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 Helg.