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NIPTE-FDA Collaborative Case Study On Model-based Design Space Development Across Scales & with Stability Considerations Design Space Integration 1.

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Presentation on theme: "NIPTE-FDA Collaborative Case Study On Model-based Design Space Development Across Scales & with Stability Considerations Design Space Integration 1."— Presentation transcript:

1 NIPTE-FDA Collaborative Case Study On Model-based Design Space Development Across Scales & with Stability Considerations Design Space Integration 1

2 2 Considered –Degradation NMT 0.4 mole % lactam –Hardness NLT 3 kP –Weight variation 90 % - 110% % RSD NMT 6% –Dissolution NLT 40% @ 5 min –Disintegration NMT 10 min

3 Shelf Life Design Space 3 Probability of lactam < 0.4 mole % after 2 years @ 22°C Low Moisture max p=0.7 Medium Moisture max p=0.71

4 Tabletting Design Space 4 disintegration time =-4.54 + 0.86 * hydrophobicity + 0.06 * hardness HydrophobicityHardness % dissolved @5 min =78.1 – 0.1 * hydrophobicity – 3.0 * hardness

5 Tabletting Design Space 5 Disintegration DissolutionHydrophobicity = -26 + 36 * Blend Time => # of rotations are limited

6 Dissolution Data (provided by FDA) 6

7 Dissolution 7 % dissolved @5 min = 63.3 – 2.4 * disintegration time Disintegration is often limiting step for highly soluble drugs

8 Single Unit Op 8

9 Unit Op Interactions 9

10 Design Space 10 Single Unit Op

11 Unit Op Interactions 11

12 Design Space Integration 12 Tablet weight variation = f (spray rate, impeller speed) –within USP limit In-process lactam is well below 0.4 mole % –a meaningful limit may be established only after accelerated stability studies

13 Model Building 13 In-process lactam ~ max. product temperature Lab scale

14 Model Validation (Lab Scale) 14

15 Model Prediction 15 EEFEMT 0.1750.5 0.1751 0.451 0.5 No need to run full factorial!!! Single experiment to calibrate model parameters Second experiment to verify model predictions

16 Model Prediction (Intermediate Scale) 16

17 Summary 17 Design space for shelf life stability determined Unit op interactions determined Design space for each unit op can be determined by backward propagation Models help to predict process behavior at larger scale => save on experimental effort


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