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Process Control, Intensification, and Digitalisation in Continuous Biomanufacturing. Edition No. 1

  • Book
  • 400 Pages
  • January 2022
  • John Wiley and Sons Ltd
  • ID: 5394343
Process Control, Intensification, and Digitalisation in Continuous Biomanufacturing

Explore new trends in continuous biomanufacturing with contributions from leading practitioners in the field

With the increasingly widespread acceptance and investment in the ??technology, the last decade has demonstrated the utility of continuous ??processing in the pharmaceutical industry.

In Process Control, Intensification, and Digitalisation in Continuous Biomanufacturing, distinguished biotechnologist Dr. Ganapathy Subramanian delivers a comprehensive exploration of the potential of the continuous processing of biological products and discussions of future directions in advancing continuous processing to meet new challenges and demands in the manufacture of therapeutic products.

A stand-alone follow-up to the editor’s Continuous Biomanufacturing: Innovative Technologies and Methods published in 2017, this new edited volume focuses on critical aspects of process intensification, process control, and the digital transformation of biopharmaceutical processes. In addition to topics like the use of multivariant data analysis, regulatory concerns, and automation processes, the book also includes: - Thorough introductions to capacitance sensors to control feeding strategies and the continuous production of viral vaccines - Comprehensive explorations of strategies for the continuous upstream processing of induced microbial systems - Practical discussions of preparative hydrophobic interaction chromatography and the design of modern protein-A-resins for continuous biomanufacturing - In-depth examinations of bioprocess intensification approaches and the benefits of single use for process intensification

Perfect for biotechnologists, bioengineers, pharmaceutical engineers, and process engineers, Process Control, Intensification, and Digitalisation in Continuous Biomanufacturing is also an indispensable resource for chemical engineers seeking a one-stop reference on continuous biomanufacturing.

Table of Contents

Preface xiii

Part I Continuous Biomanufacturing 1

1 Strategies for Continuous Processing in Microbial Systems 3
Julian Kopp, Christoph Slouka, Frank Delvigne, and Christoph Herwig

1.1 Introduction 3

1.1.1 Microbial Hosts and Their Applications in Biotechnology 3

1.1.2 Regulatory Demands for Their Applied Cultivation Mode 5

1.2 Overview of Applied Cultivation Methods in Industrial Biotechnology 6

1.2.1 Batch and Fed-Batch Cultivations 7

1.2.1.1 Conventional Approaches and Their Technical Limitations 7

1.2.1.2 Feeding and Control Strategies Using E. coli as a Model Organism 8

1.2.2 Introduction into Microbial Continuous Biomanufacturing (CBM) 9

1.2.2.1 General Considerations 9

1.2.2.2 Mass Balancing and the Macroscopic Effects in Chemostat Cultures 11

1.2.3 Microbial CBM vs. Mammalian CBM 13

1.2.3.1 Differences in Upstream of Microbial CBM Compared with Cell Culture 13

1.2.3.2 Downstream in Microbial CBM 14

1.3 Monitoring and Control Strategies to Enable CBM with Microbials 16

1.3.1 Subpopulation Monitoring and Possible PAT Tools Applicable for Microbial CBM 16

1.3.2 Modeling and Control Strategies to Enable CBM with Microbials 19

1.4 Chances and Drawbacks in Continuous Biomanufacturing with E. coli 21

1.4.1 Optimization of Plant Usage Using CBM with E. coli 21

1.4.2 Reasons Why CBM with E. coli Is Not State of the Art (Yet) 23

1.4.2.1 Formation of Subpopulation Following Genotypic Diversification 23

1.4.2.2 Formation of Subpopulation Following Phenotypic Diversification 25

1.4.2.3 Is Genomic Integration of the Target Protein an Enabler for CBM with E. coli? 26

1.4.3 Solutions to Overcome the Formation of Subpopulations and How to Realize CBM with E. coli in the Future 27

1.5 Conclusion and Outlook 29

References 30

2 Control of Continuous Manufacturing Processes for Production of Monoclonal Antibodies 39
Anurag S. Rathore, Garima Thakur, Saxena Nikita, and Shantanu Banerjee

2.1 Introduction 39

2.2 Control of Upstream Mammalian Bioreactor for Continuous Production of mAbs 40

2.3 Integration Between Upstream and Downstream in Continuous Production of mAbs 46

2.3.1 Continuous Clarification as a Bridge Between Continuous Upstream and Downstream 46

2.3.2 Considerations for Process Integration 48

2.4 Control of Continuous Downstream Unit Operations in mAb Manufacturing 49

2.4.1 Control of Continuous Dead-End Filtration 49

2.4.2 Control of Continuous Chromatography 50

2.4.3 Control of Continuous Viral Inactivation 53

2.4.4 Control of Continuous Precipitation 54

2.4.5 Control of Continuous Formulation 56

2.5 Integration Between Adjacent Unit Operations Using Surge Tanks 57

2.6 Emerging Approaches for High-Level Monitoring and Control of Continuous Bioprocesses 59

2.6.1 Artificial Intelligence (AI) and Machine Learning (ML) Control 60

2.6.2 Statistical Process Control 61

2.6.3 Process Digitalization 62

2.7 Conclusions 63

References 63

3 Artificial Intelligence and the Control of Continuous Manufacturing 75
Steven S. Kuwahara

3.1 Introduction 75

3.2 Continuous Monitoring and Validation 84

3.3 Choosing Other Control Charts 84

3.4 Information Awareness 85

3.5 Management and Personnel 86

References 90

Part II Intensified Biomanufacturing 93

4 Bioprocess Intensification: Technologies and Goals 95
William G. Whitford

4.1 Introduction 95

4.2 Bioprocess Intensification 98

4.2.1 Definition 98

4.2.2 New Directions 100

4.2.3 Sustainability Synergy 102

4.3 Intensification Techniques 103

4.3.1 Enterprise Resource Management 103

4.3.2 Synthetic Biology and Genetic Engineering 104

4.3.3 New Expression Systems 105

4.3.4 Bioprocess Optimization 106

4.3.5 Bioprocess Simplification 107

4.3.6 Continuous Bioprocessing 108

4.4 Materials 109

4.4.1 Media Optimization 109

4.4.2 Variability 110

4.5 Digital Biomanufacturing 110

4.5.1 Data 111

4.5.2 Bioprocess Control 112

4.5.3 Digital Twins 113

4.5.4 Artificial Intelligence 114

4.5.5 Cloud/Edge Computing 114

4.6 Bioprocess Modeling 114

4.7 Automation and Autonomation 115

4.8 Bioprocess Monitoring 117

4.9 Improved Process and Product Development 118

4.9.1 Design of Experiments 118

4.9.2 QbD and PAT 119

4.9.3 High-Throughput Systems 119

4.9.4 Methods 120

4.9.5 Commercialized Systems 120

4.10 Advanced Process Control 121

4.11 Bioreactor Design 121

4.12 Single-Use Systems 122

4.13 Facilities 123

4.14 Conclusion 126

Abbreviations and Acronyms 126

Acknowledgment 129

References 129

5 Process Intensification Based on Disposable Solutions as First Step Toward Continuous Processing 137
Stefan R. Schmidt

5.1 Introduction 137

5.1.1 Theory and Practice of Process Intensification 137

5.1.2 Current Bioprocessing 140

5.1.3 General Aspects of Disposables 140

5.2 Technical Solutions 141

5.2.1 Process Development 141

5.2.2 Upstream Processing Unit Operations 142

5.2.2.1 High-Density, Large-Volume Cell Banking in Bags 143

5.2.2.2 Seed Train Intensification 144

5.2.2.3 Cell Retention and Harvest 145

5.2.3 Downstream Processing Unit Operations 149

5.2.3.1 Depth Filtration 149

5.2.3.2 In-line Virus Inactivation 151

5.2.3.3 In-line Buffer Blending and Dilution 152

5.2.3.4 Chromatography 153

5.2.3.5 Tangential Flow Filtration 159

5.2.3.6 Drug Substance Freezing 161

5.3 Process Analytical Technology and Sensors 162

5.3.1 Sensors for USP Applications 163

5.3.2 Sensors for DSP Applications 164

5.4 Conclusions 165

5.4.1 Transition from Traditional to Intensified Processes 165

5.4.2 Impact on Cost 169

5.4.3 Influence on Time 170

References 171

6 Single-Use Continuous Manufacturing and Process Intensification for Production of Affordable Biological Drugs 179
Ashish K. Joshi and Sanjeev K. Gupta

6.1 Background 179

6.2 State of Upstream and Downstream Processes 180

6.2.1 Sizing Upstream Process 181

6.2.2 Sizing Downstream Process 182

6.2.3 Continuous Process Retrofit into the Existing Facility 184

6.2.3.1 Upstream Process 184

6.2.3.2 Downstream Process 184

6.2.4 Learning from Chemical Industry 185

6.3 Cell Line Development and Manufacturing Role 186

6.3.1 Speeding Up Upstream and Downstream Development 188

6.3.2 The State of Manufacturing 189

6.4 Process Integration and Intensification 190

6.4.1 Intensification of a Multiproduct Perfusion Platform 190

6.4.2 Upstream Process Intensification Using Perfusion Process 192

6.5 Process Intensification and Integration in Continuous Manufacturing 192

6.6 Single-Use Manufacturing to Maximize Efficiency 194

6.6.1 The Benefits of SUT in the New Era of Biomanufacturing 195

6.6.2 Managing an SUT Cost Profile 195

6.6.3 In-Line Conditioning (ILC) 196

6.6.4 Impact of Single-Use Strategy on Manufacturing Cost of Goods 197

6.6.5 Limitations of SUT 198

6.7 Process Economy 199

6.7.1 Biopharma Market Dynamics 200

6.7.2 Management of the Key Risks of a Budding Market 201

6.8 Future Perspective 202

References 203

Part III Digital Biomanufacturing 209

7 Process Intensification and Industry 4.0: Mutually Enabling Trends 211
Marc Bisschops and Loe Cameron

7.1 Introduction 211

7.2 Enabling Technologies for Process Intensification 213

7.2.1 Process Intensification in Biomanufacturing 213

7.2.2 Process Intensification in Cell Culture 214

7.2.3 Process Intensification in Downstream Processing 214

7.2.4 Process Integration: Manufacturing Platforms 216

7.2.5 The Two Elephants in the (Clean) Room 217

7.3 Digital Opportunities in Process Development 220

7.4 Digital Opportunities in Manufacturing 222

7.5 Digital Opportunities in Quality Assurance 223

7.6 Considerations 224

7.6.1 Challenges 224

7.6.2 Gene Therapy 226

7.7 Conclusions 227

References 227

8 Consistent Value Creation from Bioprocess Data with Customized Algorithms: Opportunities Beyond Multivariate Analysis 231
Harini Narayanan, Moritz von Stosch, Martin F. Luna, M.N. Cruz Bournazou, Alessandro Buttè, and Michael Sokolov

8.1 Motivation 231

8.2 Modeling of Process Dynamics 232

8.2.1 Hybrid Models 234

8.2.2 Conclusion 238

8.3 Predictive Models for Critical Quality Attributes 238

8.3.1 Historical Product Quality Prediction 238

8.3.2 Synergistic Prediction of Process and Product Quality 242

8.4 Extrapolation and Process Optimization 242

8.5 Bioprocess Monitoring Using Soft Sensors 247

8.5.1 Static Soft Sensor 248

8.5.2 Dynamic Soft Sensors 250

8.5.3 Concluding Remarks 251

8.6 Scale-Up and Scale-Down 251

8.6.1 Differences Between Lab and Manufacturing Scales 252

8.6.2 Scale-Up 253

8.6.3 Scale-Down 254

8.6.4 Conclusions 255

8.7 Digitalization as an Enabler for Continuous Manufacturing 255

References 257

9 Digital Twins for Continuous Biologics Manufacturing 265
Axel Schmidt, Steffen Zobel-Roos, Heribert Helgers, Lara Lohmann, Florian Vetter, Christoph Jensch, Alex Juckers, and Jochen Strube

9.1 Introduction 265

9.2 Digital Twins in Continuous Biomanufacturing 269

9.2.1 USP Fed Batch and Perfusion 273

9.2.2 Capture, LLE, Cell Separation, and Clarification 273

9.2.2.1 Fluid Dynamics (Red) 277

9.2.2.2 Phase Equilibrium (Blue) 277

9.2.2.3 Kinetics (Green) 277

9.2.3 UF/DF, SPTFF for Concentration, and Buffer Exchange 278

9.2.4 Precipitation/Crystallization 282

9.2.5 Chromatography and Membrane Adsorption 282

9.2.5.1 General Rate Model Chromatography 282

9.2.5.2 SEC 284

9.2.5.3 Adsorption Mechanism 284

9.2.5.4 IEX-SMA 284

9.2.5.5 HIC-SMA 285

9.2.5.6 Modified Mixed-Mode SMA 285

9.2.5.7 Modified HIC-SMA Process Model Exemplification by mab Purification 287

9.2.5.8 Model Parameter Determination 289

9.2.5.9 Phase Equilibrium Isotherms 290

9.2.5.10 Mass Transfer Kinetics 292

9.2.6 Lyophilization 293

9.2.6.1 Thermal Conductivity of the Vial 293

9.2.6.2 Product Resistance 293

9.2.6.3 Product Temperature 295

9.2.6.4 Water Properties 295

9.3 Process Integration and Demonstration 295

9.3.1 USP Fed Batch and Perfusion 301

9.3.2 Capture, LLE, Cell Separation, and Clarification 306

9.3.3 UF/DF, SPTFF for Concentration, and Buffer Exchange 309

9.3.4 Precipitation/Crystallization 311

9.3.5 Chromatography and Membrane Adsorption 314

9.3.6 Lyophilization 314

9.3.7 Comparison Between Conceptual Process Design and Experimental Data 319

9.4 PAT in Continuous Biomanufacturing 320

9.4.1 State-of-the-Art PAT 321

9.4.2 QbD-based PAT Control Strategy 322

9.4.3 Process Simulation Toward APC-Based Autonomous Operation 323

9.4.4 Applicability of Spectroscopic Methods in Continuous Biomanufacturing 328

9.4.5 Proposed Control Strategy Including PAT 332

9.4.6 Evaluation and Summary of PAT 337

9.5 Conclusion 338

Acknowledgments 339

References 339

10 Regulatory and Quality Considerations of Continuous Bioprocessing 351
Britta Manser and Martin Glenz

10.1 Introduction 351

10.2 Integrated Processing 352

10.3 Process Traceability 353

10.3.1 Batch and Lot Definition 353

10.3.2 Lot Traceability and Deviation Management 354

10.4 Process Consistency 355

10.4.1 Process Control 356

10.4.1.1 Automation 356

10.4.1.2 Process Analytical Technologies (PAT) 357

10.4.1.3 Data Analysis 359

10.4.1.4 Real-Time Release Testing 360

10.4.2 Quality by Design 360

10.4.2.1 Multicolumn Protein A Chromatography 361

10.4.2.2 Continuous Virus Inactivation 362

10.4.2.3 Bind/Elute Cation Exchange Chromatography 362

10.4.2.4 Flow-Through Anion Exchange Chromatography 363

10.4.2.5 Ultrafiltration and Diafiltration 363

10.4.2.6 Sterile Filtration 363

10.4.2.7 Virus Reduction Filtration 363

10.4.2.8 Connection of Unit Operations 364

10.5 Patient Safety 365

10.5.1 Contamination Control 365

10.5.2 Virus Safety 366

10.5.2.1 Virus Reduction in Chromatography 367

10.5.2.2 Low-pH Virus Inactivation 367

10.5.2.3 Virus Reduction Filtration 368

10.6 Equipment Design 369

10.7 Conclusion 370

References 371

Index 377

Authors

Ganapathy Subramanian Canterbury, UK.