Preparative Chromatography E-Book

• Herausgeber: Wiley-VCH Verlag GmbH & Co. KGaA
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 1059

Veröffentlichungsjahr: 2020

Beschreibung

The third edition of this popular work is revised to include the latest developments in this fast-changing field. Its interdisciplinary approach elegantly combines the chemistry and engineering to explore the fundamentals and optimization processes involved.

Leseprobe

Table of Contents

Cover

Preface

About the Editors

List of Abbreviations

Notation

1 Introduction

1.1 Chromatography, Development, and Future Trends

1.2 Focus of the Book

1.3 Suggestions on How to Read this Book

References

2 Fundamentals and General Terminology

2.1 Principles and Features of Chromatography

2.2 Analysis and Description of Chromatograms

2.3 Mass Transfer and Fluid Dynamics

2.4 Equilibrium Thermodynamics

2.5 Column Overloading and Operating Modes

References

Note

3 Stationary Phases

3.1 Survey of Packings and Stationary Phases

3.2 Inorganic Sorbents

3.3 Cross‐Linked Organic Polymers

3.4 Advective Chromatographic Materials

3.5 Chiral Stationary Phases

3.6 Properties of Packings and Their Relevance to Chromatographic Performance

3.7 Sorbent Maintenance and Regeneration

References

Note

4 Selection of Chromatographic Systems

4.1 Definition of the Task

4.2 Mobile Phases for Liquid Chromatography

4.3 Adsorbent and Phase Systems

4.4 Criteria for Choosing Normal Phase Systems

4.5 Criteria for Choosing Reversed Phase Systems

4.6 Criteria for Choosing CSP Systems

4.7 Downstream Processing of mAbs Using Protein A and IEX

4.8 Size‐Exclusion Chromatography (SEC)

4.9 Overall Chromatographic System Optimization

References

Note

5 Process Concepts

5.1 Discontinuous Processes

5.2 Continuous Processes

5.3 Choice of Process Concepts

References

Note

6 Modeling of Chromatographic Processes

6.1 Introduction

6.2 Models for Single Chromatographic Columns

6.3 Including Effects Outside the Columns

6.4 Calculation Methods and Software

References

Note

7 Determination of Model Parameters

7.1 Parameter Classes for Chromatographic Separations

7.2 Concept to Determine Model Parameters

7.3 Detectors and Parameter Estimation

7.4 Determination of Packing Parameters

7.5 Adsorption Isotherms

7.6 Mass Transfer Kinetics

7.7 Plant Parameters

7.8 Experimental Validation of Column Models and Model Parameters

References

Note

8 Process Design and Optimization

8.1 Basic Principles and Definitions

8.2 Batch Chromatography

8.3 Recycling Chromatography

8.4 Conventional Isocratic SMB Chromatography

8.5 Isocratic SMB Chromatography Under Variable Operating Conditions

8.6 Gradient SMB Chromatography

8.7 Multicolumn Systems for Bioseparations

References

Note

9 Process Control

9.1 Standard Process Control

9.2 Advanced Process Control

References

Note

10 Chromatography Equipment: Engineering and Operation

10.1 Challenges for Conceptual Process Design

10.2 Engineering Challenges

10.3 Commercial Chromatography Columns

10.4 Commercial Chromatographic Systems

10.5 Packing Methods

10.6 Process Troubleshooting

10.7 Disposable Technology for Bioseparations

References

Note

Appendix A: Data of Test Systems

A.1 EMD53986

A.2 Tröger's Base

A.3 Glucose and Fructose

A.4 β‐Phenethyl Acetate

References

Index

End User License Agreement

List of Tables

Chapter 2

Table 2.1 Ranges of adsorption enthalpies.

Chapter 3

Table 3.1 Inorganic packings for chromatography and their characteristic prop...

Table 3.2 Survey of the type of synthetic zeolites and their applications.

Table 3.3 Isoelectric points of different oxides.

Table 3.4 Interrelationship between adsorbent characteristics and chromatogra...

Table 3.5 Performance of RP silica packed into columns with different i.d.

Table 3.6 Reversed phase silica sorbents with extended alkaline stability.

Table 3.7 Conditions influencing the stability of silica sorbents.

Table 3.8 Aluminum oxide with different surface properties.

Table 3.9 Different Brockmann grades of aluminum oxide.

Table 3.10 Ion‐exchange ligands.

Table 3.11 Properties of cation exchangers as provided by manufacturers.

Table 3.12 Properties of anion exchangers as provided by manufacturers.

Table 3.13 Properties of mixed‐mode sorbents.

Table 3.14 Commercially available protein A affinity sorbents.

Table 3.15 Protein G and L sorbents.

Table 3.16 Commercially available IMAC resins.

Table 3.17 Streptavidin and FLAG®‐based affinity resins.

Table 3.18 Other tag‐based affinity resins.

Table 3.19 Mimetic affinity sorbents.

Table 3.20 Cammelidae antibody‐based affinity sorbents.

Table 3.21 Small protein‐based affinity ligands.

Table 3.22 Customized resins for plasma protein purification.

Table 3.23 Customized affinity resins for generic recombinant proteins.

Table 3.24 Properties of different monolithic columns of the CIMmultus™ serie...

Table 3.25 Affinity resins for the capturing of adeno‐associated viral (AAV) ...

Table 3.26 Commercial packings with enantioselective properties.

Table 3.27 Different approaches to prepare bonded cellulose chiral phases on ...

Table 3.28 Cellulose‐ and amylase‐based chiral stationary phases.

Table 3.29 Product features of different classes of chiral stationary phases.

Table 3.30 Comparison of the particle size distribution data of a LiChrospher...

Table 3.31 CIP procedures for silica‐based adsorbents after Majors (2003a) an...

Table 3.32 Recommended cleaning and regeneration steps for Fractogel® IEX res...

Table 3.33 Different purification regimes for protein A sorbents.

Table 3.34 SIP procedures.

Table 3.35 Recommended solvents for storage and flushing.

Chapter 4

Table 4.1 Differentiation between analytical and preparative chromatography.

Table 4.2 Questionnaire for the collection of the information.

Table 4.3 Properties of solvents frequently used in preparative chromatograph...

Table 4.4 Limited miscibilities of solvents for preparative chromatography.

Table 4.5 Elution of recombinant human insulin on PharmPrep® P100 RP‐18 using...

Table 4.6 Common buffer compounds used in biochromatography.

Table 4.7 Buffer additives.

Table 4.8 Reagents used for the intermediate wash of protein A resins.

Table 4.9 Typical gradient runs for reversed and normal phase systems.

Table 4.10 Eluotropic series for alumina and silica.

Table 4.11 Classification of the solvent properties of common liquids.

Table 4.12 Solvents for preliminary TLC experiments.

Table 4.13 Solvent series based on dichloromethane–methanol mixtures.

Table 4.14 Optimization of an RP separation with LiChrospher® RP‐18 and diffe...

Table 4.15 Optimization of RP separation of three intermediates by gradient o...

Table 4.16 Derivatization of a chiral C3 building block and corresponding chr...

Table 4.17 Process parameters for the separation of egg white proteins on the...

Table 4.18 Commercially available preparative SEC sorbents.

Table 4.19 Summary of the purification results for an API and its impurities ...

Chapter 5

Table 5.1 Example 1.

Table 5.2 Example 2.

Table 5.3 Example 3.

Table 5.4 Example 4.

Table 5.5 Example 5.

Table 5.6 Example 6.

Chapter 6

Table 6.1 Fields of application of different continuous models available to s...

Table 6.2 Examples of dynamic process simulation tools.

Chapter 7

Table 7.1 Parameter determination methods.

Table 7.2 Methods and steps in isotherm determination.

Chapter 8

Table 8.1 Different design and operating parameters for a single column (EMD5...

Table 8.2 Different design and operating parameters for a single column (Glu/...

Table 8.3 Different design and operating parameters with

N

i

,new

less than or e...

Table 8.4 Identical dimensionless parameters for the SMB processes.

Table 8.5 Different operating and design parameters for SMB plant.

Table 8.6 Values of the objective functions at the exemplary operating points...

Table 8.7 Operating parameters for EMD53986 obtained by the TMB shortcut meth...

Table 8.8 Operating parameters for EMD53986 obtained by the experimental shor...

Table 8.9 Optimization of plate number for EMD53986.

Table 8.10 Classes of SMB process concepts under variable conditions.

Table 8.11 Theoretical case study for SMB and Varicol.

Table 8.12 Experimental case study for five‐column SMB and Varicol processes.

Table 8.13 Influence of the number of columns on extract purity for a given p...

Table 8.14 Transfer of the modifier concentrations from the batch chromatogra...

Chapter 10

Table 10.1 Modeling of a chromatographic step (Toumi et al. 2010).

Table 10.2 Typical dimensions and operation conditions for stainless steel co...

Table 10.3 Typical dimensions and operating conditions for acrylic and glass ...

Table 10.4 Construction materials and selecting attribute for chromatography ...

Table 10.5 Construction materials and selecting attribute for chromatography ...

Table 10.6 Protein binding for construction materials.

Table 10.7 Examples of available pumps, features, and limitations.

Table 10.8 Typical flow rates and tube diameters for different column geometr...

Table 10.9 Chromatographic detection systems and their detection principles.

Table 10.10 Amount of packing material per liter of bed volume.

Table 10.11 Suggestions for slurry solvents.

Table 10.12 Slurry volumes.

Table 10.13 Test systems for normal phase and reversed phase columns.

Table 10.14 Recommended solvents for storage and flushing.

Table 10.15 Possible technical failures in a chromatography system.

Appendix A

Table A.1 Typical design and model parameters for EMD53986.

Table A.2 Parameters for model validation batch column (EMD53986).

Table A.3 Parameters for model validation SMB (EMD53986).

Table A.4 Typical design and model parameters for Tröger's base.

Table A.5 Parameters for model validation SMB (Tröger's base).

Table A.6 Typical design and model parameters for fructose–glucose.

Table A.7 Parameters for model validation SMB (fructose–glucose).

Table A.8 Typical design and model parameters for

β

‐phenethyl acetate.

List of Illustrations

Chapter 1

Figure 1.1 Development of chromatography..

Chapter 2

Figure 2.1 Definitions of a chromatographic system.

Figure 2.2 Principle of adsorption chromatography.

Figure 2.3 Different volumes in beds packed with porous particles.

Figure 2.4 Illustration of chromatography with tracer components and the rel...

Figure 2.5 Chromatogram of one unretained and two retained components.

Figure 2.6 Determination of variance for Gaussian peaks (a) and estimation o...

Figure 2.7 Dependence of

HETP

on interstitial phase velocity.

Figure 2.8 Optimization of peak resolution. (a) Base case. (b) Improved effi...

Figure 2.9 Influence of selectivity on efficiency for two different resoluti...

Figure 2.10 Band broadening in a column due to axial dispersion.

Figure 2.11 Mass transfer phenomena during the adsorption of a molecule.

Figure 2.12 Fluid distribution nonidealities according to Tsotsas (1987). (a...

Figure 2.13 Different types of courses of adsorption isotherms.

Figure 2.14 Single‐component Langmuir isotherm.

Figure 2.15 Initial slopes of the isotherms for two different components.

Figure 2.16 Protein adsorption on ion‐exchange resin with steric shielding.

Figure 2.17 Influence of the course of the equilibrium isotherms on the shap...

Figure 2.18 Single‐component Langmuir isotherms and multicomponent Langmuir ...

Figure 2.19 Elution profiles for different mass ratios of the feed mixtures....

Figure 2.20 Illustration of different types of overloading chromatographic c...

Figure 2.21 Chromatograms (signal over time) for (a) isocratic elution and (...

Chapter 3

Figure 3.1 Types of chromatographic sorbents and their interaction principle...

Figure 3.2 Procedures employed to manufacture spherical silica particles.

Figure 3.3 Dehydration and dihydroxylation of silica surfaces.

Figure 3.4 Types of silanol groups: isolated (1), terminal (2), vicinal (3),...

Figure 3.5 Determination of the resolution factor at different loads for fou...

Figure 3.6 Types of RP columns. (a) “Brush” type; classical endcapping. (b) ...

Figure 3.7 Column efficiency versus load for normal phase silica, LiChrosper...

Figure 3.8 Pressure versus flow behavior of 10 and 20 μm PharmPrep® P 100 RP...

Figure 3.9 Evaluation of column stability under 100% water as the eluent. St...

Figure 3.10 Chromatogram of a test mixture to assess hydrophobic properties,...

Figure 3.11 Chromatogram of a test mixture to assess the silanol activity of...

Figure 3.12 Comparison of the capacity at 2 min residence time versus the ma...

Figure 3.13 Scheme of the agarose gel network (a) compared with a network fo...

Figure 3.14 SEM picture of a macroporous polymer bead (Eshmuno®); magnificat...

Figure 3.15 Poly(styrene‐divinylbenzene).

Figure 3.16 Presentation of ionic ligands on different ion‐exchange type res...

Figure 3.17 Inverse size exclusion data of different ion‐exchange sorbents: ...

Figure 3.18 Adsorption of dye‐labeled proteins on different ion‐exchange sor...

Figure 3.19 Binding sites of affinity selectors.

Figure 3.20 Structure of Cibacron blue and the affinity ligand A2P.

Figure 3.21 Different architectures of adsorptive materials.

Figure 3.22 Calibration curve of cetuximab on rSPA silica monolith ranging f...

Figure 3.23 Typical saturation capacity of the most used commercially availa...

Figure 3.24 Rational screening process for enantioseparation by applying tar...

Figure 3.25 Particle size distribution of silica spheres before (a) and afte...

Figure 3.26 SEM pictures of silica spheres before (a) and after (b) size cla...

Figure 3.27 TEM image of a silica xerogel (diameter of the primary particles...

Figure 3.28 SEM picture of a 20 μm spherical agglomerate consisting of 750 n...

Figure 3.29 Separation of insulin and A21‐desamido insulin before and after ...

Figure 3.30 Variation of retention time for test protein mixture after 100 c...

Figure 3.31 Influence of surface pH on the retention time of two test compou...

Figure 3.32 Reaction of dimethoxypropane for chemical removal of water from ...

Chapter 4

Figure 4.1 Tasks for preparative chromatography in different development sta...

Figure 4.2 Development of a chromatographic method.

Figure 4.3 Purification of paclitaxel out of a crude extract. Complexity of ...

Figure 4.4 Main types of preparative chromatographic separation scenarios. (...

Figure 4.5 Elements of the chromatographic system.

Figure 4.6 Decision tree for the choice of mobile phases.

Figure 4.7 Viscosity of different mixtures of water and organic solvents.

Figure 4.8 Selection of phase systems dependent on the separation problem.

Figure 4.9 Influence of methanol content and temperature on solubility.

Figure 4.10 Peak distortion due to injection of sample dissolved in pure met...

Figure 4.11 Scheme of conventional column loading (a) and at-column dilution...

Figure 4.12 Maximum solubility of a sample for two different purities; sampl...

Figure 4.13 Surface groups on silica.

Figure 4.14 Graphical representation of the adsorption process.

Figure 4.15 Nomograms for binary mixtures of

n

‐hexane and dichloromethane wi...

Figure 4.16 Solvent characterization according to proton acceptor and donor ...

Figure 4.17 Graphic representation of the PRISMA model: (a) complete model a...

Figure 4.18 Example calculation of mobile phase composition.

Figure 4.19 Basic selectivity points of the PRISMA model.

Figure 4.20 Combination of three neat solvents in the irregular part of the ...

Figure 4.21 TLC experiments for the separation of two isomers using neat sol...

Figure 4.22 Screening of binary mixtures (50 : 50 v/v) of selected neat solv...

Figure 4.23 Starting points for selectivity optimization.

Figure 4.24 Screening of ternary solvent mixtures.

Figure 4.25 Vario chamber with accessories.

Figure 4.26 Simplified procedure to establish the start and end composition ...

Figure 4.27 Retention behavior in both normal and reversed phase chromatogra...

Figure 4.28 Retention of aromatic components on RP‐8 and RP‐18 columns with ...

Figure 4.29 Separation of

Ginkgo biloba

terpenes on RP chromatography with d...

Figure 4.30 Nomogram for the elution strength of acetonitrile, methanol, and...

Figure 4.31 Standard HPLC mass spectrometric reversed phase analysis procedu...

Figure 4.32 Standard gradient with modified weak solvent.

Figure 4.33 Choice of optimal solvent mixture for RP chromatography.

Figure 4.34 Separation with LiChrospher® RP‐18 with acetonitrile–water (80 :...

Figure 4.35 Dependency of retention factor on mobile phase composition.

Figure 4.36 Optimization of mobile phase composition by gradient operation.

Figure 4.37 Initial gradient for the separation of three intermediates.

Figure 4.38 Gradient runs for two different organic solvents with LiChrosphe...

Figure 4.39 Screening strategy for chiral separations.

Figure 4.40 Effect of high feed loading on achiral stationary phase. (a) wit...

Figure 4.41 Separation of a pair of diastereomers on different nonchiral and...

Figure 4.42 mAb purification platform. (a) standard process (b) intensified ...

Figure 4.43 Static binding capacity of mAb on cation‐exchange (CEX) resins h...

Figure 4.44 Principle of the Rapptor® robotic platform. Samples are incubate...

Figure 4.45 Influence of the single equation parameters on resolution.

Figure 4.46 Working ranges of chromatographic separations.

Figure 4.47 Increase in productivity due to forced elution step (injection o...

Figure 4.48 (a–c) Chromatograms on the single sorbents. (d) Chromatogram on ...

Figure 4.49 Injection of 50 g of product on a cyano‐modified silica. Column:...

Figure 4.50 Injection of 50 g on a column filled with silica connected with ...

Chapter 5

Figure 5.1 General setup of a preparative chromatographic plant.

Figure 5.2 Separation of two components under touching band and stacked inje...

Figure 5.3 Pre‐column for the adsorption of late‐eluting impurities.

Figure 5.4 Principles of isocratic operation (a) and a simple gradient eluti...

Figure 5.5 Isocratic and gradient elution modes realized by varying mobile p...

Figure 5.6 Typical ion‐exchange separation using linear gradient elution.

Figure 5.7 Principle of closed‐loop recycling chromatography (CLRC). In conv...

Figure 5.8 Development of concentrations during closed‐loop recycling chroma...

Figure 5.9 Steady‐state recycling chromatography (SSRC) in mixed‐recycle mod...

Figure 5.10 Flip‐flop concept.

Figure 5.11 Principle of the chromatographic batch reactor.

Figure 5.12 Annular chromatographic separation.

Figure 5.13 ISEP principle; the rotating valve.

Figure 5.14 ISEP principle involving parallel and serial column interconnect...

Figure 5.15 True moving bed (TMB) chromatography with internal concentration...

Figure 5.16 Simulated moving bed (SMB) chromatography.

Figure 5.17 Possible setups of SMB units with an additional recycle pump.

Figure 5.18 Three‐section SMB concept.

Figure 5.19 Switching strategies for (a) SMB and (b) Varicol.

Figure 5.20 Flow rates during PowerFeed operation (illustrative example).

Figure 5.21 Flow rates during Partial‐Feed operation. (a) Feed flow rate. (b...

Figure 5.22 Flow rates during iSMB operation. (a) Injection period. (b) Reci...

Figure 5.23 3C‐iSMB cascade separation. (1a, 2a) Injection period. (1b, 2b) ...

Figure 5.24 Feed concentration during Modicon operation.

Figure 5.25 Solvent gradient operation of a SMB unit.

Figure 5.26 Supercritical batch chromatography with CO

2

recycling.

Figure 5.27 Supercritical fluid operation of a SFC‐SMB unit.

Figure 5.28 Examples for possible approaches for multicomponent separations ...

Figure 5.29 Integrated continuous process for protein production.

Figure 5.30 2–4 column MCC processes, commercialized by ChromaCon (CaptureSM...

Figure 5.31 Process steps of capture chromatography.

Figure 5.32 Three‐column PCC chromatography with hypothetical countercurrent...

Figure 5.33 Three‐column PCC chromatography: practical process scheme, where...

Figure 5.34 Schematic diagram of the CaptureSMB process.

Figure 5.35 Sequential multicolumn chromatography (SMCC). (a) Step 1. (b) St...

Figure 5.36 SMCC process with three columns.

Figure 5.37 Continuous multicolumn countercurrent solvent gradient purificat...

Figure 5.38 Process steps during a switching period of the twin‐column MCSGP...

Figure 5.39 Chromatographic simulated moving bed reactor.

Figure 5.40 (a) Three‐section Hashimoto process. (b) Four‐section process va...

Figure 5.41 Reactive SMB process with a pH gradient for the production of th...

Figure 5.42 Guidelines for the choice of a process concept.

Figure 5.43 Example 1: Analytical conditions.

Figure 5.44 Example 1: Preparative conditions.

Figure 5.45 Example 2: Analytical conditions.

Figure 5.46 Example 2: Preparative conditions.

Figure 5.47 Example 3: Analytical conditions.

Figure 5.48 Example 3: Preparative conditions.

Figure 5.49 Example 4: Analytical conditions.

Figure 5.50 Example 4: Preparative conditions.

Figure 5.51 Example 5: Analytical conditions.

Figure 5.52 Example 5: Preparative conditions.

Figure 5.53 Example 6: Analysis of the complete feed stock.

Figure 5.54 Example 6: Analysis of the two fractions obtained by the initial...

Chapter 6

Figure 6.1 Illustration of the discrete equilibrium stage model according to...

Figure 6.2 Principle of differential mass balances for a chromatographic col...

Figure 6.3 Classification of different continuous models capable of describi...

Figure 6.4 Differential model elements required to derive continuous models ...

Figure 6.5 Concentration profile assumed in liquid film linear driving force...

Figure 6.6 Illustration of the analytical solution of the concentration prof...

Figure 6.7 Hodograph plot corresponding to the cycle shown in Figure 6.6.

Figure 6.8 Comparison between the analytical solutions valid for linear isot...

Figure 6.9 Comparison between (a) process flow diagram and (b) simulation fl...

Figure 6.10 Scheme of discretized space–time domain using a uniform grid.

Figure 6.11 Approximation of spatial derivatives by difference quotients.

Figure 6.12 Representation of the numerical solution by the OCFE method for ...

Chapter 7

Figure 7.1 Concept to determine the model parameters (T, tracer; A and B, so...

Figure 7.2 Illustration of different ways to determine the various types of ...

Figure 7.3 Graphical guideline for determining adsorption isotherms. (a) Sin...

Figure 7.4 Principle of different static methods for isotherm determination....

Figure 7.5 Typical breakthrough curve for adsorption and desorption of a pur...

Figure 7.6 Typical breakthrough curve for adsorption and desorption of a bin...

Figure 7.7 Experimental breakthrough curves of the mixture of

R

‐ and

S

‐enant...

Figure 7.8 Comparison of experimental data (rhombuses and triangles) and fit...

Figure 7.9 Measured and calculated isotherms for pure components and mixture...

Figure 7.10 Experimental breakthrough curves of a ternary mixture 2‐phenylet...

Figure 7.11 Adsorption equilibrium data (symbols) for ternary mixtures of

2‐

...

Figure 7.12 Illustration of the principle of the (a) ECP and (b) FACP method...

Figure 7.13 Principle of the minor disturbance method for a single‐component...

Figure 7.14 (a) Results for isotherm determination for Tröger's base on Chir...

Figure 7.15 Illustration of the perturbation method. (a) Detector responses ...

Figure 7.16 Comparison of experimental and simulated profiles (feed:

R

‐enant...

Figure 7.17 Comparison of experimental and simulated profiles for the separa...

Figure 7.18 Comparison of the simulated profiles for the modified multicompo...

Figure 7.19 Measured and simulated pulse experiment for the Tröger's base ra...

Figure 7.20 Measured and simulated pulse experiment for the glucose–fructose...

Figure 7.21 Simplified axial concentration profile and flow sheet for an SMB...

Figure 7.22 Principle setup of an SMB plant including detector systems in th...

Figure 7.23 Simulation flow sheet of the SMB process (“SMB column model”).

Figure 7.24 Simulation flow sheet for the “extended SMB model.”

Figure 7.25 Node model for the TMB process.

Figure 7.26 Axial concentration profile for (a) TMB and SMB processes with d...

Figure 7.27 Relationship between the temporal profile measured behind the ei...

Figure 7.28 Measured and simulated concentration profiles in the SMB for EMD...

Figure 7.29 Measured and simulated concentration profiles in the SMB for EMD...

Figure 7.30 Simulated and measured (sampled) concentration profiles in the S...

Chapter 8

Figure 8.1 Equality of concentration profiles in a chromatographic column (E...

Figure 8.2 Comparison of concentration profiles from different columns (Glu/...

Figure 8.3 Comparison of concentration profiles with

N

i

,new

less than or equ...

Figure 8.4 Equality of axial concentration profiles in SMB plant (EMD53986).

Figure 8.5 Cut strategies for a binary mixture. (a) Cut strategy I and (b) c...

Figure 8.6 Dependency of yield for 99% purity on number of stages and loadin...

Figure 8.7 Dependency of volume‐specific productivity on number of stages an...

Figure 8.8 Dependency of specific eluent consumption on number of stages and...

Figure 8.9 Positions of the three exemplary operating points with opposition...

Figure 8.10 Comparison of chromatograms (maximum productivity; low eluent co...

Figure 8.11 Comparison of chromatograms (maximum productivity; high yield).

Figure 8.12 Design and optimization strategy for batch chromatographic colum...

Figure 8.13 Shortcut design of SSRC. (a) Determination of cut times by integ...

Figure 8.14 CLRC elution profiles of three different experiments for constan...

Figure 8.15 CLRC elution profiles with peak shaving for constant loading fac...

Figure 8.16 Scale‐up strategy for closed‐loop recycling chromatography.

Figure 8.17 Optimal axial concentration profile of an SMB process at the end...

Figure 8.18 Directions of migration of two components in a TMB separation.

Figure 8.19 Operating plane or triangle diagram for linear isotherms.

Figure 8.20 Operating plane or triangle diagram for nonlinear isotherms.

Figure 8.21 Influence of the feed concentration on the operating diagram.

Figure 8.22 Axial concentration profiles for different flow rates in section...

Figure 8.23 Axial concentration profile with pollution of the extract (syste...

Figure 8.24 Suboptimal axial concentration profile for complete separation (...

Figure 8.25 Strategy for the optimization of operating parameters.

Figure 8.26 Scheme for optimization of design and operating parameter of SMB...

Figure 8.27 Influence of the number of columns and column distribution on th...

Figure 8.28 Performance evaluation criteria of different switching schemes o...

Figure 8.29 Pareto‐optimal solutions for recovery and desorbent consumption:...

Figure 8.30 Comparison of the optimal separation performances of the (a) fou...

Figure 8.31 Pareto‐optimal curves of PowerFeed and Varicol and SMB processes...

Figure 8.32 Nominal and robust Pareto curves for four‐column SMB,

Varicol

(

V

...

Figure 8.33 Operating points for optimal productivity in the

m

II

–

m

III

plane....

Figure 8.34 Operating map for a solvent gradient TMB process.

Figure 8.35 Influence of salt concentration on (a) the operating map and (b)...

Figure 8.36 Comparison of shortcut calculations and rigorous SMB simulations...

Figure 8.37 (a) Scheme of a three‐section open‐loop gradient TMB process and...

Figure 8.38 Separation region based on equilibrium theory and equilibrium st...

Figure 8.39 Empirical design procedure of the 6‐column MCSGP process.

Figure 8.40 Empirical design procedure for the twin‐column MCSGP process. Tr...

Figure 8.41 Empirical design procedure of the twin‐column MCSGP p...

Figure 8.42 Scheme for the determination of operating parameters for the twi...

Figure 8.43 Exemplary breakthrough curves for the determination of the opera...

Figure 8.44 Human IgG batch chromatography: comparison of experimental (○) a...

Figure 8.45 Optimized batch run for IgG capture: comparison of experimental ...

Figure 8.46 Internal chromatogram at cyclic steady state for a three column ...

Figure 8.47 Comparison of the optimal productivity capture between batch chr...

Chapter 9

Figure 9.1 Flowchart of the iterative online optimization algorithm for batc...

Figure 9.2 Iterative optimization of the operating parameters of a batch sep...

Figure 9.3 Discrepancy between real and predicted chromatograms for the iter...

Figure 9.4 Three‐section reactive SMB process for glucose isomerization.

Figure 9.5 Online optimizing control structure.

Figure 9.6 Evaluation of the estimated parameters.

Figure 9.7 Experimental control result for glucose isomerization.

Figure 9.8 Reaction of the switched online parameter and state estimation sc...

Figure 9.9 Moving concentration fronts in a four zone SMB plant. Solid lines...

Figure 9.10 Experimental validation: (a) parameter estimator and (b) closed‐...

Figure 9.11 Simulated moving bed processes coupled with (a) crystallization ...

Figure 9.12 Dynamic responses to different step disturbances of the overall ...

Figure 9.13 Open‐loop (grey line) compared with closed‐loop (black line) dyn...

Chapter 10

Figure 10.1 Principle of monoclonal antibody production.

Figure 10.2 Buffer tanks and plant space requirement in a typical biotech fa...

Figure 10.3 Different scenarios of a large‐scale biotech project.

Figure 10.4 Definition of

L

/

D

ratio according to ASME BPE.

Figure 10.5 (a) Instrument tee. (b) Inline diaphragm seal with sterile conne...

Figure 10.6 Double block and bleed concept: (a) separation from distribution...

Figure 10.7 Inlet sequence at the buffer header including isolation valves.

Figure 10.8 Isobars and streamlines for a cylindrical column outlet.

Figure 10.9 Cross section of a column inlet with frit system.

Figure 10.10 Flow cell geometry design and impact on exit velocity.

Figure 10.11 Tracer transition profiles at the column outlet(s) obtained wit...

Figure 10.12 Hygienic criteria for pharmaceutical applications.

Figure 10.13 Sampling for cleanability test.

Figure 10.14 P&ID of a valve gradient‐based LPLC system.

Figure 10.15 Influence of holdup volume and diffusive space in a chromatogra...

Figure 10.16 Valve‐based and pump‐based mixing.

Figure 10.17 Acceptance range for the mixing of two solvents.

Figure 10.18 P&ID of an HPLC system.

Figure 10.19 Influence of system design on dead time and peak distortion.

Figure 10.20 (a) UOP PAREX process with rotary valve and (b) SMB process wit...

Figure 10.21 AZURA Lab SMB System.

Figure 10.22 Varicol multicolumn (1 m i.d.) continuous process.

Figure 10.23 Slurry tank and stirrers for low shear stress.

Figure 10.24 Detection regimes of HPLC detectors.

Figure 10.25 Signal‐to‐noise ratios for two peaks.

Figure 10.26 Pressure/flow curve according to chromatography media rigidity.

Figure 10.27 Circle suspension flow packing.

Figure 10.28 The principle of flow packing.

Figure 10.29 Flow packing of chromatography resins (46 cm i.d. Eastern River...

Figure 10.30 The principle of DAC packing.

Figure 10.31 DAC packing of chromatography resins (using a 46 cm i.d. Easter...

Figure 10.32 The principle of stall packing.

Figure 10.33 Stall packing phase of the combined method (a 46 cm i.d. Easter...

Figure 10.34 Vacuum packing.

Figure 10.35 Vibration packing of rigid matrices in a process column. The vi...

Figure 10.36 Test chromatogram of a

t

0

marker and three phthalic acid esters...

Figure 10.37 Plate height–linear velocity curve of two different adsorbents ...

Figure 10.38 Disposable multicolumn purification unit (Cadence™ BioSMB Proce...

Figure 10.39 Examples of disposable membrane devices.

Appendix A

Figure A.1 Chemical structure of EMD53986.

Figure A.2 Chemical structure of Tröger's base.

Figure A.3 Chemical structure of glucose.

Figure A.4 Chemical structure of fructose.

Figure A.5 Chemical structure of β‐phenethyl acetate.

Guide

Cover

Table of Contents

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Preparative Chromatography

Edited by

Henner Schmidt-Traub

Michael Schulte

Andreas Seidel-Morgenstern

Third Edition

Editors

Prof. (em.) Dr.‐Ing. Henner Schmidt‐Traub

TU Dortmund

Fakultüt für Bio‐ und

Chemieingenieurwesen Lehrstuhl für

Anlagen‐ und

Prozesstechnik Emil‐Figge‐Str. 70

44227 Dortmund

Germany

Dr. Michael Schulte

Merck KGaA

Life Science ‐ Bioprocessing

Purification R&D Frankfurter Str. 250

64293 Darmstadt

Germany

Prof. Dr.‐Ing. Andreas Seidel‐Morgenstern

Otto‐von‐Guericke‐Universität

Institut für

Verfahrenstechnik

Lehrstuhl für Chemische

Verfahrenstechnik and

Max‐Planck‐Institut für Dynamik

komplexer technischer

SystemeSandtorstraße 1

Universitätsplatz 239106

Magdeburg Germany

Cover

The cover image of a multicolumn continuous plant is reproduced by courtesy of Novasep, France.

The cover image of a column head is reproduced by courtesy of Merck, Germany.

All books published by Wiley‐VCH are carefully produced. Nevertheless, authors, editors, and publisher do not warrant the information contained in these books, including this book, to be free of errors. Readers are advised to keep in mind that statements, data, illustrations, procedural details or other items may inadvertently be inaccurate.

Library of Congress Card No.:

applied for

British Library Cataloguing‐in‐Publication Data

A catalogue record for this book is available from the British Library.

Bibliographic information published by the Deutsche Nationalbibliothek

The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available on the Internet at <http://dnb.d-nb.de>.

© 2020 Wiley‐VCH Verlag GmbH & Co. KGaA, Boschstr. 12, 69469 Weinheim, Germany

All rights reserved (including those of translation into other languages). No part of this book may be reproduced in any form – by photoprinting, microfilm, or any other means – nor transmitted or translated into a machine language without written permission from the publishers. Registered names, trademarks, etc. used in this book, even when not specifically marked as such, are not to be considered unprotected by law.

Print ISBN: 978‐3‐527‐34486‐4

ePDF ISBN: 978‐3‐527‐81631‐6

ePub ISBN: 978‐3‐527‐81633‐0

oBook ISBN: 978‐3‐527‐81634‐7

Cover Design Formgeber, Mannheim, Germany

Preface

In the 7 years after publishing the second edition of this book, both practical application as well as theoretical research on preparative chromatography have progressed significantly. This motivated us to this revision.

New materials for stationary phases emerged especially for the separation of large biomolecules and widened the potentials for method developments. Although the fundamentals of chromatography are still the same as in the time of the second edition recent research expanded in order to better quantify multi-component equilibria, for instance by application  of the ideal adsorbed solution theory (IAS theory). The inspiring concept of simulated moving bed chromatography was further extended. Now a variety of new multicolumn processes are available that connect a certain number of individual columns almost in an arbitrary manner. The main driving force for these developments was biotechnology, where increasing product titers, the need to replace batch separations as a bottleneck in downstream processing, and the high costs related to some specialized stationary phase materials fostered the development of new and more efficient continuous chromatographic processes. Recent achievements summarized in the book are improved rules and procedures for design and operation of chromatographic equipment.  Further, through collaboration of process engineers and mathematicians, faster and more efficient algorithms for simulating and especially optimizing chromatographic processes have been developed and can be applied to a broad variety of concepts. Advanced process control systems are available to run chromatographic processes optimally. However, open literature gives the impression that up to now these procedures are not very common in practice. Therefore, we hope that this chapter will motivate practitioners to have a closer look at these promising methods.

With this book, we address preparative and process chromatographic issues from both the chemist's and the process engineer's viewpoints in order to improve the mutual understanding and to transfer knowledge between both disciplines. In addition, we want to reach colleagues from industries as well as academia interested in chromatographic separation with preparative purpose. Students and other newcomers looking for detailed information about design and operation of preparative chromatography are hopefully other users of this book. Our message to all of them is that chromatography is nowadays rather well understood and not that difficult and expensive as it is often claimed and perceived. On the other hand, chromatography is a challenging technique and of course not the solution for all separation problems.

Reinhard Ditz, Sebastian Engell, Andreas Jupke, Malte Kaspereit, and Arthur Susanto are former authors who joined our team again. New authors are Andreas Biselli, Achim Kienle, and Martin Leipnitz. All of them we thank for their contributions. We are aware that they have done the writing in addition to their daily work and apologize for sometimes getting on their nerves by pressing them to meet time limits. We also want to acknowledge the assistance of Matthias Etmanski, who produced new drawings, eliminated misprints, and was patient enough to handle all our revisions. The support by the editing team of Wiley was very helpful, they identified (hopefully all) misprints and created an excellent layout of the book. Last but not least, we thank our families and friends for their patience and support that was essential to bring out this book.

November 2019

Henner Schmidt‐TraubMichael SchulteAndreas Seidel‐Morgenstern

About the Editors

Henner Schmidt‐Traub was professor of Plant and Process Design at the Department of Biochemical and Chemical Engineering, TU Dortmund University, Germany, until his retirement in 2005. He is still active in the research community, and his main areas of research focus on preparative chromatography, downstream processing, and plant design. Prior to his academic appointment, Prof. Schmidt‐Traub gained 15 years of industrial experience in plant engineering.

Michael Schulte is head of Purification R&D at Merck KGaA Life Sciences, Darmstadt, Germany. In his PhD thesis at the University of Münster, Germany, he developed new chiral stationary phases for chromatographic enantioseparations. In 1995 he joined Merck, and since then he has been responsible for research and development in the area of preparative chromatography, including the development of new stationary phases, new separation processes, and the implementation of simulated moving bed technology at Merck. In his current position, he is responsible for the development of novel stationary phases for preparative chromatography.

Andreas Seidel‐Morgenstern is director at the Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany, and holds the chair in Chemical Process Engineering at the Otto von Guericke University, Magdeburg, Germany. He received his PhD in 1987 at the Institute of Physical Chemistry of the Academy of Sciences in Berlin. In 1991 and 1992 he worked as a postdoctoral fellow at the University of Tennessee, Knoxville, TN. In 1994 he finished his habilitation at the Technical University in Berlin. His current research is focused on developing chromatographic and crystallization based separation and new reactor concepts.

List of Abbreviations

ACD

at‐column dilution

AAV

adeno-associated virus

ADI

active pharmaceutical ingredient

AIEX

anion exchanger

ARX

autoregressive exogenous

ATEX

explosion proof (French: ATmospheres EXplosibles)

BET

Brunauer–Emmett–Teller

BJH

Barrett–Joyner–Halenda

BR

chromatographic batch reactor

BV

bed volume

CACR

continuous annular chromatographic reactor

CD

circular dichroism (detectors)

CEC

capillary electrochromatography

CFD

computational fluid dynamics

cGMP

current good manufacturing practice

CIEX

cation exchanger

CIP

cleaning in place

CLP

column liquid chromatography

CLRC

closed‐loop recycling chromatography

COGS

cost of goods sold

CPG

controlled pore glass

CSEP

®

chromatographic separator

CSF

circle suspension flow

CSP

chiral stationary phase

CST

continuous stirred tank

CTA

cellulose triacetate

CTB

cellulose tribenzoate

CV

column volume

DAC

dynamic axial compression

DAD

diode array detector

DMF

dimethylformamide

DMSO

dimethyl sulfoxide

DSC

distributed control system

DTA

differential thermal analysis

DVB

divinylbenzene

EC

elution consumption

ECP

elution by characteristic points

EDM

equilibrium dispersive model

EMG

exponential modified Gauss (function)

FACP

frontal analysis by characteristic points

FAT

factory acceptance test

FDA

food and drug administration

FDM

finite difference methods

FF‐SMB

fractionation and feedback SMB

FFT

forward flow test

FT

flow through

GC

gas chromatography

GMP

good manufacturing practice

GRM

general rate model

HCP

healthcare provider

HETP

height of an equivalent theoretical plate

HFCS

high‐fructose corn syrup

HIC

hydrophobic interaction chromatography

H‐NMR

hydrogen nuclear magnetic resonance (spectroscopy)

HPLC

high‐performance liquid chromatography

HPW

highly purified water

IAST

ideal adsorbed solution theory

ICH

International Guidelines for Harmonization

IEX

ion exchange

IMAC

immobilized metal affinity chromatography

IR

infrared

ISEC

inverse size‐exclusion chromatography

ISEP

®

ion‐exchange separation

iSMB

improved/intermittent simulated moving bed

LC

liquid chromatography

LGE

linear gradient elution

LHS

liquid‐handling station

LOD

limit of detection

LOQ

limit of quantification

LPLC

low‐pressure liquid chromatography

LSB

large‐scale biotech project

mAb

monoclonal antibody

MCC

multicolumn capture chromatography

MCSGP

multicolumn countercurrent solvent gradient purification

MD

molecular dynamics

MPC

model predictive control

MS

mass spectroscopy

MW

molecular weight

NMPC

nonlinear model predictive control

NMR

nuclear magnetic resonance (spectroscopy)

NN

neural network

NP

normal phase

NPLC

normal phase liquid chromatography

NSGA

nondominating sorting generic algorithm

OC

orthogonal collocation

OCFE

orthogonal collocation on finite elements

ODE

ordinary differential equation

PAT

process analytical technology

PCC

periodic countercurrent chromatography

PDE

partial differential equation

PDT

pressure decay test

PEEK

poly(etheretherketone)

PES

poly‐ether sulfone

PLC

programmable logic controller

PMP

polymethylpentene

PSD

particle size distribution

QC

quality control

R&D

research and development

RI

refractive index

RMPC

repetitive model predictive control

RP

reversed phase

SAT

site acceptance test

S/N

signal‐to‐noise ratio

SEC

size‐exclusion chromatography

SEM

scanning electron microscopy

SFC

supercritical fluid chromatography

SIP

sanitization in place

SIP

steaming in place

SMCC

sequential multicolumn chromatography

SMB

simulated moving bed

SMBR

simulated moving bed reactor

SOP

standard operation procedure

SQP

sequential quadratic programming

SSRC

steady‐state recycling chromatography

St‐DVB

styrene‐divinylbenzene

TDM

transport dispersive model

TEM

transmission electron microscopy

TEOS

tetraethoxysilane

TFA

trifluoroacetic acid

TG/DTA

thermogravimetric/differential thermal analysis

THF

tetrahydrofuran

TLC

thin‐layer chromatography

TMB

true moving bed process

TMBR

true moving bed reactor

TPX™

transparent polymethylpentene

UPLC

ultrahigh‐performance liquid chromatography

URS

user Requirements Specification

USP

United States Pharmacopeia

UV

ultraviolet

VSP

volume‐specific productivity

WFI

water for injection

WIT

water intrusion test

Notation

Symbols

Symbol

Description

Units

a

Coefficient of the Langmuir isotherm

cm

3

 g

−1

a

s

Specific surface area

cm

2

 g

−1

A

Area

cm

2

A

c

Cross section of the column

cm

2

A

Coefficient in the van Deemter equation

cm

A

s

Surface area of the adsorbent

cm

2

ASP

Cross section‐specific productivity

g cm

−2

 s

−1

b

Coefficient of the Langmuir isotherm

cm

3

 g

−1

B

Column permeability

m

2

B

Coefficient in the van Deemter equation

cm

2

 s

−1

c

Concentration in the mobile phase

g cm

−3

c

p

Concentration of the solute inside the particle pores

g cm

−3

C

Annual costs

€

C

Coefficient in the van Deemter equation

s

C

DL

Dimensionless concentration in the liquid phase

—

C

p,DL

Dimensionless concentration of the solute inside the particle pores

—

C

spec

Specific costs

€ g

−1

D

c

Diameter of the column

cm

d

p

Average diameter of the particle

cm

d

pore

Average diameter of the pores

cm

D

an

Angular dispersion coefficient

cm

2

 s

−1

D

app

Apparent dispersion coefficient

cm

2

 s

−1

D

app,pore

Apparent dispersion coefficient inside the pores

cm

2

 s

−1

D

ax

Axial dispersion coefficient

cm

2

 s

−1

D

m

Molecular diffusion coefficient

cm

2

 s

−1

D

pore

Diffusion coefficient inside the pores

cm

2

 s

−1

D

solid

Diffusion coefficient on the particle surface

cm

2

 s

−1

EC

Eluent consumption

cm

2

 s

−1

fi

Specific prices

€ l

−1

, € g

−1

f

Fugacity

—

h

Reduced plate height

—

R

f

Retardation factor

—

Δ

h

vap

Heat of vaporization

kJ mol

−1

H

Henry coefficient

—

H

p

Prediction horizon

—

H

r

Control horizon

—

HETP

Height of an equivalent theoretical plate

cm

k

ads

Adsorption rate constant

cm

3

 g

−1

 s

−1

k

des

Desorption rate constant

cm

3

 g

−1

 s

−1

k

eff

Effective mass transfer coefficient

cm

2

 s

−1

K

eq

Equilibrium constant

Miscellaneous

K

EQ

Dimensionless equilibrium coefficient

—

k

film

Boundary or film mass transfer coefficient

cm s

−1

k

′

Retention factor

—

Modified retention factor

—

k

0

Pressure drop coefficient

—

k

reac

Rate constant

Miscellaneous

LF

Loading factor

—

L

c

Length of the column

cm

Mass flow

g s

−1

m

Mass

g

m

j

Dimensionless mass flow rate in section

j

—

m

s

Total mass

g

n

T

Pore connectivity

—

N

Column efficiency, number of plates

—

N

col

Number of columns

—

N

comp

Number of components

—

N

p

Number of particles per volume element

—

Δ

p

Pressure drop

Pa

Pe

Péclet number

—

Pr

Productivity

g cm

−3

h

−1

P

s

Selectivity point

—

Pu

Purity

%

q

Solid phase loading

g cm

−3

q

*

Total loading

g cm

−3

Averaged particle loading

g cm

−3

q

sat

Saturation capacity of the stationary phase

g cm

−3

Q

DL

Dimensionless concentration in the stationary phase

—

r

Radial coordinate

cm

r

Reaction rate

Miscellaneous

r

p

Particle radius

cm

R

f

Retardation factor

—

R

s

Resolution

—

Re

Reynolds number

—

S

BET

Specific surface area

m

2

 g

−1

Sc

Schmidt number

—

Sh

Sherwood number

—

St

Stanton number

—

t

Time

s

t

0

Dead time of the column

s

t

0,e

Retention time of a non‐retained component

s

(related to external porosity)

t

0,

t

Retention time of a non‐retained component

s

(related to total porosity)

t

cycle

Cycle time

s

t

g

Gradient time

s

t

inj

Injection time

s

t

life

Lifetime of adsorbent

h

t

plant

Extra‐column dead time of the plant

s

t

R

Retention time

s

t

R,net

Net retention time

s

t

shift

Switching time of the SMB plant

s

t

tank

Dead time of tanks

s

t

pipe

Dead time of pipes

s

t

Rmax

Maximum of retention time

s

t

Rmean

Mean retention time, first statistical moment

s

t

Rshock

Retention time of a shock front

s

T

Temperature

K

T

Degree of peak asymmetry

—

u

0

Velocity in the empty column

cm s

−1

u

int,e

Interstitial velocity in the external fluid volume of the packed column

cm s

−1

u

hypo

int,t

Hypothetical effective velocity

cm s

−1

u

m

Effective velocity (total mobile phase)

cm s

−1

v

sp

Specific pore volume

cm

3

 g

−1

V

Volume

cm

3

Volume flow

cm

3

 s

−1

V

ads

Volume of the stationary phase within a column

cm

3

V

c

Total volume of a packed column

cm

3

V

i

Molar volume

cm

3

 mol

−1

V

int

Interstitial volume

cm

3

V

m

Overall fluid volume

cm

3

V

pore

Volume of the pore system

cm

3

V

solid

Volume of the solid material

cm

3

VSP

Volume‐specific productivity

g cm

−3

 s

−1

w

i

Velocity of propagation

cm s

−1

x

Coordinate

cm

x

State of the plant

—

x

Fraction

—

X

Conversion

%

X

cat

Fraction of catalyst of the fixed bed

—

Y

Yield

%

Z

Dimensionless distance

—

Greek Symbols

Symbol

Description

Units

α

Selectivity

—

α

exp

Ligand density

μmol m

−2

β

Modified dimensionless mass flow rate

—

γ

Obstruction factor for diffusion or external tortuosity

—

Γ

Objective function

—

ε

Void fraction

—

ε

0

Solvent strength parameter

—

ε

e

External (interstitial) porosity

—

ε

P

Porosity of the solid phase

—

ε

t

Total column porosity

—

η

Dynamic viscosity

mPa s

Θ

Angle of rotation

°

Λ

Total ion‐exchange capacity

mM

λ

Irregularity in the packing

—

μ

Chemical potential

J mol

−1

μ

k

k

th

moment

—

v

Kinematic viscosity

cm

2

 s

−1

v

Stoichiometric coefficient

—

π

Spreading pressure

Pa

ϱ

Density

g cm

−3

σ

t

Standard deviation

—

σ

Steric shielding parameter

—

τ

Dimensionless time

—

φ

Running variable

—

ϕ

Bed voidage

ψ

Friction number

—

ψ

reac/des

Rate of the adsorption and desorption steps

g cm

−3

 s

−1

ω

j

Characteristic coefficient in equilibrium theory

—

ω

Rotation velocity

°s

−1

Θ

cyc

Cycle time

s

Subscripts

Symbol

Description

1, 2

Component 1/component 2

I, II, III, IV

Section of the SMB or TMB process

acc

Accumulation

ads

Adsorbent

c

Column

cat

Catalyst

conv

Convection

crude

Crude loss

des

Desorbent

diff

Diffusion

disp

Dispersion

DL

Dimensionless

eff

Effective

el

Eluent

exp

Experimental

ext

Extract

feed

Feed

het

Heterogeneous

hom

Homogeneous

i

Component

i

in

Inlet

inj

Injection

j

Section

j

of the TMB or SMB process

l

Liquid

lin

Linear

max

Maximum

min

Minimum

mob

Mobile phase

mt

Mass transfer

opt

Optimal

out

Outlet

p

Particle

pore

Pore

pipe

Pipe within HPLC plant

plant

Plant without column

prod

Product

raf

Raffinate

reac

Reaction

rec

Recycles

s

solid

sat

Saturation

sec

Section

shock

Shock front

SMB

Simulated moving bed process

solid

Solid adsorbent

spec

Specific

stat

Stationary phase

tank

Tank within HPLC plant

theo

Theoretical

TMB

True moving bed process

Definition of Dimensionless Parameters

Péclet number

Convection to dispersion (column)

Péclet number of the particle

Convection to dispersion (particle)

Péclet number of the plant

Convection to dispersion (plant without column)

Reynolds number

Inertial force to viscous force

Schmidt number

Kinetic viscosity to diffusivity

Sherwood number

Mass diffusivity to molecular diffusivity

Stanton number (modified)

Mass transfer to convection

1Introduction

Henner Schmidt‐Traub 1, and Reinhard Ditz2

1TU Dortmund Fakultät für Bio‐ und Chemieingenieurwesen, Lehrstuhl für Anlagen‐ und Prozesstechnik, Emil‐Figge‐Str. 70, 44227 Dortmund, Germany

2Bristenstrasse 16, CH 8048 Zürich, Switzerland

1.1 Chromatography, Development, and Future Trends

Ink dripping on a blotting paper thrills children when they realize the rainbow of colors spreading out. It is chromatography, an effect first coined by Tswett (1906) in 1903 for the isolation of chlorophyll constituents. Now, more than a hundred years later, children still enjoy chromatographic effects. Chromatography has developed into an important method for chemical analysis and production of high purity product in micro‐ and macroscale, and today pharmaceuticals are unthinkable without chromatography.

Liquid chromatography (LC) was first applied as a purification tool and has therefore been used as a preparative method. It is the only technique that enables to separate and identify both femtomoles of compounds out of complex matrices in life sciences and allows the purification and isolation of synthetic industrial products in the ton range. Figure 1.1 characterizes the development of chromatography and its future trends.

In the 1960s, analytical high‐performance liquid chromatography (HPLC) emerged when stationary phases of high selectivity became available. At the same time, an essential technology push for preparative chromatography was created by the search of engineers for more effective purification technologies. The principle to enhance mass transfer by countercurrent flow in combination with high selectivity of HPLC significantly increased the performance of preparative chromatography in terms of productivity, eluent consumption, yield, and concentration. The first process of this kind was the simulated moving bed (SMB) chromatography for large‐scale separation in the petrochemical area and in food processing (Broughton and Gerhold 1961).

These improvements were closely coupled to the development of adsorbents of high selectivity. In the 1980s, highly selective adsorbents were developed for the resolution of racemates into their enantiomers. The availability of enantioselective packing in bulk quantities enabled the production of pure enantiomers by the SMB technology in the multi‐ton range. Productivities larger than 10 kg of pure product per kilogram of packing per day were achieved in the following years.

Figure 1.1 Development of chromatography.

Source: Unger et al. (2010). Reproduced and modified with permission of John Wiley and Sons.

In the 1990s, the SMB process concept was adapted and downsized for the production of pharmaceuticals. The development of new processes was necessarily accompanied by theoretical modeling and process simulation, which are a prerequisite for better understanding of transport phenomena and process optimization.

While preparative as well as analytical LC were heavily relying on equipment and engineering and on the physical aspects of their tools for advancement in their fields, the bioseparation domain was built around a different key aspect, namely, selective materials that allowed the processing of biopolymers, for example, recombinant proteins under nondegrading conditions, thus maintaining bioactivity. Much less focus in this area was on process engineering aspects, leading to the interesting phenomenon, that large‐scale production concepts for proteins were designed around the mechanical instability of soft gels (Janson and Jönsson 2010).

The separation of proteins and other biopolymers has some distinctly different features compared with the separation of low molecular weight (MW) molecules from synthetic routes or from natural sources. Biopolymers have an MW ranging from several thousand to several million. They are charged and characterized by their isoelectric point. More importantly, they have