Comprehensive Quality by Design for Pharmaceutical Product Development and Manufacture

This book is a structured approach to designing a product and its associated manufacturing process. It guides pharmaceutical engineers and scientists involved in product and process development how to utilize QbD practices and applications effectively while complying with government regulations. Material includes discussion of how to utilize design space, models, process control methodology, and cumulative process knowledge to seek improvements in manufacturing, while maintaining and enhancing product performance. Edited by the three researchers renowned in this field, this invaluable resource is an essential tool for all pharameutical professionals.

GINTARAS.V. REKLAITIS, PhD, is Professor of Chemical Engineering and Industrial & Physical Pharmacy at Purdue University, member of the U.S. National Academy of Engineering, and the Deputy Director of the NSF Engineering Research Center on Structured Organic Particulate Systems.

CHRISTINE SEYMOUR, PhD, is Director in Global Regulatory Chemistry, Manufacturing & Controls at Pfizer Inc, the 2018 President of AIChE, and a Director in AIChE's Society for Biological Engineering.

SALVADOR GARCÍA-MUNOZ, PhD, is a Senior Engineering Advisor in Process Modeling and Optimization in Small Molecule Development at Eli Lilly and Company.

List of Contributors xiii

Preface xix

1 Introduction 1
Christine Seymour and Gintaras V. Reklaitis

1.1 Quality by Design Overview 1

1.2 Pharmaceutical Industry 2

1.3 Quality by Design Details 3

1.4 Chapter Summaries 4

References 7

2 An Overview of the Role of Mathematical Models in Implementation of Quality by Design Paradigm for Drug Development and Manufacture 9
Sharmista Chatterjee, Christine M. V. Moore, and Moheb M. Nasr

2.1 Introduction 9

2.2 Overview of Models 9

2.3 Role of Models in QbD 12

2.4 General Scientific Considerations for Model Development 20

2.5 Scientific Considerations for Maintenance of Models 22

2.6 Conclusion 23

References 23

3 Role of Automatic Process Control in Quality by Design 25
Mo Jiang, Nicholas C. S. Kee, Xing Yi Woo, Li May Goh, Joshua D. Tice, Lifang Zhou, Reginald B. H. Tan, Charles F. Zukoski, Mitsuko Fujiwara, Zoltan K. Nagy, Paul J. A. Kenis, and Richard D. Braatz

3.1 Introduction 25

3.2 Design of Robust Control Strategies 31

3.3 Some Example Applications of Automatic Feedback Control 35

3.4 The Role of Kinetics Modeling 40

3.5 Ideas for a Deeper QbD Approach 42

3.6 Summary 44

Acknowledgments 46

References 47

4 Predictive Distributions for Constructing the ICH Q8 Design Space 55
John J. Peterson, Mohammad Yahyah, Kevin Lief, and Neil Hodnett

4.1 Introduction 55

4.2 Overlapping Means Approach 56

4.3 Predictive Distribution Approach 59

4.4 Examples 61

4.5 Summary and Discussion 68

Acknowledgments 69

References 69

5 Design of Novel Integrated Pharmaceutical Processes: A Model�]Based Approach 71
Alicia Román�]Martínez, John M. Woodley, and Rafiqul Gani

5.1 Introduction 71

5.2 Problem Description 73

5.3 Methodology 76

5.4 Application: Case Study 80

5.5 Conclusions 91

References 91

6 Methods and Tools for Design Space Identification in Pharmaceutical Development 95
Fani Boukouvala, Fernando J. Muzzio, and Marianthi G. Ierapetritou

6.1 Introduction 95

6.2 Design Space: A Multidisciplinary Concept 98

6.3 Integration of Design Space and Control Strategy 102

6.4 Case Studies 102

6.5 Conclusions 119

Acknowledgment 120

References 120

7 Using Quality by Design Principles as a Guide for Designing a Process Control Strategy 125
Christopher L. Burcham, Mark LaPack, Joseph R. Martinelli, and Neil McCracken

7.1 Introduction 125

7.2 Chemical Sequence, Impurity Formation, and Control Strategy 130

7.3 Mass Transfer and Reaction Kinetics 140

7.4 Optimal Processing Conditions 165

7.5 Predicted Product Quality under Varied Processing Conditions 174

7.6 Conclusions 186

Acknowledgments 187

Notation 187

Acronyms 187

Symbols 187

Notes 189

References 189

8 A Strategy for Tablet Active Film Coating Formulation Development Using a Content Uniformity Model and Quality by Design Principles 193
Wei Chen, Jennifer Wang, Divyakant Desai, Shih�]Ying Chang, San Kiang, and Olav Lyngberg

8.1 Introduction 193

8.2 Content Uniformity Model Development 197

8.3 RSD Model Validation and Sensitivity Analysis for Model Parameters 212

8.4 Model�]Based Design Space Establishment for Tablet Active Film Coating 219

8.5 Summary 229

Notations 230

References 230

9 Quality by Design: Process Trajectory Development for a Dynamic Pharmaceutical Coprecipitation Process Based on an Integrated Real�]Time Process Monitoring Strategy 235
Huiquan Wu and Mansoor A. Khan

9.1 Introduction 235

9.2 Experimental 237

9.3 Data Analysis Methods 239

9.4 Results and Discussion 240

9.5 Challenges and Opportunities for PCA�]Based Data Analysis and Modeling in Pharmaceutical PAT and QbD
Development 250

9.6 Conclusions 252

Acknowledgments 252

References 253

10 Application of Advanced Simulation Tools for Establishing Process Design Spaces Within the Quality by Design Framework 257
Siegfried Adam, Daniele Suzzi, Gregor Toschkoff, and Johannes G. Khinast

10.1 Introduction 257

10.2 Computer Simulation�]Based Process Characterization of a Pharmaceutical Blending Process 261

10.3 Characterization of a Tablet Coating Process via CFD Simulations 276

10.4 Overall Conclusions 294

References 295

11 Design Space Definition: A Case Study—Small Molecule Lyophilized Parenteral 301
Linas Mockus, David LeBlond, Gintaras V. Reklaitis, Prabir K. Basu, Tim Paul, Nathan Pease, Steven L. Nail, and Mansoor A. Khan

11.1 Introduction 301

11.2 Case Study: Bayesian Treatment of Design Space for a Lyophilized Small Molecule Parenteral 302

11.3 Results 307

11.4 Conclusions 311

Appendix 11.A Implementation Using WinBUGS and R 311

Shelf Life 315

Notation 316

Acknowledgments 317

References 317

12 Enhanced Process Design and Control of a Multiple�]Input Multiple�]Output Granulation Process 319
Rohit Ramachandran

12.1 Introduction and Objectives 319

12.2 Population Balance Model 320

12.3 Simulation and Controllability Studies 323

12.4 Identification of Existing “Optimal” Control�]Loop Pairings 327

12.5 Novel Process Design 330

12.6 Conclusions 335

References 336

13 A Perspective on the Implementation of QbD on Manufacturing through Control System: The Fluidized Bed Dryer Control with MPC and NIR Spectroscopy Case 339
Leonel Quiñones, Luis Obregón, and Carlos Velázquez

13.1 Introduction 339

13.2 Theory 340

13.3 Materials and Methods 344

13.4 Results and Discussion 348

13.5 Continuous Fluidized Bed Drying 355

13.6 Control Limitations 356

13.7 Conclusions 357

Acknowledgment 357

References 357

14 Knowledge Management in Support of QbD 361
G. Joglekar, Gintaras V. Reklaitis, A. Giridhar, and Linas Mockus

14.1 Introduction 361

14.2 Knowledge Hierarchy 363

14.3 Review of Existing Software 364

14.4 Workflow�]Based Framework 365

14.5 Drug Substance Case Study 368

14.6 Design Space 374

14.7 Technical Challenges 382

14.8 Conclusions 384

References 385

Index 387