diluted with

methanol to make up the volume. The solution thus prepared (10 µg/ml) of Lercanidipine

HCL was scanned in the range of 200 nm-400 nm using methanol as blank.

Construction of Calibration plot:

From the above stock solution, prepared the samples by dilution with methanol to give

final concentration of 2.5, 5.0, 7.5,10,15,20,25 µg/ml. The absorbance of all the prepared


57

solutions was then measured at the absorption maxima, using methanol as blank. The

readings were recorded in triplicate. A calibration curve was constructed by plotting

absorbance vs. concentration (μg/ml).

3.3.1.2 Scanning and calibration curve preparation of Lercanidipine HCL phosphate

buffer, pH 6.8.

Accurately weighed (10 mg) Lercanidipine HCL was transferred to 10 ml volumetric flask.

Little quantity of methanol was added to ensure complete dissolution of Lercanidipine

HCL and finally volume was made up to the mark with methanol (1 mg/ml).

Determination of Absorption maxima (λmax) of Lercanidipine HCL:

From the stock solution 10μg/ml was prepared in phosphate buffer and the solution was

scanned in the range of 200 to 400 nm to fix the maximum wave length and UV spectrum

was obtained. 0.1 ml of the stock solution was transferred to a 10 ml volumetric flask and

diluted with phosphate buffer to make up the volume. The solution thus prepared (10

µg/ml) of Lercanidipine HCL was scanned in the range of 200 nm-400 nm using phosphate

buffer.

Construction of Calibration Plot:

From the above stock solution, aliquots were accurately withdrawn with the help of pipette

and transferred to separate 10ml volumetric flasks and the volume was made up to the

mark with pH 6.8 Phosphate to give final concentration of 2,4,6,8,10µg/ml. The

absorbance of all the prepared solutions was then measured at the absorption maxima

(λ max of 236), using respective blank as blank. The readings were recorded in triplicate.

A calibration curve was constructed by plotting absorbance vs. concentration (μg/ml).

3.3.2 Preparation and Calibration Curve Preparation of Cinacalcet HCL

3.3.2.1 Scanning and calibration curve preparation of Cinacalcet HCL in methanol by

UV visible spectroscopy

Self nonoemulsifying drug delivery system for Cinacalcet HCL was prepared for oral drug

delivery. The analytical methods used for the estimation of drug content, the developed


58

formulation based on the reported UV-spectrophotometric method [2]. In the present study

the solvent used for estimation of drug content in the formulation was methanol.

Preparation of Stock Solution:

Accurately weighed (10 mg) Cinacalcet HCL was transferred to 10 ml volumetric flask.

Little quantity of methanol was added to ensure complete dissolution of Cinacalcet HCL

and finally volume was made up to the mark with methanol (1 mg/ml).

Determination of Absorption maxima (λmax) of Cinacalcet HCL:

0.1 ml of the stock solution was transferred to a 10 ml volumetric flask and diluted with

methanol to make up the volume. The solution thus prepared (10 µg/ml) of Cinacalcet

HCL was scanned in the range of 200 - 400 nm using methanol as blank.

Construction of Calibration plot :

From the above stock solution, aliquots were accurately withdrawn with the help of

pipette and transferred to separate 10ml volumetric flasks and the volume was made up to

the mark with methanol to give final concentration of 2.5 - 60 µg/ml. The absorbance of

all the prepared solutions was then measured at the absorption maxima (λ max of 281),

using methanol as blank. The readings were recorded in triplicate. A calibration curve was

constructed by plotting absorbance vs. concentration (μg/ml).

3.3.2.2 Scanning and calibration curve preparation of Cinacalcet HCL by HPLC

method

Stock Standard preparation for Linearity:

Weigh accurately about 36.7mg Cinacalcet Hydrochloride (equivalent to 33.3mg

Cinacalcet) standard and transfer in to 200mL volumetric flask. Add 5.0mL of

methanol sonicate to dissolve. Dilute to volume with dissolution medium 0.05N HCL

and mix well.

Linearity solution preparation: Transfer specified amount of standard stock solution to specified volumetric flasks and

make up to the mark with dissolution medium to get concentration from 6.66 to


59

40.Linearity was established across the range of the analytical procedure. A series of

standard preparations was prepared over a range of 20% of the lowest sample

concentration to 120% of the highest sample concentration.

3.4 Solubility Study Solubility studies performed in various oils, surfactants, and co-surfactants, by adding an

excess amount of drug into a micro tube containing 2 ml of each vehicle alone. The

mixtures were vortexed for 30 s to facilitate solubilisation and shaking (2000 rpm) in a

thermostatically controlled water bath at 37°C for 72 h. Then, the mixtures were

centrifuged at 10,000×g for 15 min (Eppendorf, NY, USA) and the supernatants were

filtered to remove undissolved drug. 100μL of supernatant was diluted with methanol and

Lercanidipine hydrochloride was quantified by using UV spectrophotometry.

3.5 Screening of Effective Oil, Surfactant and Co-Surfactant [3] Emulsification ability decide the selection of surfactant(s) and it is done by measuring and

comparing the percent transmittance of different mixtures of surfactant(s) and selected oils

with an objective to explain the basis for selection of components for nanoemulsion

formulations from the pseudo ternary phase diagrams. Solubilising capacity of drug

decide the selection of oil Lercanidipine HCL and Cinacalcet HCL. Briefly, equal quantity

of surfactant was added to the selected oil. The mixture was gently heated at 45-500C for

homogenizing the components. This isotropic mixture was diluted into 250 ml of distilled

water to yield a fine emulsion. The time taken for the formation of fine emulsion was also

noted. The resulting emulsions were observed visually for the relative turbidity. The

emulsions were allowed to stand for 2 hours and their % transmittance was assessed at

400-700 nm by UV-1700 UV-Visible double beam spectrophotometer (Shimadzu, Japan)

using distilled water as blank.

The turbidimetric method was used to assess relative efficacy of the co-surfactant to

improve the nanoemulsification ability of the surfactants and also to select best co-

surfactant from the large pool of co-surfactants available for peroral delivery. Selected

surfactant(s) was mixed with co-surfactant(s) i.e. 1:1 Smix mixture. Then, the equal

quantity of selected oil was added to this mixture (50:50) and the mixture was

homogenized with the aid of the gentle heat (45–500C). This isotropic mixture was diluted

into 250 ml of distilled water to yield fine emulsion. The time taken and ease of formation


60

of emulsions was noted by noting the number of flask inversions required to give uniform

emulsion. The resulting emulsions were observed visually for the relative turbidity.

The emulsions were allowed to stand for 2 hours and their transmittance was measured at

400-700 nm by UV-1700 UV-Visible double beam spectrophotometer (Shimadzu, Japan)

using distilled water as blank. As the ratio of cosurfactants to surfactant(s) is the same in

this case, the turbidity of resulting nanoemulsions will help in assessing the relative

efficacy of the co-surfactants to improve the nanoemulsification ability of the selected

surfactant(s) for the selected oil. Similarly, the nanoemulsification ability and the efficacy

of co-surfactant were also determined by varying the surfactant(s) to co-surfactant ratio i.e.

from 1:1 to 2:1 and 3:1.

3.6 Drug Excipients Compatibility of SNEDDS Formulations [4]

Compatibility of Lercanidipine HCL with Capmul MCM, Polysorbate 20 and Transcutol P

and of Cinacalcet HCL with Capmul MCM, Polysorbate 80 and PEG 400 were carried out

to check the physical and chemical compatibility, as they were selected for respective

formulation. Compatibility studies of excipients used in L-SNEDDS were performed using

Perkin-Elmer FTIR machine (Spectrum GX, Germany) by scanning from 4000 to 400 cm-

1 by Initial and 400C/75% RH for 1 month by IR Spectroscopy. The IR spectrum of the

formulation mixture was compared with those of relevant drug, oil and surfactants and

peak matching were done to detect any drug - excipients incompatibility peaks.

3.7 Evaluation Methods for SNEDDS Formulations

3.7.1 Refractive Index and %Transmittance [5]

The Self Nanoemulsifying system (SNEDDS) of Lercanidipine HCL and Cinacalcet HCL

was added to 250ml of purified water under continuous stirring (50 rpm) on a magnetic

stirrer at ambient temperature. Then Refractive index of system was measured by using an

Abbe’s Refractometer and turbidity was measured by measuring % transmittance by UV-

Visible spectrophotometer .

3.7.2 Measurement of Droplet Size, Polydispersity Index (PDI) and Zeta Potential

The mean size and size distribution of SNEDDS of Lercanidipine HCL and Cinacalcet

HCL were determined by photon correlation spectroscopy using zetasizer (Malvern


61

instruments, UK.) Each sample was diluted to a suitable concentration with filtered double

D.W. Size analysis was performed at 250C with light scattering at an angle of 900C.

Samples were diluted to 250 ml with purified water. Diluted samples were directly placed

into cuvette and Size, poly dispersity index and Zeta potential of L-SNEDDS was obtained

directly from the instrument [6].

3.7.3 Drug Content

Lercanidipine HCL and Cinacalcet HCL from pre-weighed SNEDDS were extracted by

dissolving in 25 ml methanol. Then methanolic extract was separated out and

Lercanidipine HCL and Cinacalcet HCL content were analysed by UV at 236 nm and at

281 nm, against standard methanolic solution of Lercanidipine HCL and Cinacalcet HCL

Respectively.

3.7.4 Effect of Dilution and Aqueous Phase Composition on Lercanidipine HCL and

Cinacalcet HCL SNEDDS [7]

Robustness of L- SNEDDS to the dilution and effect of aqueous phase composition were

studied using optimized Lercanidipine HCL and Cinacalcet HCL SNEDDS composition.

Lercanidipine HCL and Cinacalcet HCL SNEDDS were dispersed in 250 ml of aqueous

phases (Distilled water) with gentle stirring. Resulting nano emulsions were kept at 25 ±

2°C and evaluated for drug precipitation, phase separation, and changes in size over the

period of 24 hour.

3.7.5 Measurement of Viscosity of Lercanidipine HCL and Cinacalcet HCL

SNEDDS [8]

Viscosity of SNEDDS Lercanidipine HCL and Cinacalcet HCL SNEDDS were measured

at 30 rpm after dilution with aqueous phase (250 ml) with the help of Brookfield

viscometer at 250C by Spindle S-61.

3.7.6 Measurement of pH of Lercanidipine HCL and Cinacalcet HCL SNEDDS

pH of Lercanidipine HCL and Cinacalcet HCL SNEDDS were measured by using pH

meter at room temperature. pH of SNEDDS were measured after dilution with aqueous

phase (250 ml).


62

3.7.7 Self-Emulsification and Precipitation Assessment

Evaluation of the self-emulsifying property of SNEDDS formulation of Lercanidipine

HCL and Cinacalcet HCL was performed by visual assessment in glass beaker. The time

taken for the emulsion formulation (until a clear homogeneous system was obtained) was

noticed up on drop wise addition of the pre concentrate (100μL) in to 250 ml of distilled

water respectively in a glass beaker at 370C on a magnetic stirrer at 100rpm [9].

Precipitation was evaluated by visual inspection of resultant emulsion after 24 hours. The

formulations were categorized as clear (transparent or transparent with bluish tinge), non-

clear (turbid), stable (no precipitation at the end of 24 hours), or unstable (showing

precipitation within 24 hours).

3.7.8 Centrifugation and Freeze – Thaw Cycle [10]

Lercanidipine HCL and Cinacalcet HCL L-SNEDDS were diluted with 250 ml and 900 ml

aqueous phase (distilled water) and centrifuged at 5000 rpm for 30 min. In addition, they

were subjected to freeze–thaw cycle by storing it at -20°C for 24 hour and then for another

24 hour at 40°C. Nano emulsions were observed visually for phase separation and drug

precipitation, whereas their physical stability was assessed by measuring globule size

before and after centrifugation and freeze–thaw cycle.

3.7.9 In Vitro Diffusion Study [11]

In vitro diffusion studies were carried out for all formulations using dialysis technique.

Dialysis membrane pretreated to remove glycerol and sulphate salts present. Removal of

glycerol done by washing it in running water for 3–4 hours. Sulfate salts present in

membrane removed by treating with a 0.3% (w/v) solution of sodium sulfide at 80 °C for 1

minute and then washed it with hot water (60 °C) for 2 minutes, followed by acidification

with a 0.2% (v/v) solution of sulfuric acid, then rinse with hot water to remove the acid.

This membrane retains most of molecular weight 12,000 or greater. One end of pre-treated

dialysis membrane tubing was with thread and then diluted of self nanoemulsifying

formulation was placed in it. The other end of tubing was also secured with thread and was

allow rotating freely in dissolution vessel of USP 24 type II dissolution test apparatus

(Electrolab, India) that contained 900 ml dialyzing medium maintained at 37 ± 0.5°C and

stirred at 50 rpm. Drug suspension formulation (without SNEDDS) and marketed

formulation were also tested simultaneously under identical conditions for comparison.


63

Aliquots were collected periodically and replaced with fresh dissolution medium. Aliquots,

after filtration through 0.45μ PVDF filter paper, were analysed by UV spectrosocopy and

by HPLC for Lercanidipine HCL and Cinacalcet HCL content.

3.7.10 Stability Study of Lercanidipine HCL & Cinacalcet SNEDDS: [12]

Chemical and physical stability of Lercanidipine HCL and Cinacalcet HCL SNEDDS were

assessed at 40 ± 2°C/75 ± 5% RH and 25 ± 3°C/60 ± 5% (room temperature) as per ICH

guidelines. Lercanidipine HCL and Cinacalcet HCL SNEDDS were stored in glass vial for

6 months. Samples were be withdrawn at 0, 1, 3 and 6 months and assessed for physical

appearance, dispersion time, globule size and drug content.

3.8 Data Analysis

The data obtained were analysed statistically using ANOVA. The data obtained for the

optimization of process and formulation variables were statistically analysed by analysis of

variance (ANOVA) with in-built software design of Design Expert software (Stat-Ease,

Inc., USA). It was used to determine the significance and the magnitude of the effects of

different variables and their interactions. Probability values less than 0.0500 were

considered as statistically significant.

3.9 References

1. Acharjya SK, Sahoo S, Dash KK.,Annapurna M.M.(2010). Spectrophotometric

Determination of Lercanidipine Hydrochloride in Pharmaceutical Formulations.

International Journal of PharmTech Research.2 (2):1431-1436.ISSN: 0974-4304.

2. Loni, Amruta B., Ghante, Minal R., Sawant, S. D. (2012). Spectrophotometric

estimation of cinacalcet hydrochloride in bulk and tablet dosage form. Int J Pharm

Pharm Sci, 4(3), 513-515., ISSN- 0975-1491.

3. Borhade, V., Nair, H., & Hegde, D. (2008). Design and Evaluation of Self-

Microemulsifying Drug Delivery System (SMEDDS) of Tacrolimus. AAPS

PharmSciTech, 9(1), 13-21., ISSN: 1530-9932.


64

4. Jing-ling, T., Jin, S., & Zhong-Gui, H. (2007). Self-Emulsifying Drug Delivery

Systems: Strategy for Improving Oral Delivery of Poorly Soluble Drugs. Current

Drug Therapy, 2(1), 85-93.ISSN: 1574-8855.

5. Patel, J., Kevin, G., Patel, A., Raval, M., & Sheth, N. (2011). Design and

development of a self-nanoemulsifying drug delivery system for telmisartan for

oral drug delivery. Int J Pharm Investig, 1(2), 112-118., ISSN: 2230-9713.

6. Khoo, S.-M., Humberstone, A. J., Porter, C. J. H., Edwards, G. A., & Charman, W.

N. (1998). Formulation design and bioavailability assessment of lipidic self-

emulsifying formulations of halofantrine. International Journal of Pharmaceutics,

167(1), 155-164., ISSN: 0378-5173.

7. Gupta K, Mishra K, Mahajan C.,(2011). Preparation and in-vitro evaluation of self

emulsifying drug delivery system of antihypertensive drug valsartan, Int. J. Of

Pharm. & Life Sci., 2(3), 633-639., ISSN: 0976-7126.

8. Singh, B., Singh, R., Bandyopadhyay, S., Kapil, R., & Garg, B. (2013). Optimized

nanoemulsifying systems with enhanced bioavailability of carvedilol. Colloids Surf

B Biointerfaces, 101, 465-474., ISSN: 0927-7765.

9. Balakrishnan, P., Lee, B. J., Oh, D. H., Kim, J. O., Lee, Y. I., Kim, D. D., . . . Choi,

H. G. (2009). Enhanced oral bioavailability of Coenzyme Q10 by self-emulsifying

drug delivery systems. Int J Pharm, 374(1-2), 66-72., ISSN: 0378-5173.

10. Chaurasiya, A., Singh, A. K., Jain, G. K., Warsi, M. H., Sublet, E., Ahmad, F. J., . .

Khar, R. K. (2012). Dual approach utilizing self microemulsifying technique and

novel P-gp inhibitor for effective delivery of taxanes. J Microencapsul, 29(6), 583-

595., ISSN: 0265-2048.

11. Liu, L., Pang, X., Zhang, W., & Wang, S. (2006). Formulation design and in vitro

evaluation of silymarin-loaded self-microemulsifying drug delivery systems, Asian

journal of pharmaceutical sciences, 2(4),150-160., ISSN: 1818-0876.

12. Mahesh, R. D., Milan, D. L., & Navin, R. S. (2011). Preparation and In Vivo

Evaluation of Self-Nanoemulsifying Drug Delivery System (SNEDDS) Containing

Ezetimibe. Current Nanoscience, 7(4), 616-627., ISSN: 1573-4137.

Chapter 4

Result and Discussion

4.1. Result for Liquid SNEDDS of Lercanidipine HCL

4.1.1 Identification of Drug

Recognizable proof of the obtained antihypertensive drug Lercanidipine HCL and

guaranteeing its virtue is an essential before continuing with the experiment. The

Identification tests and the deductions for the drug sample based on its appearance,

solubility and melting point determination are summarized in Table 4.1.

TABLE 4.1: Identification of Lercanidpine Hydrochloride

Parameters Observations Reported [1] Inferences

Appearance Yellowish Yellowish Complies

Solubility

Soluble in methanol

and practically

insoluble in water.

Soluble in methanol

and practically

insoluble in water.

Complies

Melting point 175-177°C 175-177°C Complies

Consistence of the perceptions as for the revealed determinations confirms the obtained

sample to be of the drug Lercanidpine Hydrochloride. Different functional groups present

Chapter 4 Result and Discussion

66

in the API sample were determined by Fourier-change infrared (FT-IR) spectroscopic and

compared with the standard spectra of Lercanidpine Hydrochloride for affirmation. The

observed IR spectra of Lercanidpine Hydrochloride are appeared in Fig. 4.6. it was

checked and reasoned that the obtained sample was of Lercanidipine HCL and the drug

was utilized for every single further examination.

4.1.2 Scanning and Calibration Curve Preparation

4.1.2.1 Scanning and Calibration Curve Preparation of Lercanidipine HCL in

Methanol

The standard stock solution of Lercanidipine HCL was prepared in methanol as per the

method described in experimental section and scanned by UV Visible spectrophotometer

between 200 to 400 nm. The UV absorption spectrum of Lercanidipine HCL showed λmax

at 236 nm as shown in Fig. 4.1.

FIGURE 4.1: Scanning of Lercanidipine HCL in Methanol


67

TABLE 4.2: Calibration Curve Data of Lercanidipine HCL in Methanol

Conc

(µg/mL)

Absorbance at 236nm SD

I II III Mean

0 0.00 0.00 0.00 0.00 0.00

2.5 0.068 0.072 0.071 0.070 0.002

5 0.186 0.189 0.186 0.187 0.002

7.5 0.296 0.296 0.293 0.295 0.002

10 0.394 0.396 0.392 0.394 0.002

15 0.609 0.605 0.607 0.607 0.002

20 0.822 0.829 0.827 0.826 0.004

25 1.001 1.002 1.002 1.002 0.001

FIGURE 4.2: Calibration Plot of Lercanidipine HCL in Methanol

y = 0.041x - 0.022R² = 0.999

0

0.2

0.4

0.6

0.8

1

1.2

0 5 10 15 20 25 30

Abs

rban

ce

Concentraion(μg/ml)


68

A calibration curve was prepared in methanol in the range of 2.5-25 μg/ml by UV-Visible

spectrophotometer. The absorbance of these solutions was measured at 236 nm. This

procedure was performed in triplicate to validate the calibration curve. The data is given in

Table 4.2.

As shown in Fig. 4.2, Lercanidipine HCL follows Beer - Lambert’s law and a regression

equation was found to be y = 0.041x -0.022 with the regression coefficient (0.999) in

methanol indicates that the absorbance and concentration of drug are linearly related.

4.1.2.1 Scanning and Calibration Curve Preparation of Lercanidipine HCL in

Phosphate Buffer

The standard stock solution of Lercanidipine HCL was prepared as per the method

described in experimental section and scanned by UV Visible spectrophotometer between

200 to 400 nm. The UV absorption spectrum of Lercanidipine HCL showed λmax at 236

nm as shown in Fig. 4.3.

A calibration curve was prepared in methanol in the range of 2-10 μg/ml by UV-Visible

spectrophotometer. The absorbance of these solutions was measured at 236 nm. This

procedure was performed in triplicate to validate the calibration curve. The data is given in

Table 4.3.

As shown in Fig. 4.4, Lercanidipine HCL follows Beer- Lambert’s law and a regression

equation was found to be y = 0.025-0.0302 with the regression coefficient (0.9923)

indicates that the absorbance and concentration of drug are linearly related.

TABLE 4.3: Calibration Curve Data Of Lercanidipine HCL in Phosphate Buffer Conc

(µg/mL) Absorbance

I II III Mean STD DEV 2.0 0.011 0.011 0.012 0.011 0.000577 4.0 0.079 0.078 0.078 0.078 0.000577 6.0 0.127 0.124 0.125 0.125 0.001528 8.0 0.169 0.17 0.17 0.170 0.000577 10.0 0.214 0.215 0.215 0.215 0.000577


69

FIGURE 4.3: Scanning of Lercanidipine HCL in Phosphate Buffer

FIGURE 4.4: Calibration Plot of Lercanidipine HCL Phosphate Buffer

4.1.3 Screening of Oil and Surfactant/Co-Surfactant for Lercanidpine HCL

Lipid excipients are comprised of a large group of physically and chemically diverse

glycerides, which may be used in simple (single oil solutions of the drug substance) or in

y = 0.041x - 0.022R² = 0.999

0

0.2

0.4

0.6

0.8

1

1.2

0 5 10 15 20 25 30

Abs

rban

ce

Concentraion(μg/ml)


70

more complex nanocarriers (SMEDDS/SNEDDS, drug dissolved in the mixture of

glycerin, surfactant and or cosolvent), with considerable flexibility in formulation design

[2].

Nonionic surfactants were utilized in most of the research about SNEDDS because they

are less toxic and provide better stability over the extensive variety of pH and ionic

strength.

Nazzal et al suggested that appropriate vehicles should have a good solubilizing capacity

for the drug substance, which is essential for composing a SNEDDS[3]. The consequences

of the solubility of Lercanidipine HCL in some vehicles were shown in Table 4.4. along

with branded and generic names. The addition of co-solvent with surfactant was reported

to improve dispersibility. In this investigation co-solvents used were namely Sefsol

218,Captex 200 and Captex 355 EP/NF Span80 and Span 20 were not easily dispersed in

the aqueous system because they are lipophilic in nature. Captex -100 and Captex-200

provide lesser solubility, which was not sufficient for formulation. From the solubility

data, it was found that Plurol Oleique CC 497 and Polysorbate 20 was having the high

solubility of the drug, but Plurol oleique CC 497 showed viscous emulsion may be

because of high viscosity i.e 3000 mPa.s (20°C) with HLB 3 and Mol. Wt. 1023.258 g/mol

while Polysorbate 20 showed the good solubilization of Lercanidipine. Among the

screened surfactants Polysorbate 20 a nonionic surfactant was selected as a surfactant for

the further study. Transcutol P as co-surfactant was used on the basis of their high drug

solubilizing capacity. Capmul MCM provided good emulsification, as oil and is used in

Various Food, Cosmetic, and Industrial Uses.

The Capmul MCM having HLB value 5.5- 6.0 selected as oil on the basis of solubility

and partitioning of Lercanidpine Hydrochloride in the oil. Polysorbate 20 having HLB

value 16.7 as lipid phase surfactant and aqueous phase co surfactant Transcutol P having

HLB value 4 were selected on the soundness of the stability of dispersion prepared by

using distinctive surfactants.


71

TABLE 4.4: Solubility Study of Lercanidpine Hydrochloride in Various Vehicles

(Oils, Surfactants, Co Surfactants and Distil Water)

Solvent Solvent(mg/ml)

Pureco k 22(Corn oil, hydrogenated) 1.07±0.3

Capmul MCM(Mono-diglyceride of medium chain fatty acids (mainly

caprylic and capric) 26.39 ± 1.32

Labrafil M 2125 CS(Linoleoyl Polyoxyl-6 glycerides) 16.25 ± 1.1

Lauroglycol 90(Propylene glycol monolaurate ) 7.44 ±0.6

Transcutol P(Highly purified diethylene glycol monoethyl ether ) 30.29 ±0.24

Caproyl PG MC( Propylene glycol monocaprylate (type I) NF) 10.44 ± 0.5

Capmul MCM- EP(Mono- and Di-Glycerides) 18.33± 0.9

Plurol oleique CC 497 (Polyglyceryl-3 dioleate NF) 24.34 ±1.8

Acrysol 3.17± 0.2

Captex 200 P(Propylene Glycol Dicaprylate/Dicaprate) 2.53 ±0.2

Q-pan 20( Sorbitan monolaurate) 10.71± 0.8

Capmul PG 12 EP/NF( Type II Propylene Glycol Monolaurate) 24.14 ± 2.1

Polysorbate 80(Polyoxyethylene (80) sorbitan monolaurate) 4.94 ± 0.36

Capmul GMO 50 EP/NF(Glycerol Monooleate EP) 24.14 ± 2.1

Polysorbate 20(Polyoxyethylene (20) sorbitan monolaurate) 24.49 ±1.68

Aconon MC8(Caprylocaproyl Macrogolglycerides) 23.50 ± 1.1

Sefsol 218(Propylene Glycol Caprylate) 14.04 ±0.9

Captex-355 EP/NF(Medium-Chain Triglycerides) 2.84± 0.3

Labrafac PG(Propylene glycol dicaprylate) 1.17±0.4

Distil Water 0.016±0.01

*Mean ± SD, n=3


72

FIGURE 4.5 Solubility Chart of Lercanidpine Hydrochloride in Various Solvents

4.1.4 Drug and Surfactant Compatibility Study

4.1.4.1 Incompatibility Study of Lercanidpine Hydrochloride By Infrared

Spectroscopy

The drug Lercanidipine Hydrochloride was taken in pure form and FTIR spectra were

recorded between 4000-400 cm-1

The excipients taken for formulation are Capmul MCM (Glyceryl monocaprylate as

oil), Transcutol P (Diethyl glycol monoethyl ether as surfactant) and Polysorbate 20

(sorbitan monolaurate- Polysorbate as co-surfactant)

0 5 10 15 20 25 30 35

Pureco k 22

Capmul MCM

Labrafil M 2125 CS

Lauroglycol 90

Transcutol P

Caproyl PG MC

Capmul MCM- EP

Plurol oleique CC

Acrysol

Captex 200 P

Span 20

Capmul PG 12 EP/NF

Polysorbate 80

Capmul GMO 50 EP/NF

Polysorbate 20

Aconon MC8-2

Sefsol 218

Captex-355 EP/NF

Labrafac PG

(mg/ml)

Oil

/ Su

rfac

tan

t/C

o-s

urf

acta

nt


73

FIGURE 4.6A : FTIR of Lercanidpine HCL

FIGURE 4.6B : FTIR of Lercanidpine HCL With Excipients

FIGURE 4.7 : Overlay FTIR of Lercanidpine HCL and Lercanidpine HCL with

Excipients


74

The characteristic peak for Lercanidipine Hydrochloride observed were for pyridine

ring, benzene ring, ester and secondary amine groups. The commercial sample of

Lercanidipine Hydrochloride and mixture with excipients shown strong peak at 3300-

3500 cm-1 for O-H stretching, 3420-3440 cm-1 for pyridine ring system, 3040-3070 cm-

1 for stretching of C-H near to C=C, 1620-1650 cm-1 for C=C stretching, 1100-1300

cm-1 for C-O stretching and 1730-1750 cm-1 for C=O stretching of ester

FTIR spectra showed that the characteristic bands of Lercanidipine Hydrochloride or

each excipients alone were not altered in mixtures indicating no interactions between

Lercanidipine Hydrochloride and the selected excipients as shown in Fig. 4.7.

4.1.5 Pseudoternary Phase Diagram

SNEDDS form fine O/W emulsions with only by gentle agitation, upon their incorporation

into the aqueous phase. The determination of oil and surfactant and the blending proportion

of oil to S/CoS assume the prime job in the arrangement of the nanoemulsion. This can be

ascertained by the pseudo-ternary phase diagram as it differentiates the nanoemulsion

region from that of nanoemulsion region.

Ternary phase diagram was constructed in the absence of Lercanidipine HCL in order to

find the self-emulsifying regions and the suitable concentration of oil, surfactant, and co-

surfactant. In view of solvency Capmul MCM was utilized as the oil stage, Polysorbate 20

was utilized as the surfactant and Transcutol P was utilized as a co-surfactant for building

diverse ternary stage charts. The spontaneous emulsifying properties were observed

visually as well as by particle size analysis.

In the present examination, Capmul MCM was tried, in phase behavior studies with

Polysorbate 20 and Transcutol P as the S/ CoS mixture. Every one of the emulsions were

steady at zero time and this might be expected to the higher HLB estimation of Polysorbate

20 (HLB-16.7) and higher solubilising limit of Transcutol P. After observing clarity,

stability after 48 h, it was noted that formulations with an S / CoS ratio of 1:1 created

stable emulsions and was with the largest zone discovered appeared in Fig. 4.8.Thus,

fixing the surfactant/Co surfactant ratio of 1:1 is a superior choice from a stability

perspective.


75

Ratio of Surfactants: Co surfactants

Polysorbate 20: Transcutol P 1 : 1


Polysorbate 20: Transcutol P 2: 1





FIGURE 4.8:Pseudoternary Phase Diagrams of Capmul MCM (Oil), Polysorbate

20/ Transcutol P (S/Cos)


76

The hydrocarbon chains provide the hydrophobic nature of the polysorbates while the

hydrophilic nature is provided by the ethylene oxide subunits Because of dual

hydrophobic/hydrophilic nature,polysorbate 20 in solution tend to orient themselves so that

the exposure of the hydrophobic portion of the surfactant to the aqueous solution is

minimized.In systems containing air/water interfaces, surfactants will tend to accumulate

atthese interfaces, forming a surface layer of surfactant oriented in such a fashion that only

their hydrophilic ends are exposed to water. The ethylene oxide chains hydrogen bond with

water maintaining the solubility of the surfactant molecules may produce negative

zetapotential.Lauric acid containing component of polysorbate 20 is 40–60% of the total

number offatty acid species.The remaining fatty acids are a mixture of both saturated and

unsaturated fatty acids with caproic, caprylic, capric, and lauric acids and all other fatty

acid esters also present in polysorbate 20.

TABLE 4.5: Calculation of HLB of Capmul MCM (Oil), Polysorbate 20/ Transcutol P (S/Cos)(1:1)

Oil S/CO S HLB of oil ratio wise

HLB of surfactant ratio wise

Final Mixed HLB

HLB 6 16.7 1:1

Ratio

100 0 6 0 6

90 10 5.4 1.67 7.07

80 20 4.8 3.34 8.14

70 30 4.2 5.01 9.21

60 40 3.6 6.68 10.28

50 50 3 8.35 11.35

40 60 2.4 10.02 12.42

30 70 1.8 11.69 13.49

20 80 1.2 13.36 14.56

10 90 0.6 15.03 15.63

0 100 0 16.7 16.7


77

4.1.6 Factorial Design for Optimization of Lercanidipine HCL SNEDDS

4.1.6.1 Selection of Concentration of Oil, Surfactant and Cosurfactant

The selections of variables were based on the results of solubility data for Lercanidipine

HCL in oils and surfactants/co-surfactants, emulsifying ability of surfactant/co-

surfactant, solubilization capacity and Pseudo ternary phase diagram.

TABLE 4.6: Preliminary Trials for Development of Lercanidipine HCL SNEDDS

Preliminary Batches

Oil (% )

S:Co-S (1:1 ) (%)

Dispersion Dispersion

time (Seconds)

P1 28.57 71.43 Turbid 85

P2 21.05 78.95 Clear & Transparent 80









P11 33.33 66.67 Turbid 90

P12 25.00 75.00 Turbid 85





78

Capmul MCM was found satisfactory as oil, Polysorbate 20 and Transcutol P were

found best as surfactant and Co surfactant on the basis of solubility data. The proportion

of Polysorbate 20 and Transcutol P was chosen as 1:1.

Capmul MCM oil and Polysorbate 20: Transcutol-P mixture (1:1) was utilized to find their

suitable concentration in formulation development of SNEDDS of Lercanidipine HCL.

Preliminary batches were formulated and their results of dispersion status and dispersion

time were introduced in Table 4.6.

On the basis of the results of preliminary trials concentration of Capmul MCM oil (0.3ml)

and Concentration of Polysorbate 20: Transcutol-P mixture (1:1) (2.7ml) was fixed as

preliminary parameters for formulation development of Lercanidipine HCL SNEDDS.

Concentration of Capmul MCM oil and Concentration of surfactant/Cosurfactant plays

important role in a stable formulation of Self Nanoemulsifying drug delivery system

(SNEDDS); thus both were chosen as independent factors in a factorial design.

4.1.6.2 32 Full Factorial Designs for Optimization of Oil And Surfactant:

Cosurfactant in Formulation Development of Lercanidipine HCL SNEDDS

The preliminary trials were carried out using different concentration of Capmul MCM oil

(0.3ml – 0.5ml), Polysorbate 20 and Transcutol-P (1:1) (1.0 ml – 2.7ml).

The result of preliminary trials conducted with 0.3ml of Capmul MCM oil was found

satisfactory compared to other concentration. Aside from Capmul MCM oil concentration,

Concentration of Polysorbate20:Transcutol P mixture (1:1) was also critical in formulation

development of SNEDDS. 90 % of Polysorbate 20: Transcutol-P mixture (1:1) was found

appropriate in fundamental study.

Hence 32 factorial design was employed using concentration of Capmul MCM oil and

concentration of surfactant/Co surfactant as independent variable X1 and X2 respectively.

Coded and actual values of the independent variable were shown in Table 4.7. The runs for

factorial batches were presented in Table 4.8.


79

TABLE 4.7: Factors and Levels of Independent Variables in 32 Full Factorial Design

For Formulation of Lercanidipine HCL SNEDDS

Independent variables Level

Low (-1) Medium (0) High (+1)

Capmul MCM oil concentration (X1) (ml) 0.2 0.3 0.4

Polysorbate 20 : Transcutol-P (1:1 ) concentration (X2) (ml)

2.4 2.7 3.0

TABLE 4.8: 32 Full Factorial Design for Formulation of Lercanidipine HCL

SNEDDS

Batches X1 X2 Capmul

MCM oil (ml)

Polysorbate 20 :

Transcutol-P (1:1 ) (ml)

Dispersion Time

LS-1 -1 -1 0.2 2.4 65

LS-2 -1 0 0.2 3.7 46

LS-3 -1 1 0.2 3.0 42

LS-4 0 -1 0.3 2.4 58

LS-5 0 0 0.3 2.7 36

LS-6 0 1 0.3 3.0 40

LS-7 1 -1 0.4 2.4 73

LS-8 1 0 0.4 2.7 52

LS-9 1 1 0.4 3.0 58


80

4.1.7 Effect of Dilution on Snedds of Lercanidpine Hydrochloride by Distilled

Water

From the results of the Pseudoternary phase diagram was prepared for the Lercanidipine

HCL system by using Capmul MCM, Polysorbate 20 and Transcutol P. Formulations LS-1

to LS-9 were selected from the diagram and further characterized

Physical and chemical compatibility of the water-insoluble drugs Lercanidipine HCL with

different surfactants and co-surfactants were carried out to check the physical as well as

chemical compatibility. As appeared in Fig. 4.6 and 4.7 and Table 4.9 all the formulations

passed the physical as well as chemical compatibility tests. The formulations did not show

any changes during the compatibility studies and were found to be stable. Further studies

were carried out using this formulation.

TABLE 4.9: Effect of Dilution on SNEDDS of Lercanidpine Hydrochloride by

Distilled Water

Formulation Precipitation Crystallization Phase separation Colour change

LS-1 + + + +

LS-2 + + + +

LS-3 + + + +

LS-4 + + + +

LS-5 + + + +

LS-6 + + + +

LS-7 + + + +

LS-8 + + + +

LS-9 + + + +

Where, +Passed and - Failed


81

All Lercanidipine HCL formulations were categorized by visual inspection after dropwise

dilution of preconcentrate SNEDDS on the basis of clarity and apparent stability of the

resultant emulsion.

Visual assessment was done in the glass beaker at room temperature. The contents were

gently agitated by the magnetic stirrer. They were observed immediately, after dilution

with 250ml water for precipitation of drug, crystallization phase separation, and color

change. The dispersion was noted for each formulation after dilution with distilled water.

4.1.8 Viscosity, Refractive Index, % Transmittance and pH

Rheological techniques are used to check viscosity of SNEDDS systems. It is abundantly

established that formulation has the viscosity similar to that of water i.e.1.0. SNEDDS

having O/W nanoemulsion with water as external phase.

TABLE 4.10: Viscosity, Refractive Index and % Transmittance of Various

Lercanidpine Hydrochloride SNEDDS Formulations

Formulation

code

X1 Capmul

MCM

X2

S:Cos

Viscosity

(mPa.s)

Refractive

Index

%

Transmittance

LS-1 -1 -1 0.8865 1.368 91.34

LS-2 -1 0 0.8853 1.349 97.35

LS-3 -1 +1 0.8892 1.355 97.89

LS-4 0 -1 0.8864 1.334 100.0

LS-5 0 0 0.8824 1.369 92.57

LS-6 0 +1 0.8872 1.337 98.31

LS-7 +1 -1 0.8813 1.346 97.65

LS-8 +1 0 0.8839 1.356 97.25

LS-9 +1 +1 0.8832 1.362 98.89


82

The results of the viscosity, Refractive Index % Transmittance are as appeared in Table

4.10.

The pH of the SNEDDS depends on excipients used in the formulation. It is observed that

zeta potential may vary with the change in the pH, which in turn also affects the stability of

the formulation. All the SNEDDS of Lercanidipine HCL formulations showed pH values

in the range of 5.1 to 6.0. Thus pH is not affecting stability. Therefore, it can be predicted

that the drug is not entering into the external phase and remains in the internal phase. Since

SNEDDS with O/W water is the external phase. We found that the entire system showed

pH of water.

Viscosity of Cinacalcet HCL SNEDDS was measured by using Brookfield Viscometer at

250C temperature by using Spindle S-61 at 30 RPM after dilution with water.The refractіve

іndex and percent transmіttance data proved the transparency of system.

.

4.1.9 Thermodynamic Stability

SNEDDS formed at a particular concentration of oil, surfactant and water. A

thermodynamically stable system shows no phase separation, creaming or cracking. The

selected formulations were tested for thermodynamic stability by using the centrifugation

and freeze-thaw cycle. It was observed that the formulation LS-1 to LS-9 passed the

thermodynamic stress tests. The effect of centrifugation and freeze-thaw cycling on phase

separation of nanoemulsion and precipitation of drug is shown in Table 4.11. Both

accelerated tests are carried out to ascertain the stability of nanoemulsion under stress

conditions.

Formulations of nanoemulsion (LS-1 to LS-8) did not exhibit any drug precipitation, phase

separation after centrifugation confirming its stable nature. Similarly, optimized

formulation of nanoemulsion (LS-5) survived freeze-thaw cycles as it was found to be

reconstituted without any phase separation, drug precipitation after exposure to freeze-

thaw cycling. The cloud point should be above 37ºC. In this study, the cloud point of the

optimized formulation was found 80 ºC


83

TABLE 4.11: Centrifugation and Freeze –Thaw cycle parameter of

Lercanidipine SNEDDS

Formulation

Code OIL S/COS

Centrifugation Freeze thaw cycle

Phase

separation

Drug

precipitation

Phase

separation

Drug

precipitation

LS-1 -1 -1 No No No No

LS-2 -1 0 No No No No

LS-3 -1 1 No No No No

LS-4 0 -1 No No No No

LS-5 0 0 No No No No


LS-7 1 -1 No No No No


LS-9 1 1 No Slight No Slight

4.1.10 Particle Size Distribution (PSD) and Ζ-Potential Analysis

From the results of the Pseudoternary phase diagram was prepared for the Lercanidipine

HCL system by using Capmul MCM, Polysorbate 20 and Transcutol P. Formulations LS-1

to LS-9 were selected from the diagram and further characterized for particle size and zeta

potential. The droplet size of the SNEDDS is a decisive factor in the self-emulsification

process as the rate and extent of drug release as well as drug absorption determined by

droplet size. Also, it has been established that the smaller particle size of the SNEDDS

leads to a more rapid absorption and leads to enhancement of bioavailability of the

formulation [4].


84

TABLE 4.12: Particle Size Distribution of the Various Lercanidpine Hydrochloride

SNEDDS Formulations

Formulation code Size (nm)

LS-1 101.5

LS-2 97

LS-3 105.5

LS-4 101

LS-5 50

LS-6 82

LS-7 286

LS-8 245

LS-9 225

Fig. 4.9 and 4.10 show the particle size distribution and zeta potential of Lercanidipine

HCL SNEDDS respectively. The average particle size of Lercanidipine HCL SNEDDS is

as shown in Table 4.12. The optimal batch was LS-5 with mean particle size 50 nm in

water.

The resulting nanoemulsion produced was with a small mean size and a narrow particle

size distribution regardless of the dispersion medium. The charge of SEDDS is also an

important factor that should be checked [5]. Zeta potential of all SNEDDS was measured

using a Coulter counter after dilution with purified water to avoid error caused by the

dispersion medium. A negatively charged emulsion was obtained with Lercanidipine

loaded SNEDDS.

The optimal batch LS-5 had the least zeta potential, i.e. -24.12 mV i.e towards the negative

side. The zeta potential indicates the stability of nanoemulsion. The high value of zeta

potential indicates electrostatic repulsion between two droplets.


85

Size (d.nm) % Intensity St. Dev(d.nm):

_________________________________________________________________________

Z-Average (d.nm): 50 Peak1: 50 95.3 64.09

PDI: 0.267 Peak2: 0.000 0.0 0.000

Intercept: 0.945 Peak2: 0.000 0.0 0.000

Result Quality: Good

FIGURE 4.9: Particle size distribution of formulation Lercanidpine Hydrochloride

FIGURE 4.10 : Zeta potential of Lercanidipine SNEDDS

The DLVO theory states that electric double layer repulsion will stabilize nanoemulsion

where electrolyte concentration in the continuous phase is less than a certain value.


86

4.1.11 Polydispersibility Index (PDI)

Polydispersibility index is the indicator of the size range of particles in the SNEDDS.

SNEDDS having particles less than 100 mm and PDI less than 0.3 termed as ideal

SNEDDS or in other words, particles size having more than 100 mm should be maximum

up to 23%. The results show that formulations LS-5 passed the PDI as it PDI obtained was

0.267 which was less than 0.3.

4.1.12 In Vitro Diffusion Study

Literature study showed that a dialysis method used for SNEDDS for in vitro study. In

this study, dialysis membrane was used as per described in experimental to allow an

increase in the membrane surface area available for transport from the donor to the receiver

phases and, hence, to maintain sink conditions in the donor phase by infinite dilution of the

emulsion in the outer vessel. The revolution speed of the paddle was maintained at a rate of

50 RPM. Aliquots were withdrawn from the flask at periodic time intervals, replaced with

equivalent amounts of fresh media and analyzed by UV spectroscopy at λ max 236 nm.

The faster release from SNEDDS may be endorsed by the fact that in this formulation, the

Lercanidipine HCL is a solubilized form and upon exposure to the dissolution medium

produced in small droplets that can dissolve rapidly in the dissolution medium. The release

profile for formulations LS-1 to LS-9 is as shown in the Fig. 4.11. The formulation LS-5

showed the highest release rate among all the liquid SNEDDS formulations i.e. 96.19 % in

60 min which is highest among all batches. In this case, the drug was present in form of

nano globules of nanoemulsion and water was an aqueous phase. Due to the low size of

nanoparticles, drug easily diffuses through the dialysis membrane. Thus, the in-vitro study

concludes that the release of Lercanidipine HCL was greatly enhanced by SNEDDS

formulation. The batch LS-5 was thus taken for further studies and comparison.

Comparison of drug release profiles of various SNEDDS formulations with pure drug and

marketed tablet formulation was shown in Fig. 4.12.

The drug release percentage of Lercanidipine HCL from SNEDDS form was significantly

higher than that of Lercanidipine HCL from a pure drug suspension and Marketed

formulation as the conventional tablet. Order of drug release through the dialysis

membrane was Lercanidipine HCL SNEDDS > Marketed formulation > Pure drug.


87

FIGURE 4.11: The release profile for formulations LS-1 to LS-9 of Lercanidpine

Hydrochloride SNEDDS

FIGURE 4.12 Comparison of Release Profile of Various SNEDDS Formulations with

Pure Drug and Marketed Tablet Formulation

It suggests that Lercanidipine HCL was dissolved from SNEDDS resulting in faster drug

release than pure drug suspension and marketed formulation due to small droplet size and

it can enhance bioavailability. The release rate of the drug from SNEDDS (LS-5) was

faster than other SNEDDS formulations. This revealed that the size of droplet size of

0.00

30.65

51.02

73.58

92.76 95.08 96.19

0.00

20.00

40.00

60.00

80.00

100.00

120.00

0 10 20 30 40 50 60

% D

rug

Diff

usio

n

Time (Min)

Lercanidipine HCl SNEDDS

L1

L2

L3

L4

L5

L6

L7

L8

L9

0.00

30.65

51.02

73.58

92.76 95.08 96.19

0.00

21.51

36.8245.36

58.29

72.32 74.85

0.00

10.5719.96

30.08

41.95 43.29 46.51

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

90.00

100.00

0 10 20 30 40 50 60% D

rug

Diff

usio

n

Time (Min)

Lercanidipine HCL

Lercanidipine HClSNEDDSTablet


88

nanoemulsion could affect the release rate of drug positively and it might suggest that the

release rate of the drug could be controlled by regulating mean particle size

4.1.13 Optimization of Lercanidpine Hydrochloride SNEDDS Formulation

4.1.13.1Experimental Design and Statistical Analysis of Dispersion Time

In order to optimize the preparation of formulations, the amount of oil Capmul MCM (X1)

and S: CoS ratio Polysorbate 20: Transcutol P (1:1) (X2) was chosen as independent

variables. These two factors that might affect the nano size formulation and three levels of

each factor were selected (Table 4.7) and arranged according to a 32 full factorial

experimental (Table 4.8).

The objective of this study was to formulate SNEDDS of Lercanidpine Hydrochloride by

pre-emulsion ternary phase diagram method and to optimize the effects of formulation

variables on response parameters. Based on preliminary studies, Capmul MCM,

Polysorbate 20 and Transcutol P were chosen as lipid, lipid phase surfactant and aqueous

phase surfactant respectively. Capmul MCM and Polysorbate 20:Transcutol P ratio was

selected as variables and dispersion time as response parameters. A 32 full factorial design

was selected as it helps study the effect on response parameters by changing both variables

simultaneously with a minimum number of experimental runs.

The dispersion time and globule size of the 9 batches (LS-1 to LS-9) showed a wide

variation 36-73 seconds (Table 4.13). The data clearly indicated the strong dependence of

response variables in the selected independent variables.

In order to quantify the effect of formulation variables on the response parameters,

mathematical model construction is helpful in predicting values of response parameters at

any selected values of formulation variables within the boundaries of the design. It may be

the case that the levels of formulation variables which are intermediate between the

selected levels yield an optimum formulation. Design Expert software was used to generate

a mathematical model for each response parameter and the subsequent statistical analysis .

The coefficients of the polynomial equations generated using Design expert for dispersion

time of Lercanidpine Hydrochloride SNEDDS studied are listed in Table 4.14 along with


89

the values of r2. Five coefficients (a to e) were calculated with k as the intercept.

TABLE 4.13: Observed Values of Dispersion Time of Lercanidpine HCL SNEDDS

Formulation code Dispersion Time (second)

LS-1 65

LS-2 46

LS-3 42

LS-4 58

LS-5 36

LS-6 40

LS-7 73

LS-8 52

LS-9 58

Y=k+aX1+bX2+cX1X2+dX1+eX2

The equation was used to obtain estimates of the responses (dispersion time) at various

factor combinations, where the optimum combination was found to be similar to that

corresponding to LS-5 and hence LS-5 was treated as the optimized batch.

Final Equation in Terms of Actual Factors

Dispersion time (seconds) =

+37.11111

+5.00000 * Conc. of Oil

-9.33333 * Conc. Surfactant/Co-surfactant(1:1)

+2.00000 * Conc. of Oil * Conc. Surfactant/Co-surfactant(1:1)

+11.33333 * Conc. of Oil2

+11.33333 * Conc. Surfactant/Co-surfactant(1:1)2


90

TABLE 4.14:Values of Coefficients for Polynomial Equations and r2 for Dispersion

Time Response Variables of Lercanidpine Hydrochloride SNEDDS

Coefficient code Dispersion time (seconds)

K 37.11

A 5

B -9.33

C 2

D 11.33

E 11.33

r2 0.9876

For the dispersion time response, the Model F-value of 47.74 implies the model is

significant. There is only a 0.46% chance that a "Model F-Value" this large could occur

due to noise.P value was found to be 0.0046, with a value less than 0.0500 indicating

model terms are significant.

The "Predicted R-Squared" of 0.8595 is in reasonable agreement with the "Adjusted R-

Squared" of 0.9669."Adeq Precision" measures the signal to noise ratio. A ratio greater

than 4 is desirable. The ratio of 19.100 indicates an adequate signal. This model can be

used to navigate the design space. Since the values of r2 are relatively high i.e 0.9876 for

dispersion time polynomial equations form an excellent fit to the experimental data and are

highly statistically valid.

Three-dimensional response surface plots for the dispersion time response parameter were

constructed to study the effects of both formulation variables simultaneously along with

the behavior of the system.Fig. 4.13, 4.14 and 4.15 points out about the effect of Capmul

MCM and Polysorbate 20: Transcutol P ratio of dispersion time. It can be observed from

Fig. 4.15 that dispersion time increased with increase in Capmul MCM. Polysorbate 20:

Transcutol P ratio had the opposite effect. As the S: Cos increase the dispersion time

decrease.


91

TABLE 4.15 : Analysis of variance for Response Surface - Quadratic Model of Dispersion Time

Source Sum of Squares df Mean

Square F-value p-value

Model 1202.44 5 240.49 47.74 0.0046 significant

A-Conc. of Oil 150.00 1 150.00 29.78 0.0121

B-Conc. Surfactant/Co-surfactant(1:1)

522.67 1 522.67 103.76 0.0020

AB 16.00 1 16.00 3.18 0.1727

A² 256.89 1 256.89 51.00 0.0057

B² 256.89 1 256.89 51.00 0.0057

Residual 15.11 3 5.04

Cor Total 1217.56 8

Factor coding is Actual.

Sum of squares is Type III – Partial

The effective formulation obtained from the factorial design LS-5 containing Capmul

MCM (10%) and Polysorbate 20: Transcutol (90%) ratio showed the possible result from

the expected values of ANOVA.

The close resemblance between observed and predicted response values as per Table 4.16

and Response Surface Plot Fig. 4.13 assessed the robustness of the predictions. These

values indicate the validity of the generated model.


92

TABLE 4.16: Optimized Values Obtained by Applying Constraints on Variables and

Responses

Formulation code Expected Dispersion Time (second)

Observed Dispersion Time (second)

LS-1 66.11 65

LS-2 43.44 46

LS-3 43.44 42

LS-4 57.78 58

LS-5 37.11 36

LS-6 39.11 40

LS-7 72.11 73

LS-8 53.44 52

LS-9 57.44 58

4.1.13.2 Various Schematic Diagrams for Dispersion Time

FIGURE 4.13 : Predicted Vs Actual Dispersion Time Plot of Lercanidpine

Hydrochloride SNEDDS


93

FIGURE 4.14:Contour plot of interaction of Capmul MCM and Polysorbate 20:

Transcutol P Ratio on Dispersion Time

FIGURE 4.15 : Response surface plots of interaction of Capmul MCM and

Polysorbate 20: Transcutol P Ratio on Dispersion Time


94

4.13.3 Experimental Design and Statistical Analysis for Globule Size

In order to optimize the preparation of formulations, the amount of oil (X1) and S: CoS

ratio (X2) was chosen as independent variables. These two factors that might affect the

nano size formulation and three levels of each factor were selected (Table 4.7) and

arranged according to a 32 full factorial experimental (Table 4.8).

The objective of this study was to formulate SNEDDS of Lercanidpine Hydrochloride by

pre-emulsion ternary phase diagram method and to optimize the effects of formulation

variables on response parameters. Based on preliminary studies, Capmul MCM,

Polysorbate 20 and Transcutol P were chosen as lipid, lipid phase surfactant and aqueous

phase surfactant respectively. Capmul MCM and Polysorbate 20: Transcutol P ratio were

selected as variables and globule size as response parameters. A 32 full factorial design was

selected as it helps to study the effect on response parameters by changing both variables


TABLE 4.17 : Observed values of Lercanidpine Hydrochloride SNEDDS obtained by

applying constraints on variables and responses

Formulation code Observed globule size (nm)

LS-1 101.5

LS-2 97

LS-3 105.5

LS-4 101

LS-5 50

LS-6 82

LS-7 286

LS-8 245

LS-9 225


95

The globule size for the 9 batches (LS-1 to LS-9) showed a wide variation from 50-286

nm respectively (Table 4.17). The data clearly indicated strong dependence of response

variables in the selected independent variables.

In order to quantify the effect of formulation variables on the response parameters,

mathematical model construction is helpful in predicting values of response parameters at

any selected values of formulation variables within the boundaries of the design. It may be

the case that the levels of formulation variables which are intermediate between the

selected levels yield an optimum formulation. Design Expert software was used to generate

a mathematical model for each response parameter and the subsequent statistical analysis .

TABLE 4.18 : Values of Coefficients for Polynomial Equations and r2 for Globule

Size Response Variables of Lercanidpine Hydrochloride SNEDDS

Polynomial coefficient values for response variables

Coefficient code Globule size (nm)

K 64.67

A 75.33

B -12.67

C -16.25

D 99

E 19.5

r2 0.9909

The coefficients of the polynomial equations generated using Design expert for dispersion

time and globule size of Lercanidpine Hydrochloride SNEDDS studied are listed in Table

4.18.along with the values of r2. Five coefficients (a to e) were calculated with k as the

intercept.



96


Globule size = 64.6667

75.3333 *Conc. of Oil -12.667 *Conc. Surfactant/Co-surfactant(1:1)

-16.25 Conc. of Oil * Conc. Surfactant/Co-surfactant(1:1)

99 *Conc. of Oil²

19.5 *Conc. Surfactant/Co-surfactant(1:1)²

The equation was used to obtain estimates of the responses (globule size) at various factor

combinations, where the optimum combination was found to be similar to that


TABLE 4.19 : Analysis of Variance for Response Surface - Quadratic Model of

Globule Size

Source Sum of Squares Df Mean


Model 56432.08 5 11286.42 65.19 0.0029 Significant

A-Conc. of Oil 34050.67 1 34050.67 196.67 0.0008


962.67 1 962.67 5.56 0.0996

AB 1056.25 1 1056.25 6.10 0.0901

A² 19602.00 1 19602.00 113.22 0.0018

B² 760.50 1 760.50 4.39 0.1271

Residual 519.42 3 173.14

Cor Total 56951.50 8

Factor coding is Actual.

Sum of squares is Type III – Partial


97

For globule size response, the Model F-value of 65.19 implies the model is significant.

There is only a 0.29% chance that a "Model F-Value" this large could occur due to noise. P

value was found to be 0.0029, with a value less than 0.0500 indicating model terms are

significant.

The "Predicted R-Squared" of 0.9292 is in reasonable agreement with the "Adjusted R-

Squared" of 0.9757."Adeq Precision" measures the signal to noise ratio. A ratio greater

than 4 is desirable. The ratio of 20.733 indicates an adequate signal, thus the proposed

model can be used to navigate the design space.

Since the values of r2 are relatively high for globule size, polynomial equations form an

excellent fit to the experimental data and are highly statistically valid.

TABLE 4.20 : Optimized Values of Lercanidpine Hydrochloride SNEDDS Obtained

by Applying Constraints on Variables and Responses

Formulation code Expected globule

size(nm)

Observed globule

size(nm)

LS-1 104.25 101.5

LS-2 88.33 97

LS-3 111.42 105.5

LS-4 96.83 101

LS-5 64.67 50

LS-6 71.5 82

LS-7 287.42 286

LS-8 239 245

LS-9 229.58 225


98

Three-dimensional response surface plots for each response parameter were constructed to

study the effects of both formulation variables simultaneously along with the behavior of

the system.

Fig. 4.16, 4.17 and 4.18 shows effect of Capmul MCM and Polysorbate 20: Transcutol P

ratio of globule size. It can be observed from the Fig. 4.18 that Capmul MCM had a

positive effect on globule size, i.e. globule size decrease with a decrease in oil. A greater

amount of lipid may have resulted in increasing the size of SNEDDS. Response surface

plots Fig. 4.18 indicates that the Capmul MCM had a greater impact on globule size

compared to surfactant: Co surfactant ratio.

The effective formulation obtained from the factorial design LS-5 containing Capmul

MCM (10%) and Polysorbate 20: Transcutol (90%) ratio showed the possible result from

the expected values of ANOVA.

The close resemblance between observed and predicted response values as per Table 4.20,

Fig. 4.16 assessed the robustness of the predictions. These values indicate the validity of

the generated model.

4.1.13.4 Various Schematic Diagrams for Globule Size

FIGURE 4.16 : Predicted vs actual Globule Size plot of Lercanidpine Hydrochloride

SNEDDS


99

FIGURE 4.17 : Contour plot of interaction of Capmul MCM and Polysorbate 20:

Transcutol P Ratio on Globule size

FIGURE 4.18 : Response surface plots of interaction of Capmul MCM and

Polysorbate 20: Transcutol P (1:1)Ratio on Globule Size


100

4.1.13.5 Experimental Design and Statistical Analysis for Release of Lercanidpine Hydrochloride

In order to optimize the preparation of formulations, the amount of oil (X1) and S: CoS

ratio (X2) was chosen as independent variables. These two factors that might affect the

nano size formulation and three levels of each factor were selected (Table 4.7) and

arranged according to a 32 full factorial experimental Table 4.8).

The objective of this study was to formulate L-SNEDDS of Lercanidpine Hydrochloride

by pre-emulsion ternary phase diagram method and to optimize the effects of formulation

variables on response parameters. Capmul MCM and Polysorbate 20: Transcutol P ratio

was selected as variables and % release as response parameters. A 32 full factorial design

was selected as it helps to study the effect on response parameters by changing both

variables simultaneously with a minimum number of experimental runs.

TABLE 4.21 : % Observed Drug release of Lercanidpine Hydrochloride SNEDDS as

per full factorial design

Formulation Code Observed % Drug release

LS-1 81.79

LS-2 90.36

LS-3 91.79

LS-4 89.29

LS-5 96.19

LS-6 87.26

LS-7 81.55

LS-8 83.93

LS-9 77.98


101

The L-SNEDDS for the 9 batches (LS-1 to LS-9) showed a wide variation in % release

from 77.98 to 96.19 (Table 4.21). The data clearly indicated strong dependence of

response variables on the selected independent variables.

Design Expert software was used to generate a mathematical model for each response

parameter and the subsequent statistical analysis.

TABLE 4.22 : Values of Coefficients for Polynomial Equations and r2 for Response

Variables of Lercanidpine Hydrochloride SNEDDS

Coefficient code Polynomial coefficient values for response

variables for % release Y

K 94.39111

A -3.41333

B 0.73333

C -3.3925

D -6.34667

E -5.21667

r2 0.9388

The coefficients of the polynomial equations generated using Design expert for % release

of Lercanidpine Hydrochloride SNEDDS studied are listed in (Table 4.22) along with the

values of r2. Five coefficients (a to e) were calculated with k as the intercept.

The equation was used to obtain estimates of the responses, i.e. % release at various factor

combinations, where the optimum combination was found to be similar to that



2


102

Final Equation in Terms of Actual Factors:

Percentahge release =

+94.39111

-3.41333 * Conc. of Oil

+0.73333 * Conc. Surfactant/Co-surfactant(1:1)

-3.39250 * Conc. of Oil * Conc. Surfactant/Co-surfactant(1:1)

-6.34667 * Conc. of Oil2

-5.21667 * Conc. Surfactant/Co-surfactant(1:1)2

Since % release of Lercanidpine Hydrochloride L-SNEDDS, the Model F-value of 9.20

implies the model is significant. There is only a 4.86 % chance that a "Model F-Value"

this large could occur due to noise. P value was found to be 0.0486, with a value less than

0.0500 indicating model terms are significant.

TABLE 4.23 : Analysis of Variance for Response Surface - Quadratic Model of % Release

Response: % release (Y)

ANOVA for Response Surface Quadratic Model

Analysis of variance table [Partial sum of squares - Type III]

Source Sum of Squares

Df

Mean Square

F Value

p-value Prob >

F


A-Conc. of Oil 69.91 1 69.91 12.66 0.0379

B-Conc. Surfactant/Co-surfactant(1:1) 3.23 1 3.23 0.58 0.5003

AB 46.04 1 46.04 8.34 0.0632

A^2 80.56 1 80.56 14.59 0.0316

B^2 54.43 1 54.43 9.85 0.0517

Residual 16.57 3 5.52

Cor Total 270.72 8


103

TABLE 4.24: Optimized Values Obtained by Applying Constraints on Variables and

Responses

Formulation Expected % Release Observed % Release

LS-1 82.12 81.79

LS-2 91.46 90.36

LS-3 90.37 91.79

LS-4 88.44 89.29

LS-5 94.39 96.19

LS-6 89.91 87.26

LS-7 77.76 81.55

LS-8 84.63 83.93

LS-9 76.76 77.98

Adeq Precision" measures the signal to noise ratio. A ratio greater than 4 is desirable. The

ratio of 9.191 indicates an adequate signal. This model can be used to navigate the design

space.

Three-dimensional response surface plots for each response parameter were constructed to

study the effects of both formulation variables simultaneously along with the behavior of

the system.


104

Fig. 4.19, 4.20 and 4.21 pointing out about the effect of Capmul MCM and Polysorbate

20: TranscutolP ratio on % release. It can be observed from Fig. 4.21 that % release

increased with increase in Polysorbate 20: Transcutol P ratio.

The effective formulation obtained from the factorial design LS- 5 containing Capmul

MCM (10%) and Polysorbate 20: TranscutolP (90%) ratio showed the possible result

from the expected values of ANOVA.

The close resemblance between observed and predicted response values as per Table 4.24

and Fig. 4.19 assessed the robustness of the predictions. These values indicate the validity

of the generated model.

4.1.13.6 Various Schematic Diagram for Release Time

FIGURE 4.19 : Predicted Vs Actual % Release Plot of Lercanidpine Hydrochloride SNEDDS

Design-Expert® Software% release

Color points by value of% release:

96.19

77.98

Internally Studentized Residuals

No

rma

l %

Pro

ba

bil

ity

Normal Plot of Residuals

-2.00 -1.00 0.00 1.00 2.00

1

5

10

2030

50

7080

90

95

99


105

FIGURE 4.20 : Contour plot of interaction of Capmul MCM and Polysorbate 20:

Transcutol P Ratio on % Release

FIGURE 4.21: Response surface plots of interaction of Capmul MCM and

Polysorbate 20: Transcutol P Ratio on % Release

Design-Expert® Software% release

Design points above predicted valueDesign points below predicted value96.19

77.98

X1 = A: Conc. of OilX2 = B: Conc. Surfactant/Co-surfactant(1:1)

-1.00

-0.50

0.00

0.50

1.00

-1.00

-0.50

0.00

0.50

1.00

75

80

85

90

95

100

%

re

lea

se

A: Conc. of Oil B: Conc. Surfactant/Co-surfactant(1:1)


106

4.1.13.7 Comparision of Full and reduced models for Lercanidipine HCL

Dispersion Time of Lercanidipine HCL

TABLE 4.25 Comparision of Models for Lercanidipine HCL Dispersion Time(Y1)

Response

FM

RM

b0

37.11111

37.11111

b1

5

5

b2

-9.333333

-9.333333

b12

2

-

b11

11.33333

11.33333

b22

11.33333

11.33333

DF SS MS F R2

Regression

FM

5 1202.444 240.4888889 47.74412 0.987589 F cal=

3.176

F tab=

10.127

DF(1,3)

RM 4 1186.444444 296.6111 38.13571 0.974448

Error

FM 3 15.11111 5.037037037

RM 4 31.11111111 7.777778

A full model equation of dispersion time

YDTF =37.11111111+5X1-9.333333333 X2+2X1X2+11.33333333X12+11.33333333 X2

2

The reduced model for dispersion time

YDTR =37.11111111+5 X1 - 9.333333333 X2+11.33333333X12+11.33333333 X2

2

The coefficient of X1 was 5 and X2 was -9.3, which indicated that large negative value of

X2 was predominantly increasing dispersion time of SNEDDS. The regression coefficient

of X1X2 was 2, X12 was 11.33333333, X2

2 was 11.33333333 and which indicated their

positive influence on globule size. When the coefficients of the two independent variables

in Equation YDTF were compared, the value for the variable X2 (b2= -9.3) was found to be

maximum and hence the variable X2 was considered to be a major contributing variable for

dispersion time.

The significance levels of coefficients b12 was found to be P= 0.172724 hence they were

omitted from the full model to generate reduced model. The coefficients b0, b1, b2 and b11


107

and b22 were found to be significant at P < 0.05; hence they were retained in the reduced

model. The reduced model was tested in portions to determine whether the co-efficient b12

contribute significant information for the prediction of dispersion time or not. The critical

value of F for α=0.05 is equal to 3.176 (df= 1,3). Since the calculated value (F= 3.176) is

less than the critical value (F =10.127), it may be concluded that the interaction terms b12

did not contribute significantly to the prediction of globule size and therefore they can be

omitted from the full model to generate reduced model.

Globule size of Lercanidipine HCL

TABLE 4.26: Comparision of Models for Lercanidipine HCL Globule Size(Y2)

Response

FM

RM

b0

64.66667

77.66667

b1

75.33333

75.33333

b2

-12.66667

-12.66667

b12

-16.25

-

b11

99

99

b22

19.5

-

DF SS MS F R2

Regression FM 5 56432.08 11286.42 65.18707 0.99088 F calc

=5.246

Ftab=9.55

DF(2,3)

RM 3 54615.33 18205.11 38.96364 0.95898

Error FM 3 519.4167 173.1389

RM 5 2336.167 467.2333

A full model equation of glo1bule size

YGSF =64.66667+75.33333X1-12.66667 X2-16.25X1X2+99 X12+19.5 X2

2

The reduced model for glo1bule size

YGSR ==77.66667+75.33333X1-12.66667 X2+96 X12

The coefficient of X1 was 75.33333 and X2 was -12.66667, which indicated that large

positive value of X1 was predominantly increasing globule size of SNEDDS. The

regression coefficient of X1X2 was -16.25 indicate its negative influence while X12 was 99

and X22 was 19.5 which indicated their positive influence. When the coefficients of the two

independent variables in Equation YGSF were compared, the value for the variable X1


108

(b1= 75.33333) was found to be maximum and hence the variable X2 was considered to be

a major contributing variable for globule size. Full and reduced model for globule size

The significance levels of coefficients b12 and b22 were found to be P= 0.090069 and

0.127071 respectively hence they were omitted from the full model to generate reduced

model. The coefficients b0, b1, b2 and b11 were found to be significant at P < 0.05; hence

they were retained in the reduced model. The reduced model was tested in portions to

determine whether the co-efficient b12 and b22 contribute significant information for the

prediction of globule size or not. The critical value of F for α=0.05 is equal to 9.55

(df= 2,3). Since the calculated value (F=5.246) is less than the critical value (F =9.55), it

may be concluded that the interaction terms b12 and b22 does not contribute significantly to

the prediction of globule size and therefore they can be omitted from the full model to

generate reduced model.

Release rate of Lercanidipine HCL

DF SS MS F R2

Regression

FM

5 254.1555 50.83110722 9.203521 0.938798 F cal=

9.094996

F tab=19

DF(2,2)

RM 3 153.6921 51.2307 2.188739 0.567706

Error FM 3 16.56902 5.523006481

RM 5 117.0325 23.40649

A full model equation of Release rate

YDRF=94.39111-3.41333X1+0.73333X2-3.3925X1X2-6.34667X12-5.21667X2

2

The reduced model for Release rate

TABLE 4.27: Comparision of Models for Lercanidipine HCL Release Rate (Y3)

Response

FM

RM

b0

94.39111

90.91333

b1

-3.41333

-3.41333

b2

0.73333

0.73333

b12

-3.3925

-

b11

-6.34667

-6.34667

b22

-5.21667

-


109

YDRR =90.91333-3.41333X1+0.73333X2-6.34667X12

The coefficient of X1 was -3.41333 and X2 was 0.73333, which indicated that large

negative value of X1 was predominantly decreasing release of drug of SNEDDS. The

regression coefficient of X1X2 was -3.3925 X12 was -6.34667 and X2

2 was -5.21667

indicated their negative influence. When the coefficients of the two independent variables

in Equation YDRF were compared, the value for the variable X1(b1= -3.41333) was found

to be maximum and hence the variable X1 was considered to be a major contributing

variable for release of drug.

The significance levels of coefficients b12 and b22 were found to be P= 0.063162 and

0.051695 respectively hence they were omitted from the full model to generate reduced

model. The results of statistical analysis are shown in the Table 4.27. The coefficients

b0, b1, b2 and b11 were found to be significant at P < 0.05; hence they were retained in the

reduced model. The reduced model was tested in portions to determine whether the

co-efficient b12 and b22 contribute significant information for the prediction of release rate

or not. The critical value of F for α=0.05 is equal to 9.55(df= 2,2). Since the calculated

value (F=9.094) is less than the critical value (F =19), it may be concluded that the

interaction terms b12 and b22 does not contribute significantly to the prediction of release

rate and therefore they can be omitted from the full model to generate reduced model.

4..1.14 Desirabilities range of Lercanidipine HCL

Desirabilities range from zero to one for any given response. The program combines

individual desirabilities into a single number and then searches for the greatest overall

desirability nearer to 1. A value of one represents the case where all goals are met

perfectly.

By using numerical optimization, a desirable value for each input factor and response can

be selected. Therein, the possible input optimizations that can be selected include: the

range, maximum, minimum, target, none (for responses) and set so as to establish an

optimized output value for a given set of conditions.


110

FIGURE 4.22 : Overlay Plot of Lercanidipine HCL

FIGURE 4.23 : Desirability of Lercanidipine HCL 4.1.15 Stability Study of Lercanidipine HCL SNEDDS Stability study of optimized batch of Lercanidipine HCL SNEDDS (LS-5) was conducted

at two different storage conditions:

1. Room temperature


111

2. Accelerated condition (40°C & 75% RH)

Stability study of optimized batch (LS-5) of Lercanidipine HCL SNEDDS was used for

both conditions. Stability chamber was used for accelerated condition. The globule size is

the most important parameter for activity and physical stability of any Nano sized

formulation. In addition to change in globule size, assay was also carried out periodically

to determine the stability of drug in the formulation at various storage conditions.

4.1.15.1 Change in Globule Size and Zeta Potential Upon Stability

Globule size and Zeta potential of optimized batch of Lercanidipine HCL SNEDDS

(LS-5) was measured at periodic intervals. Globule size and Zeta potential were measured

after 1, 3 and 6 months. The results are recorded in Table 4.28 and Table 4.29.

TABLE 4.28 : Globule Size Analysis Upon Stability

Stability Conditions

Optimized Batch

Average of Globule Size (D90) (nm)

Initial 1 Month 3 Month 6 Month

Room Temperature LS-5 50nm 51.45 55.47 70.47

Accelerated Conditions LS-5 50nm 51.84 57.15 71.55

TABLE 4.29 : Zeta Potential Analysis Upon Stability


Optimized Batch

Zeta Potential (mV)

Initial 1 Month 3 Month 6 Month Room

Temperature LS-5 -24.12 -23.42 -23.26 -22.18

Accelerated Conditions LS-5 -24.12 -23.45 -22.72 -21.15

4.1.15.2 Drug content determination upon stability

Drug content determination of Lercanidipine HCL in the optimized SNEDDS (batch LS-5)

kept on stability was carried out. Table 4.30 showed results of chemical drug stability

during different storage conditions. It can be concluded that there was no significant


112

change in drug amount during 6 months of storage. The optimized SNEDDS formulation

was found to be chemically stable.

TABLE 4.30: Drug Content Determination Analysis Upon Stability


Optimized Batch

% Assay (For Lercanidipine HCL)


Room Temperature LS-5 100.2 ± 0.45 99.8 ± 0.44 99.2 ± 0.76 98.7 ± 0.25

Accelerated Conditions LS-5 100.2 ± 0.26 99.5 ± 0.23 98.5 ± 0.84 98.3 ± 0.26


113

4.2 Result for SNEDDS of Cinacalcet HCL

4.2.1 Identification of Cinacalcet HCL

Recognition of the procured drug sample Cinacalcet HCL and ensuring its purity is a

requirement before proceeding with the formulation development. The identification tests and

the inferences for the drug sample based on its appearance, solubility and melting point

determination are summarized in Table 4.31.

TABLE 4.31 : Identification of Cinacalcet HCL

Parameters Observations Reported [6] Inferences

Appearance

Cinacalcet HCL is a

hite to off-white,

crystalline solid

Cinacalcet HCL is a

White to off-white,

crystalline Solid

Complies

Solubility

Soluble in methanol

or 95% ethanol, but

merely somewhat

Soluble in Water

Soluble in methanol

or 95% ethanol, but

only slightly

Soluble in Water

Complies

Melting Point 175-177°C 175-177°C [7] Complies

Compliance of the observations with respect to the reported specifications verifies the sample

to be of the drug Cinacalcet HCL.Various functional groups present in the API sample were

determined by Fourier-transform infrared (FT-IR) spectroscopy and compared with the

standard spectra of Cinacalcet HCL for confirmation. The observed IR spectra of Cinacalcet

HCL are shown in Fig. 4.29. It was verified and resolved that the procured sample was of

Cinacalcet HCL and the sample was employed for all further investigations.

4.2.2 Scanning and calibration curve preparation

4.2.2.1 Scanning and calibration curve preparation of Cinacalcet HCL in methanol [8]

The standard stock solution of Cinacalcet HCL was prepared in methanol as per the method

described in experimental section and scanned by UV Visible spectrophotometer between 200


114

to 400 nm. The UV absorption spectrum of Cinacalcet HCL showed λmax at 281 nm as

shown in Fig. 4.24.

A calibration curve was prepared in methanol in the range of 2.5-60 μg/ml by UV-Visible

spectrophotometer. This procedure was performed in triplicate to validate the calibration

curve. The data is given in Table 4.32.

FIGURE 4.24 : Scanning of Cnacalcet HCL in Methanol

Table 4.32 shows the mean absorbance values of the solutions along with the standard

deviation values. As shown in Fig. 4.25, Cinacalcet HCL follows Beer- Lambert’s law and a

regression equation was found to be y = 0.015x + 0.020 with the regression coefficient

(0.999) in methanol indicating that the absorbance and concentration of drug are linearly

related.


115

Stock Standard preparation for Linearity

Accurately weighed about 36.7mg Cinacalcet Hydrochloride (equivalent to 33.3mg

Cinacalcet) standard was transfered in to 200mL volumetric flask and 5 mL of methanol

was added and sonicate to dissolve. The solutiuon was diluted to volume with dissolution

medium and mixed well.

TABLE 4.32 : Calibration Curve Data of Cinacalcet HCL in Methanol

Sr. No. Conc (µg/mL)

Absorbance at 281nm

1 I II III Mean STD DEV

2 2.5 0.053 0.04 0.056 0.050 0.008505

3 5.0 0.1 0.11 0.1 0.103 0.005774

4 10.0 0.17 0.16 0.18 0.170 0.01

5 20.0 0.35 0.34 0.36 0.350 0.01

6 30.0 0.51 0.5 0.53 0.513 0.015275

7 40.0 0.66 0.65 0.66 0.657 0.005774

8 50.0 0.821 0.81 0.84 0.824 0.015177

9 60.0 0.956 0.95 0.98 0.962 0.015875

FIGURE 4.25 : Calibration Curve of Cinacalcet HCL in Methanol

y = 0.0159x + 0.0205R² = 0.999

0

0.2

0.4

0.6

0.8

1

1.2

0 10 20 30 40 50 60 70

Abs

orba

nce

Conc (µg/mL)

Cinacalcet HCl


116

TABLE 4.33 : Calibration Curve Data of Cinacalcet HCL by HPLC

Column : Waters X-bridge shield RP18, 150mm x 4.6mm, 3.5µm

(Part No.186003045) or equivalent

Mobile phase : 0.1% v/v Ortho-phosphoric acid: Acetonitrile (55:45)

Flow Rate : 1.3 mL/min

Wavelength : 220 nm

Injection volume : 10Μl

Column temperature : 35°C

Run time : 5 minutes

Diluent : Dissolution media - 0.05N Hydrochloric acid

TABLE 4.34 : Linearity and Range

Linearity

Level Target concentration %

Target

Concentration

(µg/ml)

Stock

solution (ml)

Final

Volume (ml)

Level-1 20% of 0.033mg/mL 6.65 1 25

Level-2 50% of 0.033mg/mL 16.63 5 50

Level-3 80% of 0.033mg/mL 26.6 4 25

Level-4 100% of 0.033mg/mL 33.25 5 25

Level-5 120% of 0.033mg/mL 39.9 6 25


117

Linearity solution preparation

Specified amount of standard stock solution was transferred to specified volumetric flasks

as given in Table 4.34 and the volume was made up to the mark with dissolution medium.

Linearity was established across the range of the analytical procedure. A series of

standard preparations was prepared over a range of 20% of the lowest sample

concentration to 120% of the highest sample concentration.

TABLE 4.35: Observations for Linearity

Linearity level Linearity level (%)

Actual concentration (µg/mL)

Peak responses (Mean)

STDEV

Level 1 20% of 0.033mg/mL 6.65 572191 20.1

Level 2 50% of 0.033mg/mL 16.63 1416753 31.2

Level 3 80% of 0.033mg/mL 26.6 2260373 20.4

Level 4 100% of 0.033mg/mL 33.25 2805963 12.3

Level 5 120% of 0.033mg/mL 39.9 3364569 29.5

Slope 83943

Y-Intercept 18476

Correlation coefficient (r) 0.999

As shown in Fig. 4.26 and regression equation was found to be y = 83,942.691x + 18,475.934

with regression coefficient R² = 0.999.


118

FIGURE 4.26 : Calibration Curve of Cinacalcet HCL by HPLC

FIGURE 4.27: HPLC Chromatogram of Cinacalcet HCL in Dissolution Medium

572191

1416753

2260373

2805963

3364569

y = 83,942.691x + 18,475.934

R² = 0.999

0

500000

1000000

1500000

2000000

2500000

3000000

3500000

4000000

0 10 20 30 40 50

Are

a

Concentration (µg/mL)

Calibration Curve Cinacalcet


119

4.2.3 Screening of oil and surfactant/co-surfactant for Cinacalcet HCL

Lipid excipients are comprised of a large group of physically and chemically diverse

glycerides, which may be applied in simple (single oil solutions of the drug substance) or in

more complex nanocarriers (SMEDDS/SNEDDS, drug dissolved in the mixture of glycerin,

surfactant and or cosolvent), with considerable flexibility in formulation design .

Non-ionic surfactants were used in most of the investigation about SNEDDS because they are

less toxic and less affected by pH and ionic strength. Appropriate vehicles should have the

good solubilizing capacity for the drug substance, which is all important in composing a

SNEDDS. The results of solubility of Cinacalcet HCL in some vehicles are shown in Fig.

4.28. Table 4.36 shows solubility of Cinacalcet HCL in various vehicles along with their

generic names. The addition of co-solvent with surfactant was reported to improve

dispersibility. In this work it was found that Peuroco K 22 Captex-200 P, Captex 355 EP and

Labrafac PG have very low efficiency for Cinacalcet drug solubility and thus not selected for

expression. From the solubility data it was observed that Capmul MCM, Capmul MCM EP,

Capmul GMO oil have high solubility. Q-pan 20, PEG 400, acconon C30,Aconon MC8-2,

acconon C18 Lauroglycol 90, Caproyl PG MC, polysorbate 20 and polysorbate 80 have high

solubility of the drug. Series of combination tried to obtain better emulsification by using

Capmul MCM, Capmul MCM EP and Capmul GMO along with various surfactant and Co

surfactant combination. Best emulsification obtained from Capmul MCM with Polysorbate 80

as surfactant and PEG 400 as Co surfactant.

Solubility study of Cinacalcet HCL in various vehicles (oils, surfactants, co surfactants and

distill water) done at 25˚C.


120

TABLE 4.36: Solubility Study of Cinacalcet HCL in Various Vehicles

Vehicles Mean+Std dev

Pureco k 22(Corn oil, hydrogenated) 0.13 +0.00

Labrafil M 2125 CS (Linoleoyl Polyoxyl-6 glycerides) 16.80 +0.33

Acconon C30(Polyoxyethylene (30) coconut glycerides) 43.00 +0.67

Acconon C 80( Polyoxyethylene 80) coconut glycerides) 114.53 +2.53

Capmul MCM- EP(Mono- and Di-Glycerides) 224.00 +2.00

Acrysol 14.87 +0.60

Q-pan 20( Sorbitan monolaurate) 46.60 +0.13

Polysorbate 80(Polyoxyethylene (80) sorbitan monolaurate) 19.80 +0.73

Polysorbate 20(Polyoxyethylene (20) sorbitan monolaurate) 26.82 +0.15

Sefsol 218(Propylene Glycol Caprylate) 87.80 +2.20

Capmul MCM(Mono-diglyceride of medium chain fatty acids

(mainly caprylic and capric) 111.40 +2.00

Lauroglycol 90(Propylene glycol monolaurate ) 40.53 +0.13

Transcutol P(Highly purified diethylene glycol monoethyl ether ) 211.60 +1.20

Capryol PG MC( Propylene glycol monocaprylate (type I) NF) 30.80 +0.13

Plurol oleique CC 497(Polyglyceryl-3 dioleate NF) 19.47 +0.27

Captex 200 P(Propylene Glycol Dicaprylate/Dicaprate) 2.27 +0.07

Capmul PG 12 EP/NF(Type II Propylene Glycol Monolaurate) 46.47 +1.07

Capmul GMO 50 EP/NF(Glycerol Monooleate EP) 47.67 +0.60

Aconon MC8-2(Caprylocaproyl Macrogolglycerides) 41.00 +1.53

Captex-355 EP/NF (Medium-Chain Triglycerides) -1.33+0.29

Labrafac PG(Propylene glycol dicaprylate) -0.93 +0.00

PEG 400(Polyethylene Glycol 400) 46.00 +0.24037

*Mean ± SD, n=3


121

FIGURE 4.28 : Solubility Chart of Cinacalcet HCL in Various Solvent

4.2.4 Drug and surfactant compatibility study

4.2.4.11Incompatibility study of Cinacalcet HCL by infrared spectroscopy

FIGURE 4.28 B: FTIR of Cinacalcet HCL with Excipients Capmul MCM, Polysorbate 80 and PEG 400

-50 0 50 100 150 200 250

Pureco k 22Labrafil M 2125 Cs

Acconon C30Acconon C 80

Capmul MCM- EPAcrysol

Q-pan 20Polysorbate 80Polysorbate 20

Sefsol 218Capmul MCM

Lauroglycol 90Transcutol P

Caproyl PG MCPlurol oleique CC 497

Captex 200 PCapmul PG 12 EP/NF

Capmul GMO 50 EP/NFAconon MC8-2

Captex-355 EP/NFLabrafac PG

Peg 400

Solubility mg/ml

Ve

hic

les

4000.0 3600 3200 2800 2400 2000 1800 1600 1400 1200 1000 800 600 400.011.5

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30.0

cm-1

%T

P kin3982393439103885

38093780

34382925

2868

21341967

1736

1649

14611353

1294

1251

1109

946

882848

724

580

FIGURE 4.28 A : FTIR of Cinacalcet HCL

4000.0 3600 3200 2800 2400 2000 1800 1600 1400 1200 1000 800 600 400.0 4.0 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50.0

cm-1

%T

Cinacalcet HCL APII 3842 3787

3435 3181

3052

2962 2863

2797 2751 2712

2643

2512

2429

2362 2299 2204 2088 1998

1950 1892 1829 1794 1719

1588

1517

1453

1402 1380

1329

1254

1198

1167

1128

1072

1019 980

937 920

897 877 845

799 776

747 731

703

662

612 569 540 523

471 452 416


122

FIGURE 4.29 : Overlay of FTIR of Cinacalcet HCL and Cinacalcet HCL with Excipients

The drug Cinacalcet HCL was taken in pure form and FTIR spectra were recorded between

4000-400 cm-1

The excipients taken in formulation are Capmul MCM (Glyceryl monocaprylate as oil),

Polysorbate 80 surfactant and PEG 400 as Co surfactant.

FTIR spectra showed that the characteristic bands of Cinacalcet Hydrochloride or each

excipients alone were not altered in mixtures indicating no interactions between Cinacalcet

Hydrochloride and the selected excipients as shown in above images.

The drug Cinacalcet HCL was taken in pure form and FTIR spectra were recorded between

4000-400 cm-1

The excipients taken in formulation are Capmul MCM (Glyceryl monocaprylate as oil),

PEG 400 surfactant and Polysorbate 80 as Co surfactant.

FTIR spectra showed that the characteristic bands of Cinacalcet Hydrochloride or each

excipients alone were not altered in mixtures indicating no interactions between Cinacalcet

Hydrochloride and the selected excipients as shown in above Fig. 4.28 and 4.29


123

4.2.5 Pseudoternary Phase Diagram

L-SNEDDS form fine O/W emulsions with only by gentle agitation, upon their incorporation

into the aqueous phase. The selection of oil and surfactant, and the combining proportion of

oil to S/CoS, play a prime function in the organization of the nanoemulsion. This can be seen

by a pseudo ternary phase diagram as it differentiates the nanoemulsion region from that of

nanoemulsion region.


Polysorbate 80 :PEG 400 : 1: 1


Polysorbate 80 :PEG 400 : 2: 1


Polysorbate 80: PEG 400 : 3: 1


Polysorbate 80: PEG 400 : 4 : 1

FIGURE 4.30 : Pseudoternary Phase Diagrams of Capmul MCM (Oil), Polysorbate 20/

Transcutol P (S/Cos)


124

TABLE 4.37: Calculation of HLB of Capmul MCM (Oil), Polysorbate 280/PEG 400 (S/Cos)(2:1)

oil surfactant HLB of oil ratio wise

HLB of surfactant ratio wise

Final Mixed HLB

HLB 6 HLB HLB of S/CO S 14.37 2:1

100 0 6 0 6 90 10 5.4 1.437 6.837 80 20 4.8 2.874 7.674 70 30 4.2 4.311 8.511 60 40 3.6 5.748 9.348 50 50 3 7.185 10.185 40 60 2.4 8.622 11.022 30 70 1.8 10.059 11.859 20 80 1.2 11.496 12.696 10 90 0.6 12.933 13.533 0 100 0 14.37 14.37

Surfactant micelles are spherical aggregates of the polysorbates with the ethylene oxide

subunits pointing outwards in contact with the surrounding solution may produce negative

zetapotential and the hydrocarbon tails in the center away from the water. The interior

properties of the micelles are similar to those of liquid hydrocarbon. As the surfactant

concentration increases and the surfaces become saturated the monomers in solution associate

into micelles. This normally occurs within a narrow concentration range and is referred to as

the critical micelle concentration or CMC.The ethylene oxide chains hydrogen bond with

water maintaining the solubility of the surfactant molecules.Polysorbate 80 which is

composed of longer hydrocarbon chains. oleic acid containing component of polysorbate 80 is

≥58% of its total. The remaining fatty acids are a mixture of both saturated and unsaturated

fatty acids esters present in both polysorbate 80 solutions.

Ternary phase diagram was constructed in the absence of Cinacalcet HCL in order to get the

self-emulsifying regions and suitable concentration of oil, surfactant and co-surfactant. Based

on solubility Capmul MCM was used as oil phase, Polysorbate 80 was used as surfactant and

PEG 400 was used as a co-surfactant for constructing different ternary phase diagrams. The


125

spontaneous emulsifying properties were observed visually as well as by particle size

analysis.

In the present study for phase behavior studies Capmul MCM was tested as oil, with

Polysorbate 80 and PEG 400 as the S/CoS mixture for Cinacalcet SNEDDS. All the

emulsions were stable at zero time and this may be ascribable to the higher HLB value of

Polysorbate 80 (HLB-15) and higher solubilising capacity of Polysorbate 80. After observing

clarity, stability after 48 h, it was noted that preparations with an S/CoS ratio of 2:1 produced

stable emulsions and was with largest area found.Therefore, formulating SNEDDS with the

surfactant/Co surfactant ratio of 2:1 is a better option from a stability point of view.

4.2.6 Factorial design for optimization of Cinacalcet HCL SNEDDS

4.2.6.1 Selection of Concentration of Oil, Surfactant and Cosurfactant

The selection of variable was based on the results of solubility data for Cinacalcet HCL in oils

and surfactants/co-surfactants, emulsifying ability of surfactant/co-surfactant, solubilization

capacity and Pseudo ternary phase diagram.

Capmul MCM was found satisfactory as oil, Polysorbate 80 and PEG 400 were found best as

surfactant and cosurfactant on the basis of solubility data. The ratio of Polysorbate 80 and

PEG 400 was selected as 2:1.Capmul MCM oil and Polysorbate 80: PEG 400 mixture (2:1)

was used to find their suitable concentration in formulation development of SNEDDS of

Cinacalcet HCL. Preliminary batches and their results of dispersion status and dispersion time

were presented in Table 4.38.

Along the basis of the results of preliminary trials (Table 4.38), concentration of Capmul

MCM oil (0.3ml) and Concentration of Polysorbate 80: PEG 400mixture (2:1) (2.7ml) was

created as preliminary parameters for formulation development of Cinacalcet HCL SNEDDS.

Concentration of Capmul MCM oil and Concentration of surfactant/Cosurfactant plays an

important function in a stable formulation of Self Nanoemulsifying drug delivery system

(SNEDDS); therefore both were chosen as independent variables in a factorial design.


126

TABLE 4.38 : Preliminary Trials for Development of Cinacalcet HCL SNEDDS

Preliminary Batches Oil (%)

S: cos (2:1) (%)

Dispersion Dispersion time (Seconds)

P1 28.57 71.43 Turbid 78









P10 10 90 Clear & Transparent 61

P11 33.33 66.67 Turbid 81

P12 25 75 Turbid 79

P13 20 80 Turbid 77



4.2.6.2 32 Full Factorial Designs for Optimization of Oil and Surfactant : Cosurfactant

in Formulation Development of Cinacalcet HCL SNEDDS

The preliminary trials were carried out using different concentration of Capmul MCM oil

(0.3ml – 0.5ml), Polysorbate 80 and PEG 400 (2:1) (1 – 2.7 ml). The outcome of preliminary

trials conducted with 0.3ml of Capmul MCM oil was found satisfactory compared to other

concentration. Apart from Capmul MCM oil concentration, Concentration of Polysorbate 80:


127

PEG 400mixture (2:1) was likewise important in formulation development of SNEDDS and

90 % of Polysorbate 80: PEG 400mixture (2:1) was found appropriate in preliminary work.

Hence 32 factorial design was employed using concentration of Capmul MCM oil and

concentration of surfactant/Cosurfactant as independent variable X1 and X2 respectively.

Coded and actual value of independent variable are shown in Table 4.39. The runs for

factorial batches were presented in Table 4.40.

TABLE 4.39: Factors and Levels of Independent Variables in 32 Full Factorial Design

for Formulation of Cinacalcet HCL SNEDDS

Independent variables Level

Low (-1) Medium (0) High (+1)

Capmul MCM oil concentration (X1) (ml) 0.2 0.3 0.4

Polysorbate 80: PEG 400 (2:1) concentration (X2) (ml) 2.4 2.7 3

TABLE 4.40: 32 Full Factorial Design for Formulation of Cinacalcet HCL SNEDDS

Batches X1 X2 Capmul

MCM oil (ml)

Polysorbate 80: PEG 400 (2:1)

(ml)

Dispersion Time

CS-1 -1 -1 0.2 2.4 64

CS-2 0 -1 0.3 2.4 68

CS-3 1 -1 0.4 2.4 73

CS-4 -1 0 0.2 2.7 56

CS-5 0 0 0.3 2.7 61

CS-6 1 0 0.4 2.7 73

CS-7 -1 1 0.2 3.0 54

CS-8 0 1 0.3 3.0 59

CS-9 1 1 0.4 3.0 74


128

4.2.7 Effect of dilution on SNEDDS of Cinacalcet HCL by distilled water

Physical compatibility of the water-insoluble drug Cinacalcet HCL with various surfactants

and co-surfactants were carried away to mark the physical as well as chemical compatibility.

As shown in Table 4.41, all the formulations passed the physical as well as chemical

compatibility tests. The formulations did not indicate any modifications during the

compatibility studies and were found to be unchanging. Further studies were carried out using

this formulation.

TABLE 4.41 : Effect of Dilution on SNEDDS of Cinacalcet HCL by Distilled Water

Formulation Precipitation Crystallization Phase

separation Colour change

CS-1 No precipitation No

crystallization

No phase

separation

No colour

change


crystallization

No phase

separation

No colour

change


crystallization

No phase

separation

No colour

change


crystallization

No phase

separation

No colour

change


crystallization

No phase

separation

No colour

change


crystallization

No phase

separation

No colour

change


crystallization

No phase

separation

No colour

change


crystallization

No phase

separation

No colour

change


crystallization

No phase

separation

No colour

change


129

All Cinacalcet HCL formulations were categorized by visual inspection after drop wise

dilution of preconcentrate SNEDDS on the basis of clarity and apparent stability of the

resultant emulsion.

Visual assessment was done in a glass beaker at room temperature. The contents were gently

agitated by magnetic stirrer. They were discovered immediately, after dilution with 250 mL

water for precipitation of drug, crystallization phase separation, and color change. The

dispersion was observed for each formulation after dilution with distilled water.

4.2.8 Viscosity, Refractive Index, % Transmittance and pH

Rheological techniques were used to check viscosity of SNEDDS systems. It is well proven

that the formulation has a viscosity similar to that of water i.e.1.0 forms SNEDDS having

O/W nanoemulsion with water as external phase. The effects of viscosity are as depicted in

Table 4.42. The pH of the SNEDDS depends on excipients used in the formulation.

TABLE : 4.42: Viscosity and pH of Various Cinacalcet HCL SNEDDS Formulations

Formulation code

Coded Factor Level Viscosity (mpa.s)

Refractive

Index

%

Transmittance X1:Capmul MCM

X2: S: Cos

CS-1 -1 -1 0.895 1.354 95.46

CS-2 0 -1 0.897 1.334 97.37

CS-3 1 -1 0.899 1.357 95.81

CS-4 -1 0 0.892 1.341 98.45

CS-5 0 0 0.894 1.346 92.45

CS-6 1 0 0.898 1.343 97.27

CS-7 -1 1 0.891 1.334 100

CS-8 0 1 0.893 1.357 98.25

CS-9 1 1 0.910 1.364 98.89


130

It is observed that zeta potential may vary with the alteration in the pH, which in turn also

affects the stability of the preparation. All the SNEDDS of Cinacalcet HCL formulations

showed pH values in the orbit of 5.1 to 6.0. Thus pH is not affecting stability. Thus, it can be

augured that the drug is not entering into the external phase and remains in the internal form.

Since, SNEDDS with O/W, water is the external phase. We found that entire system showed

pH of water.

Viscosity of Cinacalcet HCL SNEDDS was measured by using a Brookfield Viscometer at

250C temperature. Spindle S-61 was selected for measurement of viscosity of various

SNEDDS formulations. Viscosity measurement was done at 30 RPM after dilution with

water. pH of Cinacalcet HCL SNEDDS formulation was measured by using pH meter at

room temperature.

The refractіve іndex and percent transmіttance data proved the transparency of system.

4.2.9 Thermodynamic Stability

TABLE 4.43 : Centrifugation and Freeze –Thaw Cycle Parameter of Cinacalcet HCL SNEDDS

Centrifugation Freeze thaw cycle

Formulation Code OIL S/COS Phase

separation Drug

precipitation Phase

separation Drug

precipitation

CS-1 -1 -1 No No No No

CS-2 0 -1 No No No No

CS-3 1 -1 No No No No

CS-4 -1 0 No No No No

CS-5 0 0 No No No No


CS-7 -1 1 No No No No


CS-9 1 1 No No No Slight


131

SNEDDS formed at a peculiar concentration of oil, surfactant and water. Thermodynamically

stable systems show no phase separation, creaming or cracking. The selected formulations

were tested for thermodynamic stability by using centrifugation and freeze thaw cycle. It was

observed that formulation CS-1 to CS-8 passed the thermodynamic stress tests.

The effect of centrifugation and freeze–thaw cycling on phase separation of nanoemulsion

and precipitation of the drug is shown in Table 4.43. Both accelerated tests are carried out to

ascertain the stability of nanoemulsion under stress conditions.

Formulations of nanoemulsion (CS-1 to CS-8) did not exhibit any drug precipitation, phase

separation after centrifugation confirming its stable nature. Similarly, optimized formulation

of nanoemulsion (CS-7) survived freeze–thaw cycles as it was found to be reconstituted

without any phase separation, drug precipitation after exposure to freeze–thaw cycling. The

cloud point should be above 37ºC. In this study, the cloud point of CS-7 was to be 76ºC.

4.2.10 Particle size distribution (PSD) and Z potential analysis:

From the effects of the pseudoternary phase diagram of the Cinacalcet HCL system by using

Capmul MCM, Polysorbate 80 and PEG 400, Formulations C1 to C9 were selected from the

diagram and further characterized for particle size and zeta potential. The droplet size of the

SNEDDS is a decisive element in the self emulsification process as the rate and extent of drug

release as good as drug absorption determined by droplet size. Likewise, it has been shown

that the smaller particle size of the SNEDDS leads to a more rapid concentration and

contributes to enhancement of bioavailability of the expression. Fig. 4.32 and 4.33 indicates

the particle size distribution and zeta potential of Cinacalcet HCL SNEDDS respectively. The

mean particle size of Cinacalcet HCL SNEDDS is as depicted in Table 4.44. The optimal

batch was CS-7 with mean particle size 13.4 nm in water. The resulting nanoemulsion

produced was with a small mean size and a narrow particle size distribution regardless of the

dispersion medium. The charge of SEDDS is also an important element that should be

looked into. A negatively charged emulsion was obtained with Cinacalcet loaded SNEDDS.

This may be because the non-ionic surfactant used in emulsion formulation. The optimal

batch CS-7 had the least zeta potential, i.e. -25.42 mV i.e. towards the negative side. The zeta

potential indicates stability of nanoemulsion. The high value of zeta potential indicates

electrostatic repulsion between two droplets. DLVO theory states that electric double layer


132

repulsion will stabilize nanomulsion where the electrolyte concentration in the continuous

phase is less than a certain value.

FIGURE 4.32 : Particle Size Distribution of Various Cinacalcet HCL SNEDDS

Formulations Size


133

TABLE 4.44: Particle Size Distribution of The Various Cinacalcet HCL SNEDDS Formulations

Factor 1 Factor 2 Response

Std Run A: Conc. Of Oil (Capmul MCM)

B: Conc. of Plysorbate 80/PEG

400 (2:1)

Globule size ( nm)

2 1 -1 -1 49.51

1 2 0 -1 56.8

7 3 1 -1 53.45

3 4 -1 0 28.4

4 5 0 0 28.5

8 6 1 0 42.12

9 7 -1 1 13.4

6 8 0 1 18.5

5 9 1 1 25.84

FIGURE 4.33 : Particle Size Distribution of Formulation Cinacalcet HCL SNEDDS


134

4.2.11 Polydispersibility Index (PDI)

Polydispersibility index is the indicator of the size range of particles in the SNEDDS.

SNEDDS having particles less than 100 nm and PDI less than 0.3 termed as ideal SNEDDS

or in other words, particle size having more than 100 nm should be maximum up to 23%..

The answers show that formulations CS-7 passed the PDI as it was less than 0.3.

polydispersibility index of CS-7 SNEDD formulations obtained was 0.271

4.2.12 In Vitro diffusion study of Cinacalcet HCL

Literature study showed that a dialysis method used for SNEDDS for in vitro study. In this

investigation dialysis membrane was used as per described in experimental to allow an

increase in the membrane surface area available for transport from the donor to the receiver

phases and, hence, to maintain sink conditions in the donor phase by infinite dilution of the

emulsion in the outer vessel. The revolution speed of the paddle was maintained at a rate of

50 RPM. Aliquots were withdrawn from the flask at periodic time intervals, replaced with

equivalent amounts of fresh media and analyzed by HPLC.

The faster drug release from SNEDDS may be endorsed by the fact that in this formulation,

the Cinacalcet HCL is a solubilised form and upon exposure to the dissolution medium

produced in small droplets that can dissolve rapidly in the dissolution medium. The drug

release profile for formulations CS-1 to CS-9 is as depicted in the Fig. 4.34. The formulation

CS-7 showed 97.18 % Cinacalcet HCL 75 min. which was highest release rate among all

the liquid SNEDDS formulations. In this case, the drug was present in the form of nano

globules of nanoemulsion and water were aqueous phase. Due to low size of nano particles,

drug easily release through the dialysis membrane. Thus, in vitro study concludes that the

release of Cinacalcet HCL was greatly enhanced by SNEDDS formulation.The batch CS-7

was thus chosen for further surveys and comparing release profiles of various SNEDDS

formulations with pure drug and marketed tablet formulation was shown in Fig. 4.35.


135

FIGURE 4.34 : Release Profile for Formulations CS-1to CS-9 Of Cinacalcet HCL SNEDDS

The drug release percentage of Cinacalcet HCL from SNEDDS form was significantly higher

than that of Cinacalcet HCL, since the pure drug suspension and Marketed formulation as

conventional tablet. Order of drug release through the dialysis membrane was Cinacalcet HCL

SNEDDS > Marketed formulation > Pure drug.

It suggests that Cinacalcet HCLwas dissolved perfectly from SNEDDS due to small droplet

size, which permits a quicker pace of drug release into the aqueous phase, faster than pure

drug suspension and marketed formulation and it can enhance bioavailability. The drug

release rate of drug from SNEDDS (CS-7) was quicker than other SNEDDS formulation.

This revealed that size of droplet size of nanoemulsion could affect the release rate of drug

positively and it might suggest that the release rate of drug could be controlled by regulating

mean particle size.

0

36.11

56.42

84.73

90.5094.53 95.85 96.33 96.55 97.02 97.18

0

20

40

60

80

100

120

0 2 5 15 20 30 40 50 60 70 75

% D

rug

Diff

usio

n

Time in Min.

C1

C2

C3

C4

C5

C6

C7

C8

C9


136

FIGURE 4.35 : Comparison of Release Profile of Various SNEDDS Formulations with Pure Drug and Marketed Tablet Formulation

4.2.13 Optimization of Cinacalcet HCL SNEDDS Formulation

4.2.13.1Experimental Design and Statistical Analysis of Dispersion Time

The selection of oil Capmul MCM (HLB value 5.5- 6.0) was made on the basis of solubility

and partitioning of L-DIPINE in the oil. Lipid phase surfactant Polysorbate 80 (HLB value

15) and aqueous phase surfactant PEG 400 (HLB 13.1) were chosen along the base of

stability of dispersion prepared by using different surfactants.

In order to optimize the preparation of formulations, the amount of oil (X1) and S: CoS ratio

(X2) were chosen as independent variables.These two factors that might affect the nano size

formulation and three levels of each factor were selected (Table 4.39) and arranged according

to a 32 full factorial experimental design are shown in Table 4.40.

The aim of this work was to formulate SNEDDS of Cinacalcet HCL by pre-emulsion ternary

phase diagram method and to optimize the effects of formulation variables on response

parameters. Based on preliminary studies, Capmul MCM, Polysorbate 80 and PEG 400 were

0

36.11

56.42

84.7390.50

94.53 95.85 96.33 96.55 97.02 97.18

04.99

15.0320.18 22.38 23.60 25.83 28.09 30.37

33.67 36.01

0

19.98

40.16

65.5371.19

73.90 75.63 77.39 79.16 79.95 80.76

0

20

40

60

80

100

120

0 2 5 15 20 30 40 50 60 70 75

% D

rug

diffu

sion

Time in Min.

C7 SNEDDS

Cinacalcet HCl API

Marketed Tablet


137

chosen as lipid, lipid phase surfactant and aqueous phase surfactant respectively. Capmul

MCM and Polysorbate 80: PEG 400 ratio were selected as independent variables and

dispersion time and globule size as response parameters. A 32 full factorial design was

selected as it helps in study of the effect on response parameters by changing both variables


The L-SNEDDS for the 9 batches (CS-1 to CS-9) showed a broad variation in dispersion

time from 54 to 74 seconds (Table 4.45). The data strongly represent the substantial

dependence of response variables on the selected independent variables.

In order to measure the result of formulation variables on the response parameters,

mathematical model construction is helpful in predicting values of response parameters at any

selected values of formulation variables within the boundaries of the invention. It may be the

case that the levels of formulation variables which are intermediate between the selected

levels yield an optimal formulation. Design Expert software was utilized to bring forth a

mathematical model for each response parameter and the subsequent statistical analysis.

TABLE 4.45 : Observed Values of Dispersion Time of Cinacalcet HCL SNEDDS

Formulation code Expected Dispersion Time (sec)

Observed Dispersion Time (sec)

CS-1 64.42 64

CS-2 66.33 68

CS-3 74.25 73

CS-4 56.67 56

CS-5 61.33 61

CS-6 72.00 73

CS-7 52.92 54

CS-8 60.33 59

CS-9 73.75 74


138

TABLE 4.46:Values of Coefficients for Polynomial Equations and r2 For Dispersion

Time Response Variables of Cinacalcet HCL SNEDDS

Coefficient code Dispersion time (seconds)

K 61.33333

A +7.66667

B -3.00000

C +2.75000

D +3.00000

E +2.00000

r2 0.9808

Design Expert was used to generate the coefficients value of the polynomial equation as per

following for dispersion time of Cinacalcet HCL L-SNEDDS. The values of r2 obtained was

0.9808. Coefficients a to e were calculated with k as the intercept.


2

Y=+61.33333 +7.66667*X1-3.00000*X2+2.75000*X1X2 +3.00000*X12 +2.00000*X2

2


Dispersion time (seconds) =

+61.33333*

+7.66667* Conc. of Oil

-3.00000* Conc. Surfactant/Co-surfactant(2:1)

+2.75000* Conc. of Oil * Conc. Surfactant/Co-surfactant(2:1)

+3.00000* Conc. of Oil²

+2.00000* Conc. Surfactant/Co-surfactant(2:1)²


139

TABLE 4.47 : Analysis of Variance of Response Surface - Quadratic Model of Dispersion Time




A-Conc. of Oil 352.67 1 352.67 116.48 0.0017


54 1 54 17.83 0.0243

AB 30.25 1 30.25 9.99 0.0508

A² 18 1 18 5.94 0.0926

B² 8 1 8 2.64 0.2025

Residual 9.08 3 3.03

Cor Total 472 8

Factor coding is Actual. Sum of squares is Type III - Partial

The optimum combination was found was similar to that corresponding to CS-7 SNEDDS

and hence the CS-7 formulation was considered as the optimized batch.

For dispersion time response, the Model F-value of 30.58 implies the model is important.

There is only a 0.89% chance that a "Model F-Value" this large could occur due to noise.

P value was found to be 0.0089, with a value less than 0.0500 indicating model terms are

significant.

The predicted r² of 0.7679 is in reasonable agreement with the adjusted r² of 0.9487; i.e. the

remainder is less than 0.2.

Adeq precision measures the signal to noise ratio. A ratio greater than 4 is desirable. Ratio of

15.016 indicates an adequate signal. This model can be used to navigate the design space.

Since the values of r2 are relatively high for the responses, i.e., 0.9808 for dispersion time

polynomial equations form an excellent fit to the experimental data and are highly statistically

valid.


140

Fig. 4.36, 4.37 and 4.38 pointing out about the effect of Capmul MCM and Polysorbate 80:

PEG 400 ratio at disperse time. It can be noted from Fig. 4.38 that dispersion time increased

with increase in Capmul MCM. Polysorbate 80: PEG 400 ratio had the opposite result, as the

S: Cos increase the dispersion time decrease.

Design Expert 11 software was utilized to bring forth a mathematical model for each response

parameter and the subsequent statistical analysis.

The effective formulation obtained from the factorial design CS-7 containing Capmul MCM

(%) and Polysorbate 80: PEG 400 (%) ratio showed the possible result from the anticipated

values of ANOVA.The resemblance was close in between observed and predicted response

values indicating the robustness of the predictions. These values show the robustness of the

generated model.

The independent variables used i.e oil (Capmul MCM) and surfactant: Co surfactant

(Polysorbate 80: PEG 400) demonstrated significant effect on the response, i.e. dispersion

time of the resultant SNEDDS on dilution with double distilled water.

4.2.13.2 Various Schematic Diagram for Dispersion Time

FIGURE 4.36 : Predicted Vs Actual Dispersion Time Plot of Cinacalcet HCL SNEDDS


141

FIGURE 4.37 : Contour Plot of Interaction of Capmul MCM and Polysorbate 80: PEG

400 Ratio at Disperse Time

FIGURE 4.38 : Response Surface Plots of Interaction of Capmul MCM and Polysorbate

80: PEG 400 Ratio On Dispersion


142

The quantitative effect of components at different layer was predicted using polynomial

equation. Response methodology was then applied to forecast the levels of factor X1 and X2

to obtain an optimum formulation with dispersion time 54 seconds. It is observed that

dispersion time increased with increase in Capmul MCM while as the Polysorbate 80: PEG

400 ratio increased the dispersion time decreased.

4.2.13.3 Experimental Design and Statistical Analysis of Globule Size

The aim of the present study was to formulate L-SNEDDS of Cinacalcet HCL by pre-

emulsion ternary phase diagram and to optimize the effects of formulation variables on

response parameters. Capmul MCM and Polysorbate 80: PEG 400 ratio was selected as

variables and Globule size as response parameters. A 32 full factorial design was used as it

helps to examine the effect on response parameters by changing X1 and X2 variables

simultaneously with a minimal bit of experimental runs.

The C-SNEDDS for the 9 batches (CS-1 to CS-9) showed a broad variation in globule size

from 13.4 to 56.8 nm (Table 4.48). The data strongly represent the substantial dependence of

response variables in the selected independent variables.Design Expert 11 software was

utilized to bring forth a mathematical model for each response parameter and the subsequent

statistical analysis. Design expert 11 was used to generate the coefficients value of the

polynomial equation as per following for Globule size of Cinacalcet HCL L-SNEDDS. The

values of r2 obtained was 0.9703. Coefficients a to e were calculated with k as the intercept.


2


SIZE (nm)=

+32.43778+5.01667* Conc. of Oil²

-17.00333* Conc. Surfactant/Co-surfactant(2:1)

+2.12500*Conc. of Oil * Conc. Surfactant/Co-surfactant(2:1)

+0.853333*Conc. of Oil²

+3.24333*Conc. Surfactant/Co-surfactant(2:1)²


143


and hence the CS-7 formulation was considered as the optimized batchresponse, The Model

F-value of 19.62 implies the model is important. There is only a 1.69% chance that an F-value

this large could occur due to noise. P value was found to be 0.0169, with a value less than

0.0500 indicating model terms are significant.

TABLE 4.48 : 32 Full Factorial Designs for Formulation of Cinacalcet HCL SNEDDS

Batch

Factor 1 (X1) Factor 2 (X2) Response

A: OIL B: S/COS RATIO

(2:1) SIZE (nm)

CS-1 -1.00 -1.00 49.51

CS-2 0.00 -1.00 56.8

CS-3 1.00 -1.00 53.45

CS-4 -1.00 0.00 28.4

CS-5 0.00 0.00 28.5

CS-6 1.00 0.00 42.12

CS-7 -1.00 1.00 13.4

CS-8 0.00 1.00 18.5

CS-9 1.00 1.00 25.84

The Predicted R² of 0.7218 is in reasonable agreement with the Adjusted R² of 0.9209; i.e. the

remainder is less than 0.2.

Adeq Precision measures the signal to noise ratio. A ratio greater than 4 is desirable. The

proportion of 12.172 indicates an adequate signal. This model can be used to navigate the

design space.


144

TABLE 4.49 : Values of Coefficients for Polynomial Equations and r2 for Globule Size

Response Variables of Cinacalcet HCL SNEDDS

Coefficient code SIZE (nm)

K 32.43778

A 5.01667

B -17.0033

C 2.125

D 0.853333

E 3.24333

r2 0.9703

TABLE 4.50 : Analysis of Variance for Response Surface - Quadratic Model of Globule

Size

Source Sum of

Squares Df

Mean



A-OIL 151.00 1 151.00 7.69 0.0694

B-S/COS

Ratio 1734.68 1 1734.68 88.34 0.0026

AB 18.06 1 18.06 0.9199 0.4083

A² 1.46 1 1.46 0.0742 0.8030

B² 21.04 1 21.04 1.07 0.3767

Residual 58.91 3 19.64

Cor Total 1985.15 8

Factor coding is Coded. Sum of squares is Type III – Partial


145

Since the values of r2 are relatively high for the responses, i.e., 0.9703 for globule size

polynomial equations form an excellent fit to the experimental data and are highly statistically

valid.

Fig. 4.39, 4.40 and 4.41 pointing out about the effect of Capmul MCM and Polysorbate 80:

PEG 400 ratio of globule size. It can be noted from Fig. 4.41 that globule size increased with

increase in Capmul MCM. Polysorbate 80: PEG 400 ratio had the opposite result. As the S:

Cos increase the Globule size decrease.


and Polysorbate 80: PEG 400 (2:1) ratio showed the possible result from the anticipated

values of ANOVA.

TABLE 4.51 : optimized values obtained by applying constrains on variables and

Responses

Batch Actual Value Globule size (nm) Predicted Value Globule size (nm)

CS-1 49.51 50.65

CS-2 56.8 52.68

CS-3 53.45 56.43

CS-4 28.40 28.27

CS-5 28.50 32.44

CS-6 42.12 38.31

CS-7 13.40 12.39

CS-8 18.50 18.68

CS-9 25.84 26.67


146

4.2.13.4 Various Schematic Diagrams for Globule Size

FIGURE 4.39 : Predicted Vs Actual Globule Size Plot of Cinacalcet HCL SNEDDS

FIGURE 4.40 : Contour Plot of Interaction of Capmul MCM and Polysorbate 80: PEG 400 Ratio of Globule Size


147

FIGURE 4.41 : Response Surface Plots of Interaction of Capmul MCM and Polysorbate 80: PEG 400 Ratio of Globule Size

The resemblance was close in between observed and predicted response values indicate the

robustness of the predictions. These values show the robustness of the generated model.

The dependent variable used oil (Capmul MCM) and surfactant: Co surfactant (Polysorbate

80: PEG 400) demonstrated significant effect on the response, i.e. Globule size of the

resultant SNEDDS on dilution with double distilled water. The quantitative effect of

components at different layer was predicted using polynomial equation. Response

methodology was then applied to forecast the levels of factor X1 and X2 to obtain an

optimum formulation with Globule size 13.4 nm. It is observed that Globule size increased

with increase in Capmul MCM while as the Polysorbate 80: PEG 400 ratio increased the

Globule size decreased.


148

4.2.13.5 Experimental Design and Statistical Analysis for Drug Release

TABLE 4.52 : % Drug Release of Cinacalcet HCL SNEDDS (C1- C9) as Per Full Factorial Design

X1 X2 Response

Std Run A:Conc. of Oil

B:Conc. Surfactant/Co-surfactant(2:1)

Percentage release

2 1 -1 -1 92.7

1 2 0 -1 90.1

7 3 1 -1 88.6

3 4 -1 0 93.2

4 5 0 0 92.48

8 6 1 0 90.32

9 7 -1 1 97.18

6 8 0 1 95.45

5 9 1 1 94.14

The L-SNEDDS for the 9 batches (C1 to C9) showed a broad variation in % release from 88.6

to 97.18 (Table 4.52). The data strongly represent the substantial dependence of response

variables in the selected independent variables.

Design Expert software was utilized to bring forth a mathematical model for each response

parameter and the subsequent statistical analysis. Design expert 11 used to generate The

coefficients value of the polynomial equation as per following for drug release of Cinacalcet

HCL L-SNEDDS the values of r2 obtained was 0.9876.Coefficients a to e were calculated

with k as the intercept.


2

Y=91.99111 -1.67000*X1+2.56167*X2 + 0.265000*X1X2 +0.013333*X12 +1.02833*X2

2


149

TABLE 4.53 : Values of Coefficients for Polynomial Equations and r2 for Dispersion

Time Response Variables of Cinacalcet HCL SNEDDS

Coefficient code % Release

K 91.99111

A -1.67000*X1+

B +2.56167*X2

C + 0.265000 X1 X2

D +0.013333*X12

E +1.02833*X22

r2 0.9876

Final Equation

Percentage release =

+91.99111*

-1.67* Conc. of Oil

+2.56167* Conc. Surfactant/Co-surfactant(2:1)

+0.265* Conc. of Oil * Conc. Surfactant/Co-surfactant(2:1)

+0.013333* Conc. of Oil²

+1.02833* Conc. Surfactant/Co-surfactant(2:1)²


and hence the CS-7 formulation was considered as the optimized batch.

F-value of Cinacalcet HCL, L-SNEDDS for % release was 47.76 implied that the model is

significant.There was only a 0.46% % chance that a "Model F-Value" this large could occur

due to noise. P value was found to be 0.0046, with a value less than 0.0500 indicating model

terms are significant.


150

TABLE 4.54 : Analysis of Variance for Response Surface - Quadratic Model of % Release




A-Conc. of Oil 16.73 1 16.73 68.3 0.0037 B-Conc. Surfactant/Co-surfactant(2:1) 39.37 1 39.37 160.7 0.0011

AB 0.2809 1 0.2809 1.15 0.3628

A² 0.0004 1 0.0004 0.0015 0.972

B² 2.11 1 2.11 8.63 0.0606

Residual 0.735 3 0.245

Cor Total 59.24 8

TABLE 4.55 : Optimized Values Obtained by Applying Constraints on Variables and

Responses

Formulation code Expected % Release Observed % Release

CS-1 92.41 92.7

CS-2 90.46 90.1

CS-3 88.54 88.6

CS-4 93.67 93.2

CS-5 91.99 92.48

CS-6 90.33 90.32

CS-7 97 97.18

CS-8 95.58 95.45

CS-9 94.19 94.14


151

Adeq Precision" measurement gives the signal to noise ratio. Signal to noise ratio greater than

4 is desirable. The proportion of 20.941 indicates an adequate signal. This model can be

used to navigate the design space. The Predicted R² of 0.8919 is in reasonable agreement with

the Adjusted R² of 0.9669; i.e. the remainder is less than 0.2.

Three-dimensional response surface plots were built for each parameter. Fig. 4.42, 4.43 and

4.44 indicates the effect of Capmul® MCM (X1) and Polysorbate 80: PEG 400 ratio (X2) on

% release. It can be noted from Fig. 4.44 that % release increased as increased in Polysorbate

80: PEG 400 ratio increases.

4.2.13.6 Various Schematic Diagram for Release

FIGURE 4.42 : Predicted Vs Actual % Release Plot of Cinacalcet HCL SNEDDS


152

FIGURE 4.43 : Contour Plot of Interaction of Capmul MCM and Polysorbate 80: PEG

400 Ratio on % Release

FIGURE 4.44 : Response Surface Plots of Capmul MCM and Polysorbate 80:PEG 400

Ratio Interaction on % Release


153


and Polysorbate 80:PEG 400 (2:1) ratio showed the possible result from the anticipated values

of ANOVA.

The resemblance was close in between observed and predicted response value indicate the

robustness of the predictions. These values show the robustness of the generated model.

4.2.13.7 Comparison of Full and reduced models for Cinacalcet HCL

Dispersion time of Cinacalcet HCL

TABLE 4.56 : Comparision of Full And Reduced Model For Cinacalcet HCL Dispersion

Time (Y1)

Response

FM

RM

b0

61.33333333

64.66667

b1

7.666666667

7.666667

b2

-3

-3

b12

2.75

-

b11

3

-

b22

2

-

DF SS MS F R2

Regression

FM

5 462.9167 92.58333 30.57798 0.98075565

F calc=

6.192661

F tab=

9.276628

DF(3,3)

RM 2 406.6667 203.3333 18.67347 0.861582

Error FM 3 9.083333 3.027778

RM 6 65.33333 10.88889

A full model equation of dispersion time

YDTF =61.33333333+7.666666667X1-3 X2+2.75X1X2+3X12+2 X2

2

The reduced model for dispersion time

YDTR =64.66667+7.666666667X1-3 X2

The coefficient of X1 was 7.666666667 and X2 was -3, which indicated that large positive

value of X1 was predominantly increasing dispersion time of SNEDDS. The regression


154

coefficient of X1X2 was 2.75, X12 was 3 and X2

2 was 2 which indicated their positive

influence. When the coefficients of the two independent variables in Equation YDTF were

compared, the value for the variable X1(b1= 7.666666667) was found to be maximum and

hence the variable X1was considered to be a major contributing variable for dispersion time.

The significance levels of coefficients b12 ,b11, and b22 were found to be P = 0.050839,

P = 0.092647 and P = 0.20253 respectively and hence they were omitted from the full model

to generate reduced model. The coefficients b0, b1 and b2 were found to be significant at

P < 0.05; hence they were retained in the reduced model. The reduced model was tested in

portions to determine whether the co-efficient b12 ,b11 and b22 contribute significant

information for the prediction of dispersion time or not. The critical value of F for α = 0.05 is

equal to 3.176 (df = 3,3). Since the calculated value (F = 9.276628) is less than the critical

value (F = 3.176), it may be concluded that the interaction terms b12 ,b11, and b22 did not

contribute significantly to the prediction of dispersion time and therefore they can be omitted

from the full model to generate reduced model.

Globule size of Cinacalcet HCL

TABLE 4.57 : Comparision of Full and Reduced Model For Cinacalcet HCL Globule

Size (Y2)

Response

FM

RM

b0

32.43778

35.16889

b1

5.016667

5.016667

b2

-17.0033

-17.0033

b12

2.125

-

b11

0.853333

-

b22

3.243333

-

DF SS MS F R2

Regression

FM

5 1926.239 385.2478 19.61984 0.970326

F calc =

0.688

F tab =

9.28

DF(3,3)

RM 2 1885.682 942.8409 56.87521 0.949896

Error FM 3 58.90688 19.63563

RM 6 99.46416 16.57736


155

A full model equation of globule size

YGSF =32.43778+5.016667X1-17.0033X2+2.125X1X2+0.853333X12 +3.243333X2

2

The reduced model for glo1bule size YGSR =35.16889+5.016667X1-17.0033X2

The coefficient of X1 was 5.016667 and X2 was -17.0033, which indicated that large negative

value of X2 predominantly increasing globule size of SNEDDS. The regression coefficient of

X1X2 was 2.125, X12 was 0.853333 and X2

2 was 3.243333 which indicated their positive

influence. When the coefficients of the two independent variables in Equation were

compared, the value for the variable X2 (b2 = -17.0033) was found to be maximum and hence

the variable X2 was considered to be a major contributing variable for globule size.

The significance levels of coefficients b12, b11 and b22 were found to be P = 0.40826,

P = 0. 0.8030 and P = 0.37674 respectively hence they were omitted from the full model to

generate reduced model. The coefficients b0, b1 , and b2 and b11 were found to be significant

at P < 0.05; hence they were retained in the reduced model. The reduced model was tested in

portions to determine whether the co-efficient b12, b11 and b22 contribute significant

information for the prediction of globule size or not. The critical value of F for α = 0.05 is

equal to 9.28 (df= 3,3). Since the calculated value ( F=0.688 ) is less than the critical value

(F =9.28), it may be concluded that the interaction terms b12, b11 and b22 does not contribute

significantly to the prediction of globule size and therefore they can be omitted from the full

model to generate reduced model.

Cinacalcet HCL release rate

A full model equation of Release rate

YDRF=91.99111-1.67X1+2.561667X2+0.265X1X2-0.013333X12+1.028333X2

2

The reduced model for Release rate

YDRR=92.68556-1.67X1+2.561667X2


156

DF SS MS F R2

Regression

FM

5 58.50241 11.70048 47.75635 0.987592

F calc =

0.04

F tab =

9.276

DF(3,3)

RM 2 56.10622 28.05311 53.75522 0.947141

Error FM 3 0.735011 0.245004

RM 6 3.131206 0.521868

The coefficient of X1 was -1.67 and X2 was 2.561667, which indicated that large positive

value of X2 was predominantly increasing release of drug of SNEDDS. The regression

coefficient of X1X2 was 0.265, X12 0.013333 was and X2

2 was 1.028333 which indicated

their positive influence. When the coefficients of the two independent variables in Equation

YDRF were compared, the value for the variable X2 (b2=2.561667) was found to be maximum

and hence the variable X2 was considered to be a major contributing variable for release of

drug.

The significance levels of coefficients b12, b11, and b22 were found to be P = 0.362768,

P = 0.972005 and P = 0.060604 respectively hence they were omitted from the full model to

generate reduced model. The results of statistical analysis are shown in the Table 4.58. The

coefficients b0, b1 , and b2 and were found to be significant at P < 0.05; hence they were

retained in the reduced model. The reduced model was tested in portions to determine whether

the co-efficient b12, b11, and b22 contribute significant information for the prediction of release

rate or not. The critical value of F for α=0.05 is equal to 9.55(df = 2,2). Since the calculated

value (F = 9.094) is less than the critical value (F = 19), it may be concluded that the

interaction terms b12, b11, and b22 does not contribute significantly to the prediction of release

rate and therefore they can be omitted from the full model to generate reduced model.

TABLE 4.58 : Comparision of Full and Reduced Model For Cinacalcet HCL Release

Rate (Y3)

Response

FM

RM

b0

91.99111

92.68556

b1

-1.67

-1.67

b2

2.561667

2.561667

b12

0.265

-

b11

0.013333

-

b22

1.028333

-


157

4.2.14 Desiribility Range of Cinacalcet HCL

Desirabilities range from zero to one for any given response. The program combines

individual desirabilities into a single number and then searches for the greatest overall

desirability nearer to 0.631. A value of one represents the case where all goals are met

perfectly.

By using numerical optimization, a desirable value for each input factor and response can be

selected. Therein, the possible input optimizations that can be selected include: the range,

maximum, minimum, target, none (for responses) and set so as to establish an optimized

output value for a given set of conditions.

FIGURE 4.45 : Overlay Plot of Cinacalcet HCL


158

FIGURE 4.46 : Desirability of Cinacalcet HCL

4.2.15 Stability study of Cinacalcet HCL SNEDDS Stability study of optimized batch of Cinacalcet HCL SNEDDS(CS-7) was conducted at two

different storage conditions:

1. Room temperature

2. Accelerated condition (40°C & 75% RH)

Stability study of optimized batch of Cinacalcet HCL SNEDDS (CS-7) was used for both

conditions. Stability chamber was used for accelerated condition. The globule size is the most

important parameter for activity and physical stability of any Nano sized formulation. In

addition to change in globule size, assay was also carried out periodically to determine the

stability of drug in the formulation at various storage conditions.

4.2.15.1 Change in Globule size and Zeta potential upon stability

Globule size and Zeta potential of optimized batch of Cinacalcet HCL SNEDDS (CS-7) was

measured at periodic intervals. Globule size and Zeta potential were measured after 1, 3 and 6

months. The results are recorded in Table 4.59 and Table 4.60.


159

TABLE 4.59: Globule Size Analysis Upon Stability


Optimized Batch

Average of Globule Size (D90) (nm)


Room Temperature CS-7 13.4

13.7 14.2 14.5

Accelerated Conditions CS-7 13.4 13.9 14.4 14.8

TABLE 4.60: Zeta Potential Analysis Upon Stability


Optimized Batch

Zeta Potential (mV)


Room Temperature L5 -25.42 -23.72

-18.21

-13.1

Accelerated Conditions CS-7 -25.42 -23.18 -19.47 -12.9

4.2.15.2 Drug content determination upon stability

Drug content determination of Cinacalcet HCL in the optimized SNEDDS (batch C7) kept on

stability was carried out. Table 4.61 showed results of chemical drug stability during

different storage conditions. It can be concluded that there was no significant change in drug

amount during 6 months of storage. The optimized SNEDDS formulation was found to be

chemically stable.

TABLE 4.61: Drug Content Determination Analysis Upon Stability


Optimized Batch

% Assay (±) SD (For Cinacalcet HCL)


Room Temperature CS-7 100.1 ± 0.25 99.6 ± 0.46 99.3 ± 0.46 98.7 ± 0.58

Accelerated Conditions CS-7 100.1 ± 0.28 99.4 ± 0.63 99.1 ± 0.82 98.3 ± 0.28


160

4.3 References

1. [Online].Available:https://pubchem.ncbi.nlm.nih.gov/compound/Lercanidipin_hyd

rochloride [Accessed 4 September 2018].

2. Mohsin, K., Long, M. A., & Pouton, C. W. (2009). Design of lipid-based

formulations for oral administration of poorly water-soluble drugs: precipitation of

drug after dispersion of formulations in aqueous solution. J Pharm Sci, 98(10),

3582-3595.,ISSN: 0022-3549.

3. Nazzal, S., Smalyukh, II, Lavrentovich, O. D., & Khan, M. A. (2002). Preparation

and in vitro characterization of a eutectic based semisolid self-nanoemulsified drug

delivery system (SNEDDS) of ubiquinone: mechanism and progress of emulsion

formation. Int J Pharm, 235(1-2), 247-265. ISSN: 0378-5173.

4. Heo, M. Y., Piao, Z. Z., Kim, T. W., Cao, Q. R., Kim, A., & Lee, B. J. (2005).

Effect of solubilizing and microemulsifying excipients in polyethylene glycol

6000 solid dispersion on enhanced dissolution and bioavailability of ketoconazole.

Arch Pharm Res, 28(5), 604-611. ,ISSN: 0253-6269.

5. Attama, A. A., Nzekwe, I. T., Nnamani, P. O., Adikwu, M. U., & Onugu, C. O.

(2003). The use of solid self-emulsifying systems in the delivery of diclofenac. Int

J Pharm, 262(1-2), 23-28.,ISSN: 0378-5173.

6. Deborah N., Scott J., and David M.(2011) Nanoparticulate cinacalcet

compositions. US Patent Application 0287065A1

7. 364782-34-3 (Cinacalcet hydrochloride) Product Description [Online], http://

www. Chemicalbook. Com / Chemical Product Property _US_CB71176208. aspx.

[Accessed 29 June 2018].

8. Loni, Amruta B., Ghante, Minal R.. and Sawant, S. D. (2012) Spectrophotometric

estimation of cinacalcet hydrochloride in bulk and tablet dosage form., Int J Pharm

Pharm Sci, 4(3), 513-515.,ISSN: 0975-1491.

CHAPTER 5

Summary and Conclusion

5.1 Summary of the Work

Hypertension is a major contributor to the global disease burden, occurring as an insidious

accompaniment to aging populations [1, 2]. Hypertension management aims to reduce the

long-term risk of cardiovascular complications and involves lifestyle modifications and

antihypertensive drug therapy. In recent years, increasing attention has been focused on

SNEDDS to facilitate oral administration. The absolute bioavailability of Lercanidipine is

about 10%, because of the high first-pass metabolism in the fed condition of the patient

[3].

According to the 2004 US Renal Data Report, more than 300,000 patients with end-stage

renal disease (ESRD) require dialysis. In spite of sensational advances in drug, the death

rate for patients with ESRD remains more than 20% every year [4]. Optional

hyperparathyroidism is a genuine entanglement of dialysis and can prompt renal

osteodystrophy and other organ dysfunctions [5, 6]. Cinacalcet is demonstrated for the

treatment of hypercalcemia in patients with parathyroid carcinoma or for auxiliary

hyperparathyroidism in patients with ceaseless kidney sickness who require dialysis [7].In

some embodiments; it was found that the nanoparticulate Cinacalcet compositions exhibit

improved bioavailability as compared to known non-nanoparticulate Cinacalcet

compositions [8].

In the present study, an attempt was made to enhance the solubility, stability and in vitro

drug release of two BCS class II drugs namely Lercanidipine HCL and Cinacalcet HCL by

Chapter 5 Summary and Conclusion

162

formulating them as SNEDDS. The developed formulations were characterized by various

parameters for its ability to form nanoemulsion. Lercanidipine HCL and Cinacalcet HCL

have log P of 6.4 [9] and 6.5[10], respectively making both the drugs suitable candidates

for the development of SNEDDS.

Analytical methods were developed for chosen drugs for the estimation of the drug in

formulations. Samples of received drugs and excipients were subjected to identification

and compatibility study by FTIR. Based on drug solubility in various solvents and their

blends, SNEDDS were prepared. The present research was aimed to explore SNEDDS

formulation development of Lercanidipine HCL and Cinacalcet HCL using 32 factorial

design for improvement in drug release compared to marketed formulation of

Lercanidipine HCL and Cinacalcet HCL respectively. The present research also described

detailing advancement of stable SNEDDS of Lercanidipine and Cinacalcet HCL using oil

and surfactant/co surfactant on the basis of preliminary trials.

The 32 factorial design was utilized with various concentration of oil and surfactant and

co surfactant as independent factors. The dispersion time, globule size and medication

discharge for Lercanidipine HCL and Cinacalcet HCL were chosen as dependent factors.

The optimized batch was selected on the basis of arbitrary criteria using Design Expert

software. The data obtained were statistically analysed by ANOVA and model equations

were generated and contour plots as well as 3D surface plots were constructed for each

response. Optimized formulation assessed by different parameters like particle size,

polydispersity index, zeta potential, solubility and in vitro diffusion study. The

composition of optimized formulation containing Lercanidipine HCL and Cinacalcet HCL

showed that drug release was significantly dependent on selected independent factors.

Optimized formulations were subjected to short term accelerated stability study according

to ICH guidelines. The developed formulations were found stable under tested stability

conditions.

5.2 Achievements with Respect to Objectives The solubility of both BCS class II drugs were enhanced.

FTIR study revealed that all the excipients used were compatible with drugs.

The globule size (less than 100 nm), zeta potential (toward the highest negative side)

and PDI (less than 0.3) of optimal formulations fitted in criteria of ideal SNEDDS.


163

The data analysis of 32 full factorial design used for an optimization of SNEDDS

formulations revealed that the values of selected responses were strongly dependent on

the selected independent variables.

The in vitro study revealed that release of drugs were greatly enhanced by SNEDDS

formulation.

The optimal formulations had the maximum release rate as compared to the marketed

drugs and pure drugs.

Stability studies revealed that the formulations were found stable under tested stability

conditions.

5.3 Major Contribution and Practical Implications of the Work to

Society

Hypertension is a worldwide burden. Hypertension is one of the main sources for

mortality, as it might be asymptomatic however a considerable measure of confusions will

grow quickly and prompting demise. Anticipation and control of hypertension diminishes

mortality, and heart failure.

Secondary hyperparathyroidism is a serious complication of end-stage renal disease and

can lead to renal osteodystrophy and other organ failure. Management of deadly

parathyroid carcinoma presents a challenge because effective medical therapy was not

available. Cinacalcet is a drug of choice for the treatment of hypercalcemia in patients with

parathyroid carcinoma or for auxiliary hyperparathyroidism in patients with ceaseless

kidney sickness who require dialysis.

Based on the results obtained for conducted research, it was concluded that the proposed

objective of the research work of enhancing bioavailability of Lercanidipine HCL and

Cinacalcet HCL was achieved and it can be applied for other drugs of the BCS class II.

Present investigation on SNEDDS of antihypertensive and calcimimetic drugs explored the

possibility of efficacious treatments with dose reduction and dosing frequency for their

administration by oral route. Subsequently, further examinations with improvement and

assessment of nanoformulations of different medications ought to be directed.The


164

nanoformulation approach opens new therapeutic strategies for other diseases for

enhancing treatment success rates.

5.4 Recommendations for Future Research The present investigation was aimed for SNEDDS delivery system intended to be

administered through oral route. Reasonable model for other pharmaceutical medications

ought to be created to evaluate the scope of medication by oral route and their adequacy.

The formulation technique utilized has feasibility for scale-up on industrial scale. Hence,

after clinical trials and fulfilment of other regulatory requirements, the created formulation

has great degree for commercialization and may turn out to be a help to the general public.

5.5 Conclusion

Pharmaceutical drugs which belong to BCS class II have poor oral bioavailability due to

their limited aqueous solubilities. With the present investigations, it may be concluded that

SNEDDS of a poorly soluble drug Lercanidipine HCL and Cinacalcet HCL were

successfully developed and optimized using the systematic approach of design of

experiments (DoE).

Various preliminary experiments were performed for selection of suitable excipients and

formulation technique. Various oils and surfactants and co surfactant were screened

primarily on the basis of solubility of the drug and dispersion time with different

surfactants in trial batches. The compatibility of the excipients with the drug was assured

with FTIR spectroscopy. SNEDDS were prepared using a systematic approach of design of

experiments.After the preliminary experiments, a 32 factorial design used with dispersion

time, particle size and drug release as response variables using Design Expert 11 software

(Stat-Ease, Inc., USA). The data were statistically analysed by ANOVA and model

equations were generated and contour plots as well as 3D surface plots were constructed

for each response. Optimized SNEDDS was evaluated for particle size, polydispersity

index and zeta potential. In this research, an endeavour was made to create stable SNEDDS

to upgrade oral bioavailability of chosen drugs. Thus, the fundamental was to plan and

create nanoemulsion of selected drugs with the goal to increase the bioavailability. Suitable

analytical methods were selected /developed for determining in vitro diffusion study.


165

Optimized formulations were subjected to accelerated stability study according to ICH

guidelines and the formulations were found stable under tested stability conditions.

Lercanidipine HCL is an orally administered ACE inhibitor and Cinacalcet HCL is a

calcimimetic drug with poor solubility, stability and oral bioavailability. The objective of

our investigation was to formulate self nanoemulsifying drug delivery system (SNEDDS)

of Lercanidipine HCL and Cinacalcet HCL using oil, surfactant and co surfactant that

could improve its solubility, stability and oral bioavailability. The composition of

optimized formulation consists of Capmul MCM as oil, Polysorbate 20 as surfactant and

Transcutol P as co surfactant, containing Lercanidipine HCL. Optimized liquid SNEDDS

formulation showed 96.19 % of drug release with 50 nm droplet size, -23.2 mV Zeta

potential and had infinite dilution capability. In vitro drug release of the optimized batch

was highly dependent on selected independent variables with statistical significance

(p <0.05).

Based on the solubility of Cinacalcet HCL in the combination of oil, surfactant and co

surfactant Capmul MCM, Polysorbate 80 and PEG 400 were selected, respectively for the

development of liquid SNEDDS formulation. The optimum formulation showed better

drug release 97.18 % with required droplet size 13.4 nm and Zeta potential -25.42 mV

having infinite dilution capability. In vitro drug diffusion of the optimized batch was

highly dependent on selected independent variables with statistical significance (p <0.05).

SNEDDS of Lercanidipine HCL and Cinacalcet HCL showed better release of drug in

comparison to the orally administered marketed formulation Lerka and Pth Tablet

respectively. Thus, it was concluded from the research that the developed SNEDDS have

better potential of efficacious treatments with reduction of dose and dosing frequency for

their administration by oral route with less side effects and more cost-effective as well

acceptable to patients because of convenience of application.


166

5.6 References 1. John B, Kostis MD. (2003) Treatment of hypertension in older patients: an updated

look at the role of calcium antagonists. Am J Geriatr Cardiol., 12:319–27. ISSN

1751-715X.

2. Whitworth JA. (2003) World Health Organization (WHO)/International Society of

Hypertension (ISH) statement on management of hypertension. J hypertens.,

21(11): 1983.

3. 25 Jul 2012, Lercanidipine Hydrochloride 20mg film coated Tablets, [Online]

https: //www. medicines.org.uk/emc/product/4206/smpc.,[Accessed 27 July 2018].

4. US Renal Data System. USRDS (2004) Annual Data Report. Bethesda, MD:

National Institutes of Health, National Institute of Diabetes and Digestive and

Kidney Diseases, Available at http://www.usrds.org/adr.htm, [Accessed October

18, 2004].

5. Foley RN, Parfrey PS, SarnakMJ.(1998) Clinical epidemiology of cardiovascular

disease in chronic renal disease. Am J Kidney Dis; 32 (5 Suppl 3): S112–S119,

ISSN: 1523-6838.

6. Massry SG, Smogorzewski M. (1994) Mechanisms through which parathyroid

hormone mediates its deleterious effects on organ function in uremia. Semin

Nephrol, 14(3):219-31, ISSN 1558-4488.

7. Amgen Inc. Sensipar® [package insert] (2004) Thousand Oaks, CA: Amgen Inc.

8. Deborah N., Scott J.,David M.(2015) Nanoparticulate cinacalcet compositions, US

Patent 20110287065A.

9. July 02, 2018, Lercanidipine, https://www.drugbank.ca/drugs/DB00528 [online]

[Accessed 27 July 2018].

10. May 05, 2018, Metabocard for Cinacalcet (HMDB0015147) [online] http:/ /www.

hmdb. ca/ metabolites/ HMDB0015147, [Accessed 27 July, 2018].

CHAPTER 6

List of Publication

LIST OF RESEARCH PAPERS PUBLISHED IN JOURNALS

Ghori VL, Patel DM, Omri A, 2017, Formulation and Optimization of Self Nano Emulsifying Drug Delivery System of Lercanidipine Hydrochloride Using Response Surface Methodology, International Journal Of Pharmaceutical Research And Bio-Science, 6(4): 162-176, ISSN : 2277-8713.

Ghori VL, Patel DM, Omri A, 2018, Enhancement of Solubility and in vitro Drug Release Study for Lercanidipine Hydrochloride Loaded Liquid Self Nano Emulsifying Drug Delivery System using Factorial Design, International Journal of Pharmaceutical Research, (1):112-119, ISSN : 0975-2366.

Chapter 6 List of Publication

168


169


170

Paper Presentation of Research work in Seminar/conference

A. PAPER (POSTER) PRESENTED

1. Development and Characterization of Self Nanoemulsifying Drug Delivery

Systems (SNEDDS) of Lercanidipine HCL at Nootan Pharmacy College, Visnagar,

Gujarat, India Sponsored by SERB-DST and APTI supported National Conference

on 9-10th March 2017.

2. Formulation and optimization of Self Nano Drug Delivery System of Lercanidipine

HCL using 32 full factorial design in Pharmavision 2017 at Ahmedabad, Gujarat,

India on 9-10th September 2017. Earned 2nd prize for presentation.

3. “Development and Characterization of Self Nanoemulsifying Drug Delivery

System (SNEDDS) of Cinacalcet HCL” in international conference on pharmacy

practice “Towards The Excellence In Pharmacy Practice” on 26th -27th December

2018 at KBIPER, Gandhinagar

B. PAPER (ORAL) PRESENTED

1. Design And Development of Self Nanoemulsifying Drug Delivery System of BCS

Class II Drug By Implementation of QbD Principles in GUJCOST Sponsored Short

Term Training Program on QbD: Academic and Industrial Perspective on 13th Aug

to 18th Aug 2018 at Department of Pharmaceutical Sciences, Saurashtra

University, Rajkot - 360 005, Gujarat, India.


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