Post on 14-Aug-2015
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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