Predictive Modeling of Pharmaceutical Unit Operations

1st Edition - April 9, 2014
Editors: Preetanshu Pandey, Rahul Bharadwaj
Language: English
Hardback ISBN:
9 7 8 - 0 - 0 8 - 1 0 0 1 5 4 - 7
eBook ISBN:
9 7 8 - 0 - 0 8 - 1 0 0 1 8 0 - 6

The use of modeling and simulation tools is rapidly gaining prominence in the pharmaceutical industry covering a wide range of applications. This book focuses on modeling and si… Read more

Predictive Modeling of Pharmaceutical Unit Operations

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The use of modeling and simulation tools is rapidly gaining prominence in the pharmaceutical industry covering a wide range of applications. This book focuses on modeling and simulation tools as they pertain to drug product manufacturing processes, although similar principles and tools may apply to many other areas. Modeling tools can improve fundamental process understanding and provide valuable insights into the manufacturing processes, which can result in significant process improvements and cost savings. With FDA mandating the use of Quality
by Design (QbD) principles during manufacturing, reliable modeling techniques can help to alleviate the costs associated with such efforts, and be used to create in silico formulation and process design space. This book is geared toward detailing modeling techniques that are utilized for the various unit operations during drug product manufacturing. By way of examples that include case studies, various modeling principles are explained for the nonexpert end users. A discussion on the role of modeling in quality risk management for manufacturing and application of modeling for continuous manufacturing and biologics is also included.

List of contributors
Predictive modeling of pharmaceutical unit operations
Preface
1. Modeling of drug product manufacturing processes in the pharmaceutical industry
- Abstract
- 1.1 Introduction
- 1.2 Modeling techniques
- 1.3 Process modeling in drug product manufacturing
- References
2. Quality risk management for pharmaceutical manufacturing: The role of process modeling and simulations
- Abstract
- 2.1 Introduction
- 2.2 Quality risk management in pharmaceutical manufacturing
- 2.3 Scientific considerations in model development for quality risk management
- 2.4 Using process models to support quality risk management for emerging technologies
- 2.5 Conclusions
- References
3. Powder flow and blending
- Abstract
- 3.1 Critical role of the powder blending step in pharmaceutical manufacturing
- 3.2 Common challenges in powder blending
- 3.3 Granular mixing fundamentals
- 3.4 Assessment, measurement, and characterization
- 3.5 Modeling techniques for powder mixing
- 3.6 Summary and outlook
- Acknowledgements
- References
4. Dry granulation process modeling
- Abstract
- 4.1 Introduction
- 4.2 Challenges in dry granulation modeling and recent progress
- 4.3 Modeling tools
- 4.4 Experimental validation
- 4.5 Case studies of model application
- 4.6 Conclusions
- References
5. Mechanistic modeling of high-shear and twin screw mixer granulation processes
- Abstract
- 5.1 Introduction
- 5.2 Modeling techniques for high-shear wet granulation processes
- 5.3 Numerical techniques
- 5.4 Application of high-shear wet granulation models
- 5.5 General discussion and conclusions
- References
6. Fluid bed granulation and drying
- Abstract
- 6.1 Introduction
- 6.2 Granulation modeling
- 6.3 Drying modeling
- 6.4 FluidBeG: an integrated granulation and drying model
- 6.5 Future developments
- References
7. Modeling of milling processes via DEM, PBM, and microhydrodynamics
- Abstract
- 7.1 Introduction
- 7.2 Microhydrodynamic modeling of wet media milling
- 7.3 DEM for modeling of dry milling
- 7.4 PBM for process-scale modeling of milling
- 7.5 Multiscale modeling approaches for dry media (ball) milling
- 7.6 Case study: application of the microhydrodynamic model to preparation of drug nanosuspensions
- 7.7 Case study: application of the multiscale DEM–PBM approach to rolling ball milling
- 7.8 Concluding remarks
- Acknowledgments
- References
8. Modeling of powder compaction with the drucker–prager cap model
- Abstract
- 8.1 Introduction
- 8.2 The particulate nature of compacts and the modeling of their behavior
- 8.3 Constitutive models
- 8.4 Parameter identification
- 8.5 Finite element modeling
- 8.6 Case studies
- References
9. Modeling approaches to multilayer tableting
- Abstract
- 9.1 Introduction
- 9.2 Models
- 9.3 Conclusions
- References
10. Computational modeling of pharmaceutical die filling processes
- Abstract
- 10.1 Introduction
- 10.2 Background of pharmaceutical die filling
- 10.3 Computational setup of die filling
- 10.4 Computational analysis of die filling
- 10.5 Summary
- References
11. Modeling tablet film-coating processes
- Abstract
- 11.1 Introduction
- 11.2 Thermodynamic modeling
- 11.3 Spray atomization modeling
- 11.4 Tablet mixing modeling
- 11.5 Prospects for an integrated film-coating process model
- References
12. Modeling in pharmaceutical packaging
- Abstract
- 12.1 Introduction
- 12.2 Container WVTR of pharmaceutical packaging
- 12.3 Moisture sorption isotherm of pharmaceutical products
- 12.4 Moisture uptake modeling of packaged pharmaceutical products
- 12.5 Case studies
- 12.6 Summary
- Acknowledgments
- References
13. Continuous secondary process selection and the modeling of batch and continuous wet granulation
- Abstract
- 13.1 Paradigm shift to continuous processing for solid dose manufacture
- 13.2 Selection of the appropriate process based on powder flow and compressibility
- 13.3 Introduction to modeling batch high shear granulation
- 13.4 Modeling batch high shear granulation by sampling during granulation
- 13.5 Impact of raw material particle size and surface area changes on high shear granulation modeling
- 13.6 Models describing scale-up and equipment transfer of batch high shear granulation
- 13.7 Evaluating the significance of work, X_sat and the amount of water added within scale
- 13.8 A single equation to model granulation—SaWW model
- 13.9 Modeling twin screw continuous wet granulation
- 13.10 The impact of feeder variability on twin screw wet granulation
- 13.11 Conclusion
- References
- Appendix A DoE and Repeat Run Data Tables
14. Process modeling in the biopharmaceutical industry
- Abstract
- 14.1 Introduction
- 14.2 Theoretical foundations
- 14.3 Bioreactor operation and modeling
- 14.4 Liquid chromatography
- 14.5 Lyophilization (freeze drying)
- 14.6 Conclusions
- References
Index

Preetanshu Pandey

Preetanshu Pandey obtained his Bachelor’s chemical engineering degree from Indian Institute of Technology, Kanpur, India. He holds a M.S. and Ph.D. degree in chemical engineering from West Virginia University. He is currently working as a Principal Scientist at the Drug Product Science and Technology department at Bristol-Myers Squibb. At BMS, he is primarily involved with developing oral solid dosage drug products. Prior to joining BMS, he worked at Schering-Plough/Merck for over 3 years on drug product development of inhalation products. He is actively involved with AAPS and AICHE organizations and has chaired symposiums and open forums in previous annual meetings. He serves as a reviewer for multiple journals and has authored over 40 peer-reviewed publications, 3 patent applications, and 3 invited book chapters.

Affiliations and expertise

Principal Scientist in the Dept. of Drug Product Science and Technology at Bristol-Myers Squibb, New Brunswick, NJ, USA .

Rahul Bharadwaj

Dr. Rahul Bharadwaj is the Vice-President of Engineering and Business Development at Rocky DEM, Inc. Dr. Bharadwaj has over a decade of experience in the development, validation and application of computational tools such as Discrete Element Modeling (DEM), Computational Fluid Dynamics and Finite Element Analyses for industries such as pharmaceutical, chemical, agriculture, mining, oil & gas, etc. He received his M.S. in Mechanical Engineering from the University of Kentucky (2003) and a Ph.D. in Mechanical Engineering from Purdue University (2006). He has since then held positions as senior scientist in Pfizer R&D and also as a consulting engineer at Jenike and Johanson Inc. He is also an active member of American Institute of Chemical Engineers (AIChE), American Association of Pharmaceutical Scientists (AAPS), and is the founder and past-chair of its Process Modeling and Simulation Focus Group

Affiliations and expertise

Vice-President of Engineering and Business Development at Rocky DEM, Inc.

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