a doe/qbd optimization model for "tablet compression" process using circumscribed central...
TRANSCRIPT
FOR TABLET DEVELOPMENT AS PER QbD
OPTIMIZATION OF CPPs OF TABLET COMPRESSION PROCESS
FACTORIAL MIXTURE
BOX BEHNKEN
RESPONSE SURFACE
CIRCUMSCRIBED CENTRAL COMPOSITE
© Created & Copyrighted by Shivang Chaudhary
SHIVANG CHAUDHARY
© Copyrighted by Shivang Chaudhary
Quality Risk Manager & iP 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 [email protected]
https://in.linkedin.com/in/shivangchaudhary
facebook.com/QbD.PAT.Pharmaceutical.Development
CA
SE
STU
DY
A DoE/QbD CASE STUDY FOR
HOW TO VERIFY DESIGN SPACE?
HOW TO CREATE OVERLAY PLOT?
HOW TO INTERPRET MODEL GRAPHS?
HOW TO DIAGNOSE RESIDUALS?
HOW TO SELECT MODEL?
HOW TO SELECT EFFECT TERMS?
LOWER HARDNESS INADEQUATE DISINTEGRATION
QUALITY COMPROMISED EFFICACY COMPROMISED
WEIGHT VARIATION
SAFETY COMPROMISED
HIGH FRIABILITY INADEQUATE DISSOLUTION CONTENT NONUNIFORMITY
RISKS
FACTORIAL MIXTURE
BOX BEHNKEN
RESPONSE SURFACE
CIRCUMSCRIBED CENTRAL COMPOSITE
COMPRESSION FORCE
TURRET SPEED B
A
HOW TO SELECT DESIGN?
HOW TO IDENTIFY
RISK FACTORS?
CA
SE
STU
DY
© Created & Copyrighted by Shivang Chaudhary
OPTIMIZATION OF CRITICAL PROCESSING PARAMETERS OF TABLET COMPRESSION PROCESS
FACTORS
Factors (Variables) Levels of Factors studied -α -1 0 +1 +α
A COMPRESSION FORCE (kN) 1.17 2.00 4.00 6.00 6.83 B TURRET SPEED (RPM) 3.79 10.00 25.00 40.00 46.21
NO. OF FACTORS
NO. OF LEVELS
EXPERIMENTAL DESIGN SELECTED
TOTAL NO OF EXPERIMENTAL RUNS (TRIALS)
2
5
circumscribed CENTRAL COMPOSITE DESIGN (cCCD)
2fp + 2sp + cp = (22 )+ (2*2) + (5) = 4+4+5 = 13
To Optimize Critical Processing Parameters of Tablet Compression Process OBJECTIVE
FACTORIAL MIXTURE
BOX BEHNKEN
RESPONSE SURFACE
OPTIMIZATION OF CRITICAL PROCESSING PARAMETERS OF TABLET COMPRESSION PROCESS
A
B
CIRCUMSCRIBED CENTRAL COMPOSITE
© Created & Copyrighted by Shivang Chaudhary
HOW TO IDENTIFY FACTORS?
HOW TO VERIFY DESIGN SPACE?
HOW TO CREATE OVERLAY PLOT?
HOW TO INTERPRET MODEL GRAPHS?
HOW TO DIAGNOSE RESIDUALS?
HOW TO SELECT MODEL?
HOW TO SELECT EFFECT TERMS?
HOW TO SELECT
DESIGN?
OBJECTIVE of the experiment & NUMBERS of the factors involved were the primary two most important factors required to be considered during selection of any design for experimentation.
• In Tablet Compression, 2 Processing Parameters were critical & required to be optimized
• Moreover, the region of operability must be greater than region of interest to achieve the maximum rate of productivity to get maximum daily output at commercial manufacturing scale
• Thus, 5 Level cCCD is a time & cost effective best alternative to 3 Level FFD for optimization.
• However in 5 level cCCD, region of operability was greater than region of interest to accommodate additional star points which are at extreme levels (highest & lowest) of both factors.
“Highest”
“High”
“Medium”
“Low”
“Lowest”
CA
SE
STU
DY
TUR
RE
T SP
EE
D
COMPRESSON FORCE
HOW TO IDENTIFY FACTORS?
HOW TO SELECT DESIGN?
CPPs CQAs
FACTORIAL MIXTURE
BOX BEHNKEN
RESPONSE SURFACE
OPTIMIZATION OF CRITICAL PROCESSING PARAMETERS OF TABLET COMPRESSION PROCESS
CIRCUMSCRIBED CENTRAL COMPOSITE
© Created & Copyrighted by Shivang Chaudhary
HOW TO VERIFY DESIGN SPACE?
HOW TO CREATE OVERLAY PLOT?
HOW TO INTERPRET MODEL GRAPHS?
HOW TO DIAGNOSE RESIDUALS?
HOW TO SELECT MODEL?
HOW TO DESIGN
EXPERIMENTS?
Qualitative & Quantitative Formulation & High Shear Wet Granulation processing parameters were kept constant for all 13 experimental runs, i.e. Starting from Co-Sifting, Dry Mixing, Binder addition &
Wet Granulation, Drying, Sizing up to Blending & Lubrication in Bin Blender, & it was finally grouped into 13 equal parts according to experimental runs of cCCD
at different combination of Compression Force & Turret Speed .
CA
SE
STU
DY
HOW TO IDENTIFY FACTORS? HOW TO SELECT
DESIGN? HOW TO SELECT
EFFECT TERMS?
FACTORIAL MIXTURE
BOX BEHNKEN
RESPONSE SURFACE
OPTIMIZATION OF CRITICAL PROCESSING PARAMETERS OF TABLET COMPRESSION PROCESS
CIRCUMSCRIBED CENTRAL COMPOSITE
© Created & Copyrighted by Shivang Chaudhary
HOW TO VERIFY DESIGN SPACE?
HOW TO CREATE OVERLAY PLOT?
HOW TO INTERPRET MODEL GRAPHS?
HOW TO DIAGNOSE RESIDUALS?
HOW TO SELECT
MODEL?
During Selection of order of polynomial: MODEL [A mathematical relationship between factors & response assisting in calculations & predictions) for Analysis of Response; ANOVA was carried out thoroughly for
testing of SIGNIFICANCE of every possible MODEL (p<0.05) with insignificant LACK OF FIT (p>0.1) & response surface to confirm expected shape of response behavior
P-Value < 0.05 (Significant) P-Value > 0.10 (Insignificant) Lack of Fit is the variation of the data around the fitted model. If the model does not fit the actual response behavior well, this will be significant. Thus those models could not be used as a predictor of the response.
P-Value < 0.05 (Significant) P-Value > 0.10 (Insignificant) Sequential model sum of square provides a sequential comparison of models showing the statistical significance of
ADDING new model terms to those terms already in the model. Thus, the highest degree quadratic model was selected having p-value (Prob > F) that is lower than chosen level of significance (p = 0.05)
Sequential MODEL Sum of Square Tables
LACK of Fit Tests
Response 1: Friability Response 2: Dissolution Response 3: Content Uniformity
Response 1: Friability Response 2: Dissolution Response 3: Content Uniformity
CA
SE
STU
DY
FACTORIAL MIXTURE
BOX BEHNKEN
RESPONSE SURFACE
OPTIMIZATION OF CRITICAL PROCESSING PARAMETERS OF TABLET COMPRESSION PROCESS
CIRCUMSCRIBED CENTRAL COMPOSITE
© Created & Copyrighted by Shivang Chaudhary
HOW TO IDENTIFY FACTORS? HOW TO SELECT
DESIGN? HOW TO SELECT
EFFECT TERMS? HOW TO VERIFY
DESIGN SPACE? HOW TO CREATE
OVERLAY PLOT? HOW TO INTERPRET
MODEL GRAPHS? HOW TO SELECT
MODEL? HOW TO DIAGNOSE
MODEL?
Numerical Analysis of Model Variance was carried out to confirm or validate that the MODEL ASSUMPTIONS for the response behavior were met with actual response behavior or not, via testing of significance of each MODEL TERMs
with F >>1 & p<0.05 (less than 5% probability that a “Model F Value” this large could occur due to noise), insignificant LACK OF FIT (p>0.10), adequate PRECISION > 4, R2 Adj & R2 Pred in good agreement <0.2d, with well behaved RESIDUALS analyzed
by diagnostic plots as GRAPHICAL INDICATORS.
Residual (Experimental Error) Noise = (Observed Responses) Actual Data– (Predicted Responses) Model Value During RESIDUAL ANALYSIS, model predicted values were found higher than actual & lower than actual with equal probability in Actual
Vs Predicted Plot. In addition the level of error were independent of when the observation occurred in RESIDUALS Vs RUN PLOT, the size of the
observation being predicted in Residuals Vs Predicted Plot or even the factor setting involved in making the prediction in Residual Vs Factor Plot
PREDICTION EFFECT EQUATION ON INDIVIDUAL RESPONSE BY QUADRATIC MODEL
FRIABILITY =+0.15 -0.066A +0.026B
-7.500E-003AB +0.028A2
+0.021B2
DRUG DISSOLVED IN 30 MIN =+97.20 -8.37A +0.16B -1.75AB -5.73A2
-1.48B2
CONTENT UNIFORMITY =+4.15 -0.088A +1.45B
-0.08AB +0.13A2
+0.73B2
Response 1: Friability Response 2: Dissolution Response 3: Content Uniformity
CA
SE
STU
DY
FACTORIAL MIXTURE
BOX BEHNKEN
RESPONSE SURFACE
OPTIMIZATION OF CRITICAL PROCESSING PARAMETERS OF TABLET COMPRESSION PROCESS
CIRCUMSCRIBED CENTRAL COMPOSITE
© Created & Copyrighted by Shivang Chaudhary
HOW TO IDENTIFY FACTORS? HOW TO SELECT
DESIGN? HOW TO SELECT
EFFECT TERMS? HOW TO VERIFY
DESIGN SPACE? HOW TO CREATE
OVERLAY PLOT? HOW TO SELECT
MODEL? HOW TO DIAGNOSE
RESIDUALS? HOW TO INTERPRET
MODEL GRAPHS?
Model Graphs gave a clear picture of how the response will behave at different levels of factors at a time in 2D & 3D
Response 1: Friability Response 2: Dissolution Response 3: Content Uniformity
Interaction Plots
Contour Plots
Response Surface
CA
SE
STU
DY
Factors (Variables) Knowledge Space Design Space Control Space A Compression Force (kn) 2.0-6.0 3.0-5.0 3.5-4.5 B Turret Speed (RPM) 10-40 10-30 15-25
Responses (Effects) Goal for Individual Responses Y2 Friability To achieve tablet friability NMT 0.2%w/w Y4 Dissolution Drug release should NLT 90% in 30 minutes Y6 Content uniformity Acceptance Value should in CU test should NMT 5.0
FACTORIAL MIXTURE
BOX BEHNKEN
RESPONSE SURFACE
OPTIMIZATION OF CRITICAL PROCESSING PARAMETERS OF TABLET COMPRESSION PROCESS
CIRCUMSCRIBED CENTRAL COMPOSITE
© Created & Copyrighted by Shivang Chaudhary
HOW TO IDENTIFY FACTORS? HOW TO SELECT
DESIGN? HOW TO SELECT
EFFECT TERMS? HOW TO VERIFY
DESIGN SPACE? HOW TO SELECT
MODEL? HOW TO DIAGNOSE
RESIDUALS? HOW TO INTERPRET
MODEL GRAPHS? HOW TO DEVELOP
DESIGN SPACE?
CA
SE
STU
DY
By Overlaying contour maps from each responses on top of each other, RSM was used to find out the IDEAL “WINDOW” of Operability-Design Space per proven acceptable ranges & Edges of Failure with respect to individual goals
FACTORIAL MIXTURE
BOX BEHNKEN
RESPONSE SURFACE
OPTIMIZATION OF CRITICAL PROCESSING PARAMETERS OF TABLET COMPRESSION PROCESS
CIRCUMSCRIBED CENTRAL COMPOSITE
© Created & Copyrighted by Shivang Chaudhary
HOW TO IDENTIFY FACTORS? HOW TO SELECT
DESIGN? HOW TO SELECT
EFFECT TERMS? HOW TO SELECT
MODEL? HOW TO DIAGNOSE
RESIDUALS? HOW TO INTERPRET
MODEL GRAPHS? HOW TO CREATE
OVERLAY PLOT? HOW TO VERIFY
DESIGN SPACE?
After completion of all experiments according to DoE, Verification was required to CONFIRM DESIGN SPACE developed by selected DESIGN MODEL, which should be rugged & robust to normal variation within a SWEET SPOT in OVERLAY
PLOT, where all the specifications for the individual responses (CQAs) were met to the predefined targets (QTPP)
2.0-6.0
3.0-5.0
3.5-4.5
10.0-40.0
10.0-30.0
15.0-25.0
The OBSERVED EXPERIMENTAL RESULTS of 3 additional confirmatory runs across the entire design space were compared with PREDICTED RESULTS from Model equation by CORRELATION COEFFICIENTs. In the case of all
3 responses, R2 were found to be more than 0.900, confirming right selection of DESIGN MODEL.
COMPRESSION FORCE (kN) TURRET SPEED (RPM)
KNOWLEDEGE SPACE
DESIGN SPACE
CONTROL SPACE
Known Ranges of OPERABILITY before Designing
Optimized Ranges of FEASIBILITY after Development
Planned Ranges of CONTROLLING during Commercialization
CA
SE
STU
DY
THANK YOU SO MUCH FROM
DESIGNING 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 [email protected]
https://in.linkedin.com/in/shivangchaudhary
facebook.com/QbD.PAT.Pharmaceutical.Development