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Preparative Chromatography for Separation of Proteins addresses a wide range of modeling, techniques, strategies, and case studies of industrial separation of proteins and peptides.
• Covers broad aspects of preparative chromatography with a unique combination of academic and industrial perspectives
• Presents Combines modeling with compliantce useing of Quality-by-Design (QbD) approaches including modeling
• Features a variety of chromatographic case studies not readily accessible to the general public
• Represents an essential reference resource for academic, industrial, and pharmaceutical researchers
Contents
List of Contributors xv
Series Preface xix
Preface xxi
1 Model-Based Preparative Chromatography Process Development in the QbD Paradigm 1
Arne Staby, Satinder Ahuja, and Anurag S. Rathore
1.1 Motivation 1
1.2 Regulatory Context of Preparative Chromatography and Process Understanding 1
1.3 Application of Mathematical Modeling to Preparative Chromatography 6
Acknowledgements 8
References 8
2 Adsorption Isotherms: Fundamentals and Modeling Aspects 11
Jørgen M. Mollerup
2.1 Introduction 11
2.2 Definitions 12
2.3 The Solute Velocity Model 14
2.4 Introduction to the Theory of Equilibrium 17
2.5 Association Equilibria 21
2.6 The Classical Adsorption Isotherm 24
2.7 The Classical Ion Exchange Adsorption Isotherm 26
2.8 Hydrophobic Adsorbents, HIC and RPC 38
2.9 Protein-Protein Association and Adsorption Isotherms 47
2.10 The Adsorption Isotherm of a GLP-1 Analogue 51
2.11 Concluding Remarks 59
Appendix 2.A Classical Thermodynamics 60
References 77
3 Simulation of Process Chromatography 81
Bernt Nilsson and Niklas Andersson
3.1 Introduction 81
3.2 Simulation-Based Prediction of Chromatographic Processes 82
3.3 Numerical Methods for Chromatography Simulation 94
3.4 Simulation-Based Model Calibration and Parameter Estimation 96
3.5 Simulation-Based Parametric Analysis of Chromatography 97
3.6 Simulation-Based Optimization of Process Chromatography 101
3.7 Summary 106
Acknowledgement 107
References 108
4 Simplified Methods Based on Mechanistic Models for Understanding and Designing Chromatography Processes for Proteins and Other Biological Products 111
Noriko Yoshimoto and Shuichi Yamamoto
4.1 Introduction 111
4.2 HETP and Related Variables in Isocratic Elution 114
4.3 Linear Gradient Elution (LGE) 120
4.4 Applications of the Model 130
4.5 Summary 145
Appendix 4.A Mechanistic Models for Chromatography 149
Appendix 4.B Distribution Coefficient and Binding Sites [20- 149
References 152
5 Development of Continuous Capture Steps in Bioprocess Applications 159
Frank Riske and Tom Ransohoff
5.1 Introduction 159
5.2 Economic Rationale for Continuous Processing 160
5.3 Developing a Continuous Capture Step 162
5.4 The Operation of MCC Systems 165
5.5 Modeling MCC Operation 167
5.6 Processing Bioreactor Feeds on a Capture MCC 169
5.7 The Future of MCC 171
References 172
6 Computational Modeling in Bioprocess Development 177
Francis Insaidoo, Suvrajit Banerjee, David Roush, and Steven Cramer
6.1 Linkage of Chromatographic Thermodynamics (Affinity, Kinetics, and Capacity) 177
6.2 Binding Maps and Coarse-Grained Modeling 180
6.3 QSPR for Either Classification or Quantification Prediction 188
6.4 All Atoms MD Simulations for Free Solution Studies and Surfaces 192
6.5 Ensemble Average and Comparison of Binding of Different Proteins in Chromatographic Systems 204
6.6 Antibody Homology Modeling and Bioprocess Development 205
6.7 Summary of Gaps and Future State 209
Acknowledgment 212
References 212
7 Chromatographic Scale-Up on a Volume Basis 227
Ernst B. Hansen
7.1 Introduction 227
7.2 Theoretical Background 229
7.3 Proof of Concept Examples 232
7.4 Design Applications: How to Scale up from Development Data 233
7.5 Discussion 240
7.6 Recommendations 242
References 245
8 Scaling Up Industrial Protein Chromatography: Where Modeling Can Help 247
Chris Antoniou, Justin McCue, Venkatesh Natarajan, Jörg Thömmes, and Qing Sarah Yuan
8.1 Introduction 247
8.2 Packing Quality: Why and How to Ensure Column Packing Quality Across Scales 248
8.3 Process Equipment: Using CFD to Describe Effects of Equipment Design on Column Performance 257
8.4 Long-Term Column Operation at Scale: Impact of Resin Lot-to-Lot Variability 264
8.5 Closing Remarks 265
References 265
9 High-Throughput Process Development 269
Silvia M. Pirrung and Marcel Ottens
9.1 Introduction to High-Throughput Process Development in Chromatography 269
9.2 Process Development Approaches 271
9.3 Case Descriptions 279
9.4 Future Directions 286
References 286
10 High-Throughput Column Chromatography Performed on Liquid Handling Stations 293
Patrick Diederich and Jürgen Hubbuch
10.1 Introduction 293
10.2 Chromatographic Methods 299
10.3 Results and Discussion 300
10.4 Summary and Conclusion 328
Acknowledgements 329
References 330
11 Lab-Scale Development of Chromatography Processes 333
Hong Li, Jennifer Pollard, and Nihal Tugcu
11.1 Introduction 333
11.2 Methodology and Proposed Workflow 336
11.3 Conclusions 377
Acknowledgments 377
References 377
12 Problem Solving by Using Modeling 381
Martin P. Breil, Søren S. Frederiksen, Steffen Kidal, and Thomas B. Hansen
12.1 Introduction 381
12.2 Theory 382
12.3 Materials and Methods 385
12.4 Determination of Model Parameters 385
12.5 Optimization In Silico 388
12.6 Extra-Column Effects 390
Abbreviations 397
References 398
13 Modeling Preparative Cation Exchange Chromatography of Monoclonal Antibodies 399
Stephen Hunt, Trent Larsen, and Robert J. Todd
13.1 Introduction 399
13.2 Theory 401
13.3 Model Development 403
13.4 Model Application 413
13.5 Conclusions 424
Nomenclature 425
Greek letters 425
References 426
14 Model-Based Process Development in the Biopharmaceutical Industry 429
Lars Sejergaard, Haleh Ahmadian, Thomas B. Hansen, Arne Staby, and Ernst B. Hansen
14.1 Introduction 429
14.2 Molecule—FVIII 430
14.3 Overall Process Design 431
14.4 Use of Mathematical Models to Ensure Process Robustness 432
14.5 Experimental Design of Verification Experiments 435
14.6 Discussion 438
14.7 Conclusion 439
Acknowledgements 439
Appendix 14.A Practical MATLAB Guideline to SEC 439
Appendix 14.B Derivation of Models Used for Column Simulations 449
References 455
15 Dynamic Simulations as a Predictive Model for a Multicolumn Chromatography Separation 457
Marc Bisschops and Mark Brower
15.1 Introduction 457
15.2 BioSMB Technology 459
15.3 Protein A Model Description 460
15.4 Fitting the Model Parameters 463
15.5 Case Studies 464
15.6 Results for Continuous Chromatography 469
15.7 Conclusions 475
References 476
16 Chemometrics Applications in Process Chromatography 479
Anurag S. Rathore and Sumit K. Singh
16.1 Introduction 479
16.2 Data Types 480
16.3 Data Preprocessing 481
16.4 Modeling Approaches 485
16.5 Case Studies of Use of Chemometrics in Process Chromatography 490
16.6 Guidance on Performing MVDA 495
References 497
17 Mid-UV Protein Absorption Spectra and Partial Least Squares Regression as Screening and PAT Tool 501
Sigrid Hansen, Nina Brestrich, Arne Staby, and Jürgen Hubbuch
17.1 Introduction 501
17.2 Mid-UV Protein Absorption Spectra and Partial Least Squares Regression 503
17.3 Spectral Similarity and Prediction Precision 511
17.4 Application as a Screening Tool: Analytics for High-Throughput Experiments 516
17.5 Application as a PAT Tool: Selective In-line Quantification and Real-Time Pooling 518
17.6 Case Studies 523
17.7 Conclusion and Outlook 532
References 532
18 Recent Progress Toward More Sustainable Biomanufacturing: Practical Considerations for Use in the Downstream Processing of Protein Products 537
Milton T. W. Hearn
18.1 Introduction 537
18.2 The Impact of Individualized Unit Operations versus Integrated Platform Technologies on Sustainable Manufacturing 543
18.3 Implications of Recycling and Reuse in Downstream Processing of Protein Products Generated by Biotechnological Processes: General Considerations 549
18.4 Metrics and Valorization Methods to Assess Process Sustainability 553
18.5 Conclusions and Perspectives 573
Acknowledgment 573
References 574
Index 583
