OPTIMIZATION OF CRITICAL FACTORS

FOR INJECTION/ EYE/EAR/ NASAL DROPS DEVELOPMENT AS PER QbD

OPTIMIZATION OF PRESERVATIVE SYSTEM FOR IN USE STABILITY OF MULTIDOSE STERILES

INADEQUATE ANTIMICROBIAL CONC. INADEQUATE ANTIOXIDANT CONC

MICROBIAL LOAD IN-USE OXIDATION IMPURITIES

3 LEVEL FACTORIAL

PLACKETTE BURMAN

MIXTURE RESPONSE SURFACE FACTORIAL

2 LEVEL FULL FACTORIAL WITH CP

EVALUATION OF CRITICAL FACTORS

ANALYSIS OF RESPONSE

DESIGNING OF EXPERIMMENTS

IDENTIFICATION OF FACTORS

ANTIMICROBIAL A

B ANTIOXIDANT

C BUFFERING AGENT

RISKS

SAFETY COMPROMISED

CA

SE

STU

DY

7

© Created & Copyrighted by Shivang Chaudhary

SHIVANG CHAUDHARY Created & Copyrighted by:

Quality Risk Manager & Intellectual Property Sentinel- CIIE, IIM Ahmedabad, INDIA MS Pharm (Pharmaceutics)-NIPER, PGD (Patents Law)-NALSAR

shivaniper@gmail.com

Factors (Variables) Levels of Factors studied -1 Center point (0) +1

A Antimicrobial (%W/W) 0.005 0.010 0.015 B Antioxidant (%W/W) 0.050 0.100 0.150 C Buffering Agent (%W/W) 0.800 1.400 2.000

NO. OF FACTORS

NO. OF LEVELS

EXPERIMENTAL DESIGN SELECTED

ADD. CENTER POINTS

TOTAL NO OF EXPERIMENTAL RUNS (NO OF TRIALS)

3

2

23 FULL FACTORIAL DESIGN WITH ADD. CENTER POINTS

3

23 + 3 = 11

OBJECTIVE To Optimize Preservative System for In Use Stability Of Multi-dose Sterile Product (Injection, Eye/Ear Drops)

3 LEVEL FACTORIAL

PLACKETTE BURMAN

OPTIMIZATION OF PRESERVATIVE SYSTEM FOR IN USE STABIILITY OF MULTIDOSE STERILE PRODUCT

MIXTURE RESPONSE SURFACE FACTORIAL

A ANTIMICROBIAL

C

BU

FF

ER

ING

AG

EN

T

2 LEVEL FULL FACTORIAL WITH CP C

ASE

ST

UD

Y 7

OPTIMIZATION OF CRITICAL FACTORS

EVALUATION OF CRITICAL FACTORS

ANALYSIS OF RESPONSE

IDENTIFICATION OF FACTORS

DESIGNING OF EXPERIMMENTS

© Created & Copyrighted by Shivang Chaudhary

IDENTIFICATION OF FACTORS

CQAs CMAs

PREDICTION EFFECT EQUATION OF EACH FACTOR & THEIR INTERACTIONS ON INDIVIDUAL RESPONSE BY LINEAR MODEL

REDUCTION in Microbial Load after 14 days =+99.42 +0.35A +0.075B +0.15C -0.050AB -0.075AC +0.025ABC

OXIDIZED Impurities after 14 days=+0.46 -0.035A -0.18B -0.052C +7.50E-003AB +5.00E-003AC + 0.010BC -2.50E-003ABC

OPTIMIZATION OF PRESERVATIVE SYSTEM FOR IN USE STABIILITY OF MULTIDOSE STERILE PRODUCT

3 LEVEL FACTORIAL

PLACKETTE BURMAN

MIXTURE RESPONSE SURFACE FACTORIAL

2 LEVEL FULL FACTORIAL WITH CP C

ASE

ST

UD

Y 7

OPTIMIZATION OF CRITICAL FACTORS

EVALUATION OF CRITICAL FACTORS

DESIGNING OF EXPERIMMENTS

ANALYSIS OF RESPONSE

© Created & Copyrighted by Shivang Chaudhary

IDENTIFICATION OF FACTORS

DESIGNING OF EXPERIMMENTS

REDUCED LINEAR MODEL

REDUCTION in Microbial Load after 14 days =+99.42 +0.35A +0.075B +0.15C -0.050AB -0.075AC +0.00BC +0.025ABC

OXIDIZED Impurities after 14 days=+0.46 -0.035A -0.18B -0.052C

OPTIMIZATION OF PRESERVATIVE SYSTEM FOR IN USE STABIILITY OF MULTIDOSE STERILE PRODUCT

3 LEVEL FACTORIAL

PLACKETTE BURMAN

MIXTURE RESPONSE SURFACE FACTORIAL

2 LEVEL FULL FACTORIAL WITH CP C

ASE

ST

UD

Y 7

OPTIMIZATION OF CRITICAL FACTORS

ANALYSIS OF RESPONSE

SIGNIFICANT EFFECTS: MODEL TERMS

NEGLIGIBLE TERMS: ERROR ESTIMATES

TESTS FOR FITNESS OF LINEAR MODEL

ANALYSIS of CURVATURE= FCurvature = (y ̅factorial - y ̅center)2/ σ̂ [1/Nfactorial + 1/Ncenter]

by comparing the average of the factorials points to the average of the center points

SS (curvature) = SS (A2) + SS (B2) + SS (C2) is an aliased combination of all 3 quadratic terms, as

center point is the mid level of all 3 factors.

Insignificant Lack of Fit

Variation of the replicated design points about their means is about the same as the variation of the means

from the fitted line in the response surface.

So selected REDUCED LINEAR MODEL WITH 2FI & 3FI terms can be used as a predictor of the response.

No need for ADDITIONAL REPLICATED experiment to estimate pure error

Linear model should be augmented with ADDITIONAL more runs

for CENTER POINTS via design tools to estimate quadratic

terms individually i.e. A2, B2, C2.

Significant Curvature (peak/ valley in the middle

of response surface).

ANALYSIS of Lack of FIT= FLOF= MS Lack of Fit/ MS Pure Error =

[Difference between mean vs predicted value] / [Difference between replicates & their mean value]

SS residual = SS lack of fit +SS pure error SS lof= SS of the means about fitted model SSpe=SS of the replicates about their mean

p curvature =α < 0.01 at 95%CI

F curvature > 1

plof Value =α > 0.10 at 95%CI

Flof Value < 1

© Created & Copyrighted by Shivang Chaudhary

Responses (Effects) 5 Goals for Individual Responses Y1 Reduction in Microbial Load after 14D in use To achieve NLT 99.5% reduction in microbial load

Y2 %Oxidized Impurities after 14D in use To minimize the level of oxidized impurities NMT 0.5%

3 LEVEL FACTORIAL

PLACKETTE BURMAN

OPTIMIZATION OF PRESERVATIVE SYSTEM FOR IN USE STABIILITY OF MULTIDOSE STERILE PRODUCT

MIXTURE RESPONSE SURFACE FACTORIAL

2 LEVEL FULL FACTORIAL WITH CP C

ASE

ST

UD

Y 7

IDENTIFICATION OF FACTORS

DESIGNING OF EXPERIMMENTS

ANALYSIS OF RESPONSE EVALUATION OF

CRITICAL FACTORS OPTIMIZATION OF CRITICAL FACTORS

Factors (Variables) Knowledge Space Design Space Control Space A Antimicrobial (%W/W) 0.005-0.015 0.010-0.015 0.012-0.015 B Antioxidant (%W/W) 0.050-0.150 0.080-0.150 0.010-0.150 C Buffering Agent (%W/W) 0.800-2.000 0.800-2.000 0.800-2.000

© Created & Copyrighted by Shivang Chaudhary

THANK YOU SO MUCH FROM

DESIGN IS A JOURNEY OF DISCOVERY…

© Created & Copyrighted by Shivang Chaudhary

SHIVANG CHAUDHARY

© Copyrighted by Shivang Chaudhary

Quality Risk Manager & Intellectual Property Sentinel- CIIE, IIM Ahmedabad MS (Pharmaceutics)- National Institute of Pharmaceutical Education & Research (NIPER), INDIA

PGD (Patents Law)- National academy of Legal Studies & Research (NALSAR), INDIA

+91 -9904474045, +91-7567297579 shivaniper@gmail.com

https://in.linkedin.com/in/shivangchaudhary

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