Covers a widespread view of Quality by Design (QbD) encompassing the many stages involved in the development of a new drug product.

The book provides a broad view of Quality by Design (QbD) and shows how QbD concepts and analysis facilitate the development and manufacture of high quality products. QbD is seen as a framework for building process understanding, for implementing robust and effective manufacturing processes and provides the underpinnings for a science-based regulation of the pharmaceutical industry.

Edited by the three renowned researchers in the field,Comprehensive Quality by Design for Pharmaceutical Product Development and Manufacture guides pharmaceutical engineers and scientists involved in product and process development, as well as teachers, on how to utilize QbD practices and applications effectively while complying with government regulations. The material is divided into three main sections: the first six chapters address the role of key technologies, including process modeling, process analytical technology, automated process control and statistical methodology in supporting QbD and establishing the associated design space. The second section consisting of seven chapters present a range of thoroughly developed case studies in which the tools and methodologies discussed in the first section are used to support specific drug substance and drug-product QbD related developments. The last section discussed the needs for integrated tools and reviews the status of information technology tools available for systematic data and knowledge management to support QbD and related activities.

Highlights

Demonstrates Quality by Design (QbD) concepts through concrete detailed industrial case studies involving of the use of best practices and assessment of regulatory implicationsChapters are devoted to applications of QbD methodology in three main processing sectorsdrug substance process development, oral drug product manufacture, parenteral product processing, and solid-liquid processingReviews the spectrum of process model types and their relevance, the range of state-of-the-art real-time monitoring tools and chemometrics, and alternative automatic process control strategies and methods for both batch and continuous processesThe role of the design space is demonstrated through specific examples and the importance of understanding the risk management aspects of design space definition is highlighted

Comprehensive Quality by Design for Pharmaceutical Product Development and Manufacture is an ideal book for practitioners, researchers, and graduate students involved in the development, research, or studying of a new drug and its associated manufacturing process.

List of Contributors xiiiPreface xix1 Introduction 1Christine Seymour and Gintaras V. Reklaitis1.1 Quality by Design Overview 11.2 Pharmaceutical Industry 21.3 Quality by Design Details 31.4 Chapter Summaries 4References 72 An Overview of the Role of Mathematical Models in Implementation of Quality by Design Paradigm for Drug Development and Manufacture 9Sharmista Chatterjee, Christine M. V. Moore, and Moheb M. Nasr2.1 Introduction 92.2 Overview of Models 92.3 Role of Models in QbD 122.4 General Scientific Considerations for Model Development 202.5 Scientific Considerations for Maintenance of Models 222.6 Conclusion 23References 233 Role of Automatic Process Control in Quality by Design 25Mo 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. Braatz3.1 Introduction 253.2 Design of Robust Control Strategies 313.3 Some Example Applications of Automatic Feedback Control 353.4 The Role of Kinetics Modeling 403.5 Ideas for a Deeper QbD Approach 423.6 Summary 44Acknowledgments 46References 474 Predictive Distributions for Constructing the ICH Q8 Design Space 55John J. Peterson, Mohammad Yahyah, Kevin Lief, and Neil Hodnett4.1 Introduction 554.2 Overlapping Means Approach 564.3 Predictive Distribution Approach 594.4 Examples 614.5 Summary and Discussion 68Acknowledgments 69References 695 Design of Novel Integrated Pharmaceutical Processes: A Model?]Based Approach 71Alicia Román?]Martínez, John M. Woodley, and Rafiqul Gani5.1 Introduction 715.2 Problem Description 735.3 Methodology 765.4 Application: Case Study 805.5 Conclusions 91References 916 Methods and Tools for Design Space Identification in Pharmaceutical Development 95Fani Boukouvala, Fernando J. Muzzio, and Marianthi G. Ierapetritou6.1 Introduction 956.2 Design Space: A Multidisciplinary Concept 986.3 Integration of Design Space and Control Strategy 1026.4 Case Studies 1026.5 Conclusions 119Acknowledgment 120References 1207 Using Quality by Design Principles as a Guide for Designing a Process Control Strategy 125Christopher L. Burcham, Mark LaPack, Joseph R. Martinelli, and Neil McCracken7.1 Introduction 1257.2 Chemical Sequence, Impurity Formation, and Control Strategy 1307.3 Mass Transfer and Reaction Kinetics 1407.4 Optimal Processing Conditions 1657.5 Predicted Product Quality under Varied Processing Conditions 1747.6 Conclusions 186Acknowledgments 187Notation 187Acronyms 187Symbols 187Notes 189References 1898 A Strategy for Tablet Active Film Coating Formulation Development Using a Content Uniformity Model and Quality by Design Principles 193Wei Chen, Jennifer Wang, Divyakant Desai, Shih?]Ying Chang, San Kiang, and Olav Lyngberg8.1 Introduction 1938.2 Content Uniformity Model Development 1978.3 RSD Model Validation and Sensitivity Analysis for Model Parameters 2128.4 Model?]Based Design Space Establishment for Tablet Active Film Coating 2198.5 Summary 229Notations 230References 2309 Quality by Design: Process Trajectory Development for a Dynamic Pharmaceutical Coprecipitation Process Based on an Integrated Real?]Time Process Monitoring Strategy 235Huiquan Wu and Mansoor A. Khan9.1 Introduction 2359.2 Experimental 2379.3 Data Analysis Methods 2399.4 Results and Discussion 2409.5 Challenges and Opportunities for PCA?]Based Data Analysis and Modeling in Pharmaceutical PAT and QbDDevelopment 2509.6 Conclusions 252Acknowledgments 252References 25310 Application of Advanced Simulation Tools for Establishing Process Design Spaces Within the Quality by Design Framework 257Siegfried Adam, Daniele Suzzi, Gregor Toschkoff, and Johannes G. Khinast10.1 Introduction 25710.2 Computer Simulation?]Based Process Characterization of a Pharmaceutical Blending Process 26110.3 Characterization of a Tablet Coating Process via CFD Simulations 27610.4 Overall Conclusions 294References 29511 Design Space Definition: A Case StudySmall Molecule Lyophilized Parenteral 301Linas Mockus, David LeBlond, Gintaras V. Reklaitis, Prabir K. Basu, Tim Paul, Nathan Pease, Steven L. Nail, and Mansoor A. Khan11.1 Introduction 30111.2 Case Study: Bayesian Treatment of Design Space for a Lyophilized Small Molecule Parenteral 30211.3 Results 30711.4 Conclusions 311Appendix 11.A Implementation Using WinBUGS and R 311Shelf Life 315Notation 316Acknowledgments 317References 31712 Enhanced Process Design and Control of a Multiple?]Input Multiple?]Output Granulation Process 319Rohit Ramachandran12.1 Introduction and Objectives 31912.2 Population Balance Model 32012.3 Simulation and Controllability Studies 32312.4 Identification of Existing Optimal Control?]Loop Pairings 32712.5 Novel Process Design 33012.6 Conclusions 335References 33613 A Perspective on the Implementation of QbD on Manufacturing through Control System: The Fluidized Bed Dryer Control with MPC and NIR Spectroscopy Case 339Leonel Quiñones, Luis Obregón, and Carlos Velázquez13.1 Introduction 33913.2 Theory 34013.3 Materials and Methods 34413.4 Results and Discussion 34813.5 Continuous Fluidized Bed Drying 35513.6 Control Limitations 35613.7 Conclusions 357Acknowledgment 357References 35714 Knowledge Management in Support of QbD 361G. Joglekar, Gintaras V. Reklaitis, A. Giridhar, and Linas Mockus14.1 Introduction 36114.2 Knowledge Hierarchy 36314.3 Review of Existing Software 36414.4 Workflow?]Based Framework 36514.5 Drug Substance Case Study 36814.6 Design Space 37414.7 Technical Challenges 38214.8 Conclusions 384References 385Index 387