Preface

This book covers various aspects of preparative chromatography, with a unique combination of academic research and industrial applications. We expect it to appeal to those in academia and industry who are involved in process development and the production of peptides and proteins, an area where the industry is typically reluctant to publicly share their knowledge because of trade secret considerations. Most of these major developments have either not been disclosed at all or exist only as oral conference contributions. This book aims to alleviate some of these gaps as we aim to supplement the academic contributions with industrial contributions. This aspect makes the treatment quite novel and unique when compared with other texts on the topic.

The book is divided into two parts: basic modeling and reviews and industrial separations/case studies. The basic modeling section aims to describe the recent developments in chromatographic theory and general approaches to research to provide increased understanding of the fundamentals behind chromatographic separation and behavior of proteins in these environments. The aim of this section is to provide a solid background in the theory of chromatography to the readers and to better prepare them for industrial case studies. Topics covered comprise the application of various approaches of modeling including computer simulations and mechanistic modeling. Chapter 1, by the editors, is designated to the general background for use of the various modeling tools and approaches.

The first section of the book contains fundamental contributions, general overviews, and reviews. Chapter 2, by Mollerup, provides a general and thorough overview of the thermodynamic tools and isotherm description necessary to model process chromatography in a double chapter. The author proposes approaches for acquiring accurate experimental data from which the model parameters in the adsorption isotherms can be estimated, in order to facilitate the use of simulation tools to the design and optimization of a chromatographic separation process.

Simulation of the performance of chromatographic separation of proteins is a powerful tool, and Chapter 3, by Nilsson and Andersson, presents a summary of the many methodologies applied to various chromatographic techniques including ion exchange, affinity, and multimodal chromatography. Predictions of chromatographic behavior have been presented for a set of different separation problems, illustrating that a large number of common protein separation problems can be simulated quite easily with today's technology.

Chapter 4, by Yoshimoto and Yamamoto, describes simplified methods for understanding and designing chromatography processes for proteins and other biological products, with a focus on modeling of gradient elution chromatography. Simplified models based on the mechanistic model for linear gradient elution chromatography of proteins and other large molecule biological products are presented, together with several applications of the models to process design and process understanding and for bio-recognition.

Continuous processing, including chromatography, has gained much attention the last decade, and Chapter 5, by Riske and Ransohoff, presents industrial application of such multicolumn chromatography (MCC) systems for general capture. The authors suggest that the appropriateness and use of MCC in capture steps and in other parts of the downstream process depend on a number of factors, including the molecular characteristics and stability of the target molecule, the feed titer and product amount required, and the facility design and intention (multipurpose or dedicated). As industry gains more experience with MCC and other forms of continuous processing, the authors foresee that MCC is likely to be more commonly used throughout industry.

Molecular dynamics (MD) is another area that is getting much attention in recent years, and this approach will undoubtedly be key to better understanding of interactions on the molecular level and will ultimately result in better mechanistic models. This topic is described with case studies in Chapter 6, by Insaidoo, Banerjee, Roush, and Cramer. The authors summarize the current state of computational biophysics for determination of individual contributions of key interactions at an atomistic level. They conclude that there remains a significant gap in the linkage of experimental techniques (typically macroscopic) to biophysical modeling and that it is essential that these gaps be closed in order to realize the potential for rational process design.

Chapter 7, by Hansen, teaches the upscaling technique based on volumetric flow rate, which is founded in well-known chromatographic theory and equations, and the approach provides high process design flexibility. The chapter presents an overview of the underlying theory and also provides several examples of successful scale-ups on ion exchange and reversed-phase chromatography. A couple of industrial case studies related to these scale-ups are also presented. Finally, a step-by-step guide for scale-up is presented together with recommendations and a discussion of the challenges that a practitioner is likely to face.

The industrial separations section presents new and existing chromatographic unit operations and discusses how mechanistic and empirical modeling approaches are used to optimize equipment and methodologies. Equipment includes column hardware, scale-down equipment, continuous operation mode, etc., as well as tools for monitoring and control; for example, on-, in-, and at-line equipment for improved process development and manufacturing methods. Improved methodologies comprise scaling approaches, the use of models for validation, uncertainty and robustness evaluations, and process design. A mix of industrial, equipment vendor, and academic authors contributed to this section. Chapter 8, by Antoniou, McCue, Natarajan, Thömmes, and Yuan, provides a number of examples where modeling may help in scale-up of chromatography in industry and how computational fluid dynamics (CFD) has been applied. The authors explore why column packing is such an important criterion that has to be consistent across scales, and they discuss how models can be utilized to predict column packing across scales and to perform packing consistently in an industrial environment.

Chapters 9, 10, and 11 (by Pirrung and Ottens; Diederich and Hubbuch; and Li, Pollard, and Tugcu, respectively) present industrial applications of process development, optimization, and small-scale practice. Chapter 9, among others, demonstrates the use of the high-throughput process development (HTPD) setup to generate mechanistic model parameters for process development, optimization, and design. The authors have discussed the pros and cons of the various experimental approaches, including the one-factor-at-a-time (OFAT), design of experiments (DOE), mechanistic modeling, and hybrid approaches. Chapter 10 provides guidance to process development using robot systems, including modeling/simulation of peak shapes for mechanistic modeling and validation. Factors that have been examined include the influence of pipetting precision, absorption measurements in microtiter plates, peak fractionation, flow patterns, and salt step heights in gradient elution experiments. Separate and combined effects have been qualitatively and quantitatively investigated using both experiments and simulations based on a mechanistic model. The authors demonstrate that with a sufficient number of fractions collected per peak, a significant improvement in precision can be obtained despite low analytical precision. Finally, Chapter 11, focuses on DOE and OFAT in an HTPD setup and presents the state-of-the-art experimental process development approach. A methodology for lab-scale chromatography process development utilizing high-throughput tools in conjunction with traditional column-based methodologies has been presented. The proposed experimental plan for process development relies heavily on a DOE approach supplemented with OFAT experiments. It fully utilizes HTPD and transitions into lab-scale column experiments where additional confirmation is required for defining parameter ranges and scale-up.

Chapters 12, 13, and 14 (by Breil, Frederiksen, Kidal, and Hansen; Hunt, Larsen, and Todd; and Sejergaard, Ahmadian, T.B. Hansen, Staby, and E.B. Hansen, respectively,) present three industrial case studies of mechanistic modeling for use in-process development, optimization, challenge, and identification of critical process parameters, troubleshooting, deviation handling, control strategy setup, and establishing a design space for chromatographic purification. Also included are equation systems and computer coding that may help new applicants in setting up models. Chapter 13 presents an example where the general rate model has been used to describe transport behavior in the column and in the beads and the steric mass action binding model to describe protein binding to the resin matrix. This approach has been used successfully to describe the primary mechanisms involved in cation exchange chromatography of proteins. An open-source chromatography solver was used to estimate model parameters and evaluate the impact of operating parameters on process performance. Model parameters were estimated by performing a set of specific model calibration experiments. Pulse injection experiments...