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Shi C, Chen XJ, Zhong XZ, Yang Y, Lin DQ, Chen R. Realization of digital twin for dynamic control toward sample variation of ion exchange chromatography in antibody separation. Biotechnol Bioeng 2024; 121:1702-1715. [PMID: 38230585 DOI: 10.1002/bit.28660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 12/26/2023] [Accepted: 01/05/2024] [Indexed: 01/18/2024]
Abstract
Digital twin (DT) is a virtual and digital representation of physical objects or processes. In this paper, this concept is applied to dynamic control of the collection window in the ion exchange chromatography (IEC) toward sample variations. A possible structure of a feedforward model-based control DT system was proposed. Initially, a precise IEC mechanistic model was established through experiments, model fitting, and validation. The average root mean square error (RMSE) of fitting and validation was 8.1% and 7.4%, respectively. Then a model-based gradient optimization was performed, resulting in a 70.0% yield with a remarkable 11.2% increase. Subsequently, the DT was established by systematically integrating the model, chromatography system, online high-performance liquid chromatography, and a server computer. The DT was validated under varying load conditions. The results demonstrated that the DT could offer an accurate control with acidic variants proportion and yield difference of less than 2% compared to the offline analysis. The embedding mechanistic model also showed a positive predictive performance with an average RMSE of 11.7% during the DT test under >10% sample variation. Practical scenario tests indicated that tightening the control target could further enhance the DT robustness, achieving over 98% success rate with an average yield of 72.7%. The results demonstrated that the constructed DT could accurately mimic real-world situations and perform an automated and flexible pooling in IEC. Additionally, a detailed methodology for applying DT was summarized.
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Affiliation(s)
- Ce Shi
- Process Development Downstream, Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
| | - Xu-Jun Chen
- Process Development Downstream, Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
| | - Xue-Zhao Zhong
- Process Development Downstream, Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
| | - Yan Yang
- Process Development Downstream, Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
| | - Dong-Qiang Lin
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
| | - Ran Chen
- Process Development Downstream, Shanghai Engineering Research Center of Anti-tumor Biological Drugs, Shanghai Henlius Biotech, Inc., Shanghai, China
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2
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Altern SH, Kocot AJ, LeBarre JP, Boi C, Phillips MW, Roush DJ, Menegatti S, Cramer SM. Mechanistic model-based characterization of size-exclusion-mixed-mode resins for removal of monoclonal antibody fragments. J Chromatogr A 2024; 1718:464717. [PMID: 38354506 DOI: 10.1016/j.chroma.2024.464717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Revised: 01/22/2024] [Accepted: 02/03/2024] [Indexed: 02/16/2024]
Abstract
Although antibody fragments are a critical impurity to remove from process streams, few platformable purification techniques have been developed to this end. In this work, a novel size-exclusion-mixed-mode (SEMM) resin was characterized with respect to its efficacy in mAb fragment removal. Inverse size-exclusion chromatography showed that the silica-based resin had a narrow pore size distribution and a median pore radius of roughly 6.2 nm. Model-based characterization was carried out with Chromatography Analysis and Design Toolkit (CADET), using the general rate model and the multicomponent Langmuir isotherm. Model parameters were obtained from fitting breakthrough curves, performed at multiple residence times, for a mixture of mAb, aggregates, and an array of fragments (varying in size). Accurate fits were obtained to the frontal chromatographic data across a range of residence times. Model validation was then performed with a scaled-up column, altering residence time and feed composition from the calibration run. Accurate predictions were obtained, thereby illustrating the model's interpolative and extrapolative capabilities. Additionally, the SEMM resin achieved 90% mAb yield, 37% aggregate removal, 29% [Formula: see text] removal, 54% Fab/Fc removal, 100% Fc fragments removal, and a productivity of 72.3 g mAbL×h. Model predictions for these statistics were all within 5%. Simulated batch uptake experiments showed that resin penetration depth was directly related to protein size, with the exception of the aggregate species, and that separation was governed by differential pore diffusion rates. Additional simulations were performed to characterize the dependence of fragment removal on column dimension, load density, and feed composition. Fragment removal was found to be highly dependent on column load density, where optimal purification was achieved below 100 mg protein/mL column. Furthermore, fragment removal was dependent on column volume (constant load mass), but agnostic to whether column length or diameter was changed. Lastly, the dependence on feed composition was shown to be complex. While fragment removal was inversely related to fragment mass fraction in the feed, the extent depended on fragment size. Overall, the results from this study illustrated the efficacy of the SEMM resin in fragment and aggregate removal and elucidated relationships with key operational parameters through model-based characterization.
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Affiliation(s)
- Scott H Altern
- Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA; Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, USA
| | - Andrew J Kocot
- Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA; Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, USA
| | - Jacob P LeBarre
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, USA
| | - Cristiana Boi
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, USA; Biomanufacturing Training and Education Center (BTEC), North Carolina State University, Raleigh, NC, USA; Department of Civil, Chemical, Environmental, and Materials Engineering, University of Bologna, Bologna, Italy
| | - Michael W Phillips
- Downstream Research and Development, EMD Millipore Corporation, Burlington, MA, USA
| | - David J Roush
- Process Research and Development, Merck & Co., Inc., Rahway, NJ, USA
| | - Stefano Menegatti
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, USA; Biomanufacturing Training and Education Center (BTEC), North Carolina State University, Raleigh, NC, USA; North Carolina Viral Vector Initiative in Research and Learning (NC-VVIRAL), North Carolina State University, Raleigh, NC, USA
| | - Steven M Cramer
- Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA; Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, USA.
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3
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Qu Y, Baker I, Black J, Fabri L, Gras SL, Lenhoff AM, Kentish SE. Application of mechanistic modelling in membrane and fiber chromatography for purification of biotherapeutics - A review. J Chromatogr A 2024; 1716:464588. [PMID: 38217959 DOI: 10.1016/j.chroma.2023.464588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 12/03/2023] [Accepted: 12/17/2023] [Indexed: 01/15/2024]
Abstract
Mechanistic modelling is a simulation tool which has been effectively applied in downstream bioprocessing to model resin chromatography. Membrane and fiber chromatography are newer approaches that offer higher rates of mass transfer and consequently higher flow rates and reduced processing times. This review describes the key considerations in the development of mechanistic models for these unit operations. Mass transfer is less complex than in resin columns, but internal housing volumes can make modelling difficult, particularly for laboratory-scale devices. Flow paths are often non-linear and the dead volume is often a larger fraction of the overall volume, which may require more complex hydrodynamic models to capture residence time distributions accurately. In this respect, the combination of computational fluid dynamics with appropriate protein binding models is emerging as an ideal approach.
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Affiliation(s)
- Yiran Qu
- Department of Chemical Engineering, University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Irene Baker
- Cell Culture and Purification Development, CSL Innovation, Melbourne, Victoria 3000, Australia
| | - Jamie Black
- Cell Culture and Purification Development, CSL Innovation, Melbourne, Victoria 3000, Australia
| | - Louis Fabri
- Cell Culture and Purification Development, CSL Innovation, Melbourne, Victoria 3000, Australia
| | - Sally L Gras
- Department of Chemical Engineering, University of Melbourne, Melbourne, Victoria 3010, Australia; Bio21 Institute of Molecular Science and Biotechnology, Melbourne, Victoria 3052, Australia
| | - Abraham M Lenhoff
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, USA
| | - Sandra E Kentish
- Department of Chemical Engineering, University of Melbourne, Melbourne, Victoria 3010, Australia.
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4
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Yang YX, Chen YC, Yao SJ, Lin DQ. Parameter-by-parameter estimation method for adsorption isotherm in hydrophobic interaction chromatography. J Chromatogr A 2024; 1716:464638. [PMID: 38219627 DOI: 10.1016/j.chroma.2024.464638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 01/06/2024] [Accepted: 01/08/2024] [Indexed: 01/16/2024]
Abstract
Hydrophobic interaction chromatography (HIC) is used as a critical polishing step in the downstream processing of biopharmaceuticals. Normally the process development of HIC is a cumbersome and time-consuming task, and the mechanical models can provide a powerful tool to characterize the process, assist process design and accelerate process development. However, the current estimation of model parameters relies on the inverse method, which lacks an efficient and logical parameter estimation strategy. In this study, a parameter-by-parameter (PbP) method based on the theoretical derivation and simplifying assumptions was proposed to estimate the Mollerup isotherm parameters for HIC. The method involves three key steps: (1) linear regression (LR) to estimate the salt-protein interaction parameter and the equilibrium constant; (2) linear approximation (LA) to estimate the stoichiometric parameter and the maximum binding capacity; and (3) inverse method to estimate the protein-protein interaction parameter and the kinetic coefficient. The results indicated that the LR step should be used for dilution condition (loading factor below 5%), while the LA step should be conducted when the isotherm is in the transition or nonlinear regions. Six numerical experiments were conducted to implement the PbP method. The results demonstrated that the PbP method developed allows for the systematic estimation of HIC parameters one-by-one, effectively reducing the number of parameters required for inverse method estimation from six to two. This helps prevent non-identifiability of structural parameters. The feasibility of the PbP-HIC method was further validated by real-world experiments. Moreover, the PbP method enhances the mechanistic understanding of adsorption behavior of HIC and shows a promising application to other stoichiometric displacement model-derived isotherms.
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Affiliation(s)
- Yu-Xiang Yang
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education, Zhejiang Key Laboratory of Smart Biomaterials, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310058, China
| | - Yu-Cheng Chen
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education, Zhejiang Key Laboratory of Smart Biomaterials, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310058, China
| | - Shan-Jing Yao
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education, Zhejiang Key Laboratory of Smart Biomaterials, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310058, China
| | - Dong-Qiang Lin
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education, Zhejiang Key Laboratory of Smart Biomaterials, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310058, China.
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5
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Koch J, Scheps D, Gunne M, Boscheinen O, Frech C. Mechanistic modeling of cation exchange chromatography scale-up considering packing inhomogeneities. J Sep Sci 2023; 46:e2300031. [PMID: 36846902 DOI: 10.1002/jssc.202300031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 02/24/2023] [Accepted: 02/25/2023] [Indexed: 03/01/2023]
Abstract
In process development and characterization, the scale-up of chromatographic steps is a crucial part and brings a number of challenges. Usually, scale-down models are used to represent the process step, and constant column properties are assumed. The scaling is then typically based on the concept of linear scale-up. In this work, a mechanistic model describing an anti-Langmuirian to Langmuirian elution behavior of a polypeptide, calibrated with a pre-packed 1 ml column, is applied to demonstrate the scalability to larger column volumes up to 28.2 ml. Using individual column parameters for each column size, scaling to similar eluting salt concentrations, peak heights, and shapes is experimentally demonstrated by considering the model's relationship between the normalized gradient slope and the eluting salt concentration. Further scale-up simulations show improved model predictions when radial inhomogeneities in packing quality are considered.
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Affiliation(s)
- Jonas Koch
- Department of Biotechnology, Institute for Biochemistry, University of Applied Sciences, Mannheim, Germany
| | - Daniel Scheps
- CMC Microbial Platform, Sanofi-Aventis Deutschland GmbH, Frankfurt am Main, Germany
| | - Matthias Gunne
- IA MSAT M&I DS, Sanofi-Aventis Deutschland GmbH, Frankfurt am Main, Germany
| | - Oliver Boscheinen
- CMC Microbial Platform, Sanofi-Aventis Deutschland GmbH, Frankfurt am Main, Germany
| | - Christian Frech
- Department of Biotechnology, Institute for Biochemistry, University of Applied Sciences, Mannheim, Germany
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6
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Hess R, Yun D, Saleh D, Briskot T, Grosch JH, Wang G, Schwab T, Hubbuch J. Standardized method for mechanistic modeling of multimodal anion exchange chromatography in flow through operation. J Chromatogr A 2023; 1690:463789. [PMID: 36649667 DOI: 10.1016/j.chroma.2023.463789] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 12/14/2022] [Accepted: 01/08/2023] [Indexed: 01/12/2023]
Abstract
Multimodal chromatography offers an increased selectivity compared to unimodal chromatographic methods and is often employed for challenging separation tasks in industrial downstream processing (DSP). Unfortunately, the implementation of multimodal polishing into a generic downstream platform can be hampered by non-robust platform conditions leading to a time and cost intensive process development. Mechanistic modeling can assist experimental process development but readily applicable and easy to calibrate multimodal chromatography models are lacking. In this work, we present a mechanistic modeling aided approach that paves the way for an accelerated development of anionic mixed-mode chromatography (MMC) for biopharmaceutical purification. A modified multimodal isotherm model was calibrated using only three chromatographic experiments and was employed in the retention prediction of four antibody formats including a Fab, a bispecific, as well as an IgG1 and IgG4 antibody subtype at pH 5.0 and 6.0. The chromatographic experiments were conducted using the anionic mixed-mode resin Capto adhere at industrial relevant process conditions to enable flow through purification. An existing multimodal isotherm model was reduced to hydrophobic interactions in the linear range of the adsorption isotherm and successfully employed in the simulation of six chromatographic experiments per molecule in concert with the transport dispersive model (TDM). The model reduction to only three parameters did prevent structural parameter non-identifiability and enabled an analytical isotherm parameter determination that was further refined by incorporation of size exclusion effects of the selected multimodal resin. During the model calibration, three linear salt gradient elution experiments were performed for each molecule followed by an isotherm parameter uncertainty assessment. Lastly, each model was validated with a set of step and isocratic elution experiments. This standardized modeling approach facilitates the implementation of multimodal chromatography as a key unit operation for the biopharmaceutical downstream platform, while increasing the mechanistic insight to the multimodal adsorption behavior of complex biologics.
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Affiliation(s)
- Rudger Hess
- Karlsruhe Institute of Technology (KIT), Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe, Germany; DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - Doil Yun
- DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - David Saleh
- DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - Till Briskot
- DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - Jan-Hendrik Grosch
- DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - Gang Wang
- DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - Thomas Schwab
- DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - Jürgen Hubbuch
- Karlsruhe Institute of Technology (KIT), Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe, Germany.
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7
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Chen YC, Yao SJ, Lin DQ. Parameter-by-parameter method for steric mass action model of ion exchange chromatography: Simplified estimation for steric shielding factor. J Chromatogr A 2023; 1687:463655. [PMID: 36442298 DOI: 10.1016/j.chroma.2022.463655] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 11/16/2022] [Accepted: 11/16/2022] [Indexed: 11/19/2022]
Abstract
Mechanistic models play a crucial role in the process development and optimization of ion-exchange chromatography (IEC). Recent researches in steric mass action (SMA) model have heightened the need for better estimation of nonlinear parameter, steric shielding factor σ. In this work, a straightforward approach combination of simplified linear approximation (SLA) and inverse method (IM) was proposed to initialize and further determine σ, respectively. An existed, unique, and positive σ can be derived from SLA. Compared with linear approximation (LA) developed in our previous study, σ of the multi-component system can be calculated easily without solving the complex system of linear equations, leading to a time complexity reduction from O(n3) to O(n). The proposed method was verified first in numerical experiments about the separation of three charge variants. The calculated σ was more reasonable than that of LA, and the error of elution profiles with the parameters estimated by SLA+IM was only one-sixth of that by LA in numerical experiments. Moreover, the error accumulation effect could also be reduced. The proposed method was further confirmed in real-world experiments about the separation of monomer-dimer mixtures of monoclonal antibody. The results gave a lower error and better physical understanding compared to LA. In conclusion, SLA+IM developed in the present work provides a novel and straightforward way to determine σ. This simplification would help to save the effort of calibration experiments and accelerate the process development for the multi-component IEC separation.
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Affiliation(s)
- Yu-Cheng Chen
- Zhejiang Key Laboratory of Smart Biomaterials, Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China
| | - Shan-Jing Yao
- Zhejiang Key Laboratory of Smart Biomaterials, Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China
| | - Dong-Qiang Lin
- Zhejiang Key Laboratory of Smart Biomaterials, Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China.
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8
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Sivanathan GT, Mallubhotla H, Suggala SV, Tholu MS. Separation of closely related monoclonal antibody charge variant impurities using poly(ethylenimine)-grafted cation-exchange chromatography resin. 3 Biotech 2022; 12:293. [PMID: 36276450 PMCID: PMC9515282 DOI: 10.1007/s13205-022-03350-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 09/04/2022] [Indexed: 11/28/2022] Open
Abstract
The removal of protein charge variants due to complex chemical and enzymatic modifications like glycosylation, fragmentation and deamidation presents a significant challenge in the purification of monoclonal antibodies (mAb) and complicates downstream processing. These protein modifications occur either in vivo or during fermentation and downstream processing. The presence of charge variants can lead to diminished biological activity, differences in pharmacokinetics, pharmacodynamics, stability and efficacy. Therefore, these different product variants should be appropriately controlled for the consistency of product quality and to ensure patient safety. This investigation focuses on the development of a chromatography step for the removal of the charge variants from a recombinant single-chain variable antibody fragment (scFv-Fc-Ab). Poly(ethyleneimine)-grafted cation-exchange resins (Poly CSX and Poly ABX) were evaluated and compared to traditional macroporous cation-exchange and tentacle cation-exchange resins. Linear salt gradient experiments were conducted to study the separation efficiency of scFv-Fc-Ab variants using different resins. A classical thermodynamic model was used to develop a mechanistic understanding of the differences in charge variant retention behaviour of different resins. High selectivity in separation of scFv-Fc-Ab charge variants is obtained in the Poly CSX resin.
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Affiliation(s)
- Ganesh T. Sivanathan
- Department of Chemical Engineering, JNTUA, Ananthapuramu, Andhra Pradesh 515002 India
- Biopharmaceutical Development, Syngene International Ltd., Bangalore, 560099 India
| | - Hanuman Mallubhotla
- Biopharmaceutical Development, Syngene International Ltd., Bangalore, 560099 India
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Bernau CR, Knödler M, Emonts J, Jäpel RC, Buyel JF. The use of predictive models to develop chromatography-based purification processes. Front Bioeng Biotechnol 2022; 10:1009102. [PMID: 36312533 PMCID: PMC9605695 DOI: 10.3389/fbioe.2022.1009102] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 09/23/2022] [Indexed: 11/13/2022] Open
Abstract
Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.
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Affiliation(s)
- C. R. Bernau
- Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Aachen, Germany
| | - M. Knödler
- Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Aachen, Germany
- Institute for Molecular Biotechnology, RWTH Aachen University, Aachen, Germany
| | - J. Emonts
- Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Aachen, Germany
| | - R. C. Jäpel
- Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Aachen, Germany
- Institute for Molecular Biotechnology, RWTH Aachen University, Aachen, Germany
| | - J. F. Buyel
- Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Aachen, Germany
- Institute for Molecular Biotechnology, RWTH Aachen University, Aachen, Germany
- University of Natural Resources and Life Sciences, Vienna (BOKU), Department of Biotechnology (DBT), Institute of Bioprocess Science and Engineering (IBSE), Vienna, Austria
- *Correspondence: J. F. Buyel,
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10
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Shekhawat LK, Tiwari A, Yamamoto S, Rathore AS. An accelerated approach for mechanistic model based prediction of linear gradient elution ion-exchange chromatography of proteins. J Chromatogr A 2022; 1680:463423. [PMID: 36001907 DOI: 10.1016/j.chroma.2022.463423] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 08/12/2022] [Accepted: 08/14/2022] [Indexed: 11/30/2022]
Abstract
With growing demands for therapeutic monoclonal antibodies, in silico downstream process development based on mechanistic modeling of chromatography separation process is being increasingly used for process optimization and process characterization. Application of mechanistic modeling in biopharmaceutical industry has been sparse due to the significant investment of time and resources that are required for performing model calibration. Mechanistic modeling of the chromatography process involves a large number of mass transport and binding parameters and their initial input values are required for simulations. These input values of column parameters can be easily obtained either from experiments or from empirical correlations available in literature. On the other hand, obtaining the model input valves for binding kinetic parameters is usually a cumbersome process as it involves performing batch experiments which are not only tedious but also require significant quantities of purely isolated main product and its related impurities, which is challenging as the product related impurities are typically present in smaller quantities and hence are difficult to obtain as pure species. In the present work, a mechanistic model that is based on the general rate model coupled with extended Langmuir binding model has been used for prediction of linear gradient elution peaks of monoclonal antibody on cation exchanger chromatography. The present work describes an accelerated approach for obtaining the input values for binding kinetic parameters in the extended Langmuir binding model from the two Yamamoto coefficient A and B values obtained by Yamamoto method directly from the model calibration linear gradient elution runs of different gradient slopes and at low to moderate protein loadings. The equations that can relate the two coefficients to the extended Langmuir model equation binding kinetic parameters were derived. Therefore, once A and B are determined, the binding kinetic parameter values were determined straightforward, thereby avoiding the problem of multiple solutions for the model parameters. The estimated binding parameters were successfully validated from isocratic elution experiments performed at low loading. What we demonstrate is that the proposed approach allows us to estimate binding kinetic parameters in a significantly more efficient and accelerated manner than presently used approaches, thereby accelerating development and implementation of mechanistic modeling for process chromatography.
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Affiliation(s)
- Lalita Kanwar Shekhawat
- Department of Chemical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi, India; Cytiva Sweden AB Björkgatan 30, 753 23 Uppsala
| | - Anamika Tiwari
- Biomedical Engineering Center, Yamaguchi University, Tokiwadai, Ube, 755-8611, Japan; Manufacturing Technology Association of Biologics, 2-6-16, Shinkawa, Tokyo, 104-0033, Japan
| | - Shuichi Yamamoto
- Biomedical Engineering Center, Yamaguchi University, Tokiwadai, Ube, 755-8611, Japan; Manufacturing Technology Association of Biologics, 2-6-16, Shinkawa, Tokyo, 104-0033, Japan.
| | - Anurag S Rathore
- Department of Chemical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi, India.
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11
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Parameter-by-parameter method for steric mass action model of ion exchange chromatography: Theoretical considerations and experimental verification. J Chromatogr A 2022; 1680:463418. [PMID: 36001908 DOI: 10.1016/j.chroma.2022.463418] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 08/08/2022] [Accepted: 08/10/2022] [Indexed: 12/30/2022]
Abstract
Ion exchange chromatography (IEC) is one of the most widely-used techniques for protein separation and has been characterized by mechanistic models. However, the time-consuming and cumbersome model calibration hinders the application of mechanistic models for process development. A new methodology called "parameter-by-parameter method (PbP)" was proposed with mechanistic derivations of the steric mass action (SMA) model of IEC. The protocol includes four steps: (1) first linear regression (LR1) for characteristic charge; (2) second linear regression (LR2) for equilibrium coefficient; (3) linear approximation (LA) for shielding factor; (4) inverse method (IM) for kinetic coefficient. Four SMA parameters could be one-by-one determined in sequence, reducing the number of unknown parameters per species from four to one, and predicting almost consistent retention. Numerical single-component experiments were investigated firstly, and the PbP method showed excellent agreement between experiments and simulations. The effects of loadings on the PbP and Yamamoto methods were compared. It was found that the PbP method had higher accuracy and robustness than the Yamamoto method. Moreover, a five-experiment strategy was suggested to implement the PbP method, which is straightforward to reduce the cost of calibration experiments. Finally, a real-world multi-component separation was challenged and further confirmed the feasibility of the PbP method. In general, the proposed method can not only reliably estimate the SMA parameters with comprehensive physical understanding but also accurately predict retention over a wide range of loading conditions.
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12
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Automation of Modeling and Calibration of Integrated Preparative Protein Chromatography Systems. Processes (Basel) 2022. [DOI: 10.3390/pr10050945] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
With the increasing global demand for precise and efficient pharmaceuticals and the biopharma industry moving towards Industry 4.0, the need for advanced process integration, automation, and modeling has increased as well. In this work, a method for automatic modeling and calibration of an integrated preparative chromatographic system for pharmaceutical development and production is presented. Based on a user-defined system description, a system model was automatically generated and then calibrated using a sequence of experiments. The system description and model was implemented in the Python-based preparative chromatography control software Orbit.
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Kumar V, Leweke S, Heymann W, von Lieres E, Schlegel F, Westerberg K, Lenhoff AM. Robust mechanistic modeling of protein ion-exchange chromatography. J Chromatogr A 2021; 1660:462669. [PMID: 34800897 DOI: 10.1016/j.chroma.2021.462669] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 10/20/2021] [Accepted: 10/31/2021] [Indexed: 11/25/2022]
Abstract
Mechanistic models for ion-exchange chromatography of proteins are well-established and a broad consensus exists on most aspects of the detailed mathematical and physical description. A variety of specializations of these models can typically capture the general locations of elution peaks, but discrepancies are often observed in peak position and shape, especially if the column load level is in the non-linear range. These discrepancies may prevent the use of models for high-fidelity predictive applications such as process characterization and development of high-purity and -productivity process steps. Our objective is to develop a sufficiently robust mechanistic framework to make both conventional and anomalous phenomena more readily predictable using model parameters that can be evaluated based on independent measurements or well-accepted correlations. This work demonstrates the implementation of this approach for industry-relevant case studies using both a model protein, lysozyme, and biopharmaceutical product monoclonal antibodies, using cation-exchange resins with a variety of architectures (SP Sepharose FF, Fractogel EMD SO3-, Capto S and Toyopearl SP650M). The modeling employs the general rate model with the extension of the surface diffusivity to be variable, as a function of ionic strength or binding affinity. A colloidal isotherm that accounts for protein-surface and protein-protein interactions independently was used, with each characterized by a parameter determined as a function of ionic strength and pH. Both of these isotherm parameters, along with the variable surface diffusivity, were successfully estimated using breakthrough data at different ionic strengths and pH. The model developed was used to predict overloads and elution curves with high accuracy for a wide variety of gradients and different flow rates and protein loads. The in-silico methodology used in this work for parameter estimation, along with a minimal amount of experimental data, can help the industry adopt model-based optimization and control of preparative ion-exchange chromatography with high accuracy.
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Affiliation(s)
- Vijesh Kumar
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716, United States
| | - Samuel Leweke
- IBG-1: Biotechnology Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
| | - William Heymann
- IBG-1: Biotechnology Forschungszentrum Jülich GmbH, 52425 Jülich, Germany; Amgen Process Development, One Kendall Square, 360 Binney St., Cambridge, MA 02141, United States
| | - Eric von Lieres
- IBG-1: Biotechnology Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
| | - Fabrice Schlegel
- Amgen Process Development, One Kendall Square, 360 Binney St., Cambridge, MA 02141, United States
| | - Karin Westerberg
- Amgen Process Development, One Amgen Center Drive, Thousand Oaks, CA 91360, United States
| | - Abraham M Lenhoff
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716, United States.
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Heymann W, Glaser J, Schlegel F, Johnson W, Rolandi P, von Lieres E. Advanced score system and automated search strategies for parameter estimation in mechanistic chromatography modeling. J Chromatogr A 2021; 1661:462693. [PMID: 34863063 DOI: 10.1016/j.chroma.2021.462693] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Revised: 10/29/2021] [Accepted: 11/16/2021] [Indexed: 01/04/2023]
Abstract
Least squares estimation of unknown parameters from measurement data is a well-established standard method in chromatography modeling but can suffer from critical disadvantages. The description of real-world systems is generally prone to unaccounted mechanisms, such as dispersion in external holdup volumes, and systematic measurement errors, such as caused by pump delays. In this scenario, matching the shape between simulated and measured chromatograms has been found to be more important than the exact peak positions. We have therefore developed a new score system that separately accounts for the shape, position and height of individual peaks. A genetic algorithm is used for optimizing these multiple objectives. Even for non-conflicting objectives, this approach shows superior convergence in comparison to single-objective gradient search, while conflicting objectives indicate incomplete models or inconsistent data. In the latter case, Pareto optima provide important information for understanding the system and improving experiments. The proposed method is demonstrated with synthetic and experimental case studies of increasing complexity. All software is freely available as open source code (https://github.com/modsim/CADET-Match).
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Affiliation(s)
- William Heymann
- Institute of Geo- and Biosciences 1 (IBG-1), Forschungszentrum Jülich, Wilhelm-Johnen-Str. 1, 52428 Jülich, Germany; RWTH Aachen University, 52062 Aachen, Germany
| | - Juliane Glaser
- Digital Integration and Predictive Technologies (DIPT), Amgen Research Munich, Staffelseestr. 2, 81477 München, Germany
| | - Fabrice Schlegel
- Digital Integration and Predictive Technologies (DIPT), Amgen, 360 Binney St, Cambridge, MA 02142, United States
| | - Will Johnson
- Digital Integration and Predictive Technologies (DIPT), Amgen, 360 Binney St, Cambridge, MA 02142, United States
| | - Pablo Rolandi
- Digital Integration and Predictive Technologies (DIPT), Amgen, 360 Binney St, Cambridge, MA 02142, United States
| | - Eric von Lieres
- Institute of Geo- and Biosciences 1 (IBG-1), Forschungszentrum Jülich, Wilhelm-Johnen-Str. 1, 52428 Jülich, Germany.
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15
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Rakotondravao HM, Ishizuka N, Sakakibara K, Wada R, Ichihashi E, Takahashi R, Takai T, Horiuchi JI, Kumada Y. Characterization of a macroporous epoxy-polymer based resin for the ion-exchange chromatography of therapeutic proteins. J Chromatogr A 2021; 1656:462503. [PMID: 34520891 DOI: 10.1016/j.chroma.2021.462503] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 08/23/2021] [Accepted: 08/25/2021] [Indexed: 10/20/2022]
Abstract
This study investigated the adsorption capacity and mass transfer properties of a novel macroporous epoxy-polymer-based anion-exchanger, MPR Q, for the efficient separation of therapeutic proteins. MPR Q resin was prepared by phase separation based on spinodal decomposition followed by dextran grafting and ligand conjugation. Under static conditions, MPR Q exhibited a binding capacity of 49.8 mg-IgG/cm3-resin at pH 10, whereas the fastest adsorption was observed among the anion-exchanger resins tested. Inverse size-exclusion chromatography (iSEC) experiments revealed that the apparent pore diameter of MPR Q was approximately 90 nm, which was sufficiently large for the penetration of human IgG and bovine IgM. Moreover, the reduced height equivalent to a theoretical plate, h, of human IgG, determined using the linear gradient elution method was 65.8 and was not significantly changed in the range of linear velocities from 20.37 to 50.93 cm/min. The dynamic binding capacity at 10% breakthrough of MPR Q, determined by frontal analysis, exhibited a capacity of 43.8 mg/cm3 at 5.09 cm/min and 58% of DBC10% was maintained even though the linear velocity was increased to 50.93 cm/min. Furthermore, a resolution for separation of IgG and BSA by MPR Q was 1.06 at 5.09 cm/min, while it was higher than that for the conventional resin at all linear velocities from 5.09 cm/min to 50.93 cm/min. Thus, it was suggested that the MPR Q developed in this study is a promising resin that can efficiently separate large biomacromolecules such as human IgG at higher velocities.
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Affiliation(s)
| | - Norio Ishizuka
- Emaus Kyoto, Inc., 26 Saiinnishida-Cho, Ukyo, Kyoto 615-0055, Japan
| | - Keita Sakakibara
- National Institute of Advanced Industrial Science and Technology (AIST), 3-11-32 Kagamiyama, Higashihiroshima, Hiroshima 739-0046, Japan
| | - Ryota Wada
- Kyoto Research Laboratories, YMC Co., Ltd., 59 Yonnotsubo-Cho Iwakuraminami, Sakyo, Kyoto 606-0033, Japan
| | - Emi Ichihashi
- Kyoto Research Laboratories, YMC Co., Ltd., 59 Yonnotsubo-Cho Iwakuraminami, Sakyo, Kyoto 606-0033, Japan
| | - Ryosuke Takahashi
- Kyoto Research Laboratories, YMC Co., Ltd., 59 Yonnotsubo-Cho Iwakuraminami, Sakyo, Kyoto 606-0033, Japan
| | - Takatomo Takai
- Kyoto Research Laboratories, YMC Co., Ltd., 59 Yonnotsubo-Cho Iwakuraminami, Sakyo, Kyoto 606-0033, Japan
| | - Jun-Ichi Horiuchi
- Department of Material Chemistry, Kyoto Institute of Technology, 1 Hashigami-Cho, Matsugasaki, Sakyo-ku, Kyoto, Other, 606-8585, Japan
| | - Yoichi Kumada
- Department of Material Chemistry, Kyoto Institute of Technology, 1 Hashigami-Cho, Matsugasaki, Sakyo-ku, Kyoto, Other, 606-8585, Japan.
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16
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Saleh D, Hess R, Ahlers-Hesse M, Beckert N, Schönberger M, Rischawy F, Wang G, Bauer J, Blech M, Kluters S, Studts J, Hubbuch J. Modeling the impact of amino acid substitution in a monoclonal antibody on cation exchange chromatography. Biotechnol Bioeng 2021; 118:2923-2933. [PMID: 33871060 DOI: 10.1002/bit.27798] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 02/23/2021] [Accepted: 04/15/2021] [Indexed: 01/03/2023]
Abstract
A vital part of biopharmaceutical research is decision making around which lead candidate should be progressed in early-phase development. When multiple antibody candidates show similar biological activity, developability aspects are taken into account to ease the challenges of manufacturing the potential drug candidate. While current strategies for developability assessment mainly focus on drug product stability, only limited information is available on how antibody candidates with minimal differences in their primary structure behave during downstream processing. With increasing time-to-market pressure and an abundance of monoclonal antibodies (mAbs) in development pipelines, developability assessments should also consider the ability of mAbs to integrate into the downstream platform. This study investigates the influence of amino acid substitutions in the complementarity-determining region (CDR) of a full-length IgG1 mAb on the elution behavior in preparative cation exchange chromatography. Single amino acid substitutions within the investigated mAb resulted in an additional positive charge in the light chain (L) and heavy chain (H) CDR, respectively. The mAb variants showed an increased retention volume in linear gradient elution compared with the wild-type antibody. Furthermore, the substitution of tryptophan with lysine in the H-CDR3 increased charge heterogeneity of the product. A multiscale in silico analysis, consisting of homology modeling, protein surface analysis, and mechanistic chromatography modeling increased understanding of the adsorption mechanism. The results reveal the potential effects of lead optimization during antibody drug discovery on downstream processing.
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Affiliation(s)
- David Saleh
- Late Stage DSP Development, Boehringer Ingelheim, Biberach, Germany.,Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Rudger Hess
- Late Stage DSP Development, Boehringer Ingelheim, Biberach, Germany.,Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | | | - Nicole Beckert
- Pharmaceutical Development Biologics, Boehringer Ingelheim, Biberach, Germany
| | | | - Federico Rischawy
- Late Stage DSP Development, Boehringer Ingelheim, Biberach, Germany.,Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Gang Wang
- Late Stage DSP Development, Boehringer Ingelheim, Biberach, Germany
| | - Joschka Bauer
- Pharmaceutical Development Biologics, Boehringer Ingelheim, Biberach, Germany
| | - Michaela Blech
- Pharmaceutical Development Biologics, Boehringer Ingelheim, Biberach, Germany
| | - Simon Kluters
- Late Stage DSP Development, Boehringer Ingelheim, Biberach, Germany
| | - Joey Studts
- Late Stage DSP Development, Boehringer Ingelheim, Biberach, Germany
| | - Jürgen Hubbuch
- Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
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17
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Simoes-Cardoso JC, Hoshino N, Yoshimura Y, Chen CS, Dias-Cabral C, Yoshimoto N, Yamamoto S. Correlation between protein desorption behavior and its adsorption enthalpy change in polymer grafted anion exchange chromatography. Colloids Surf B Biointerfaces 2021; 205:111853. [PMID: 34098366 DOI: 10.1016/j.colsurfb.2021.111853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 04/29/2021] [Accepted: 05/13/2021] [Indexed: 10/21/2022]
Abstract
Thermodynamic studies on protein adsorption onto chromatographic surfaces mainly focus on the molecular level interaction between proteins and ligands. Yet, not much attention is given to the study of polymer grafted ligand architecture effect on thermodynamic parameters, nor to the relation between chromatographic parameters and the directly obtained thermodynamic parameters. These relations are needed in order to confer meaning and to ease future data interpretation of thermodynamic studies of protein adsorption. In this study, the adsorption of bovine serum albumin monomer (BSAm) onto chromatographic surfaces with grafted ligands was studied from a thermodynamic point of view together with chromatographic data. Isothermal titration calorimetry (ITC) results showed that BSAm adsorption is exothermic (ΔH¯ads < 0) when adsorbs onto Toyopearl GigaCapQ 650 M, Toyopearl Q600AR, and Q Sepharose XL, but endothermic (ΔH¯ads > 0) when adsorbs onto Toyopearl SuperQ and a conventional resin (Q Sepharose Fast Flow), showing clear differences in the driving forces of adsorption caused by different ligand architectures. In addition, we found a new relation between the salt required for protein elution and the change in adsorption enthalpy (ΔH¯ads) directly measured with ITC, intrinsically connecting both adsorption and desorption mechanisms.
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Affiliation(s)
- Joao Carlos Simoes-Cardoso
- Bio-Process Engineering Laboratory, Biomedical Engineering Center, Yamaguchi University, Tokiwadai 2-16-1, Ube 755-8611, Japan.
| | - Nanako Hoshino
- Bio-Process Engineering Laboratory, Biomedical Engineering Center, Yamaguchi University, Tokiwadai 2-16-1, Ube 755-8611, Japan
| | - Yusuke Yoshimura
- Bio-Process Engineering Laboratory, Biomedical Engineering Center, Yamaguchi University, Tokiwadai 2-16-1, Ube 755-8611, Japan
| | - Chyi-Shin Chen
- Bio-Process Engineering Laboratory, Biomedical Engineering Center, Yamaguchi University, Tokiwadai 2-16-1, Ube 755-8611, Japan
| | - Cristina Dias-Cabral
- CICS-UBI - Health Sciences Research Centre, University of Beira Interior, Covilhã, 6200-506, Portugal; Department of Chemistry, University of Beira Interior, Covilhã, 6201-001, Portugal
| | - Noriko Yoshimoto
- Bio-Process Engineering Laboratory, Biomedical Engineering Center, Yamaguchi University, Tokiwadai 2-16-1, Ube 755-8611, Japan
| | - Shuichi Yamamoto
- Bio-Process Engineering Laboratory, Biomedical Engineering Center, Yamaguchi University, Tokiwadai 2-16-1, Ube 755-8611, Japan
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18
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Chen CS, Yoshimoto N, Yamamoto S. Prediction of the Performance of Capture Chromatography Processes of Proteins and Its Application to the Repeated Cyclic Operation Optimization. JOURNAL OF CHEMICAL ENGINEERING OF JAPAN 2020. [DOI: 10.1252/jcej.20we116] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Chyi-Shin Chen
- Graduate School of Innovation and Science, Biomedical Engineering Center (YUBEC), Yamaguchi University
| | - Noriko Yoshimoto
- Graduate School of Innovation and Science, Biomedical Engineering Center (YUBEC), Yamaguchi University
| | - Shuichi Yamamoto
- Graduate School of Innovation and Science, Biomedical Engineering Center (YUBEC), Yamaguchi University
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19
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Saleh D, Wang G, Mueller B, Rischawy F, Kluters S, Studts J, Hubbuch J. Cross-scale quality assessment of a mechanistic cation exchange chromatography model. Biotechnol Prog 2020; 37:e3081. [PMID: 32926575 DOI: 10.1002/btpr.3081] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 09/02/2020] [Accepted: 09/11/2020] [Indexed: 12/13/2022]
Abstract
Cation exchange chromatography (CEX) is an essential part of most monoclonal antibody (mAb) purification platforms. Process characterization and root cause investigation of chromatographic unit operations are performed using scale down models (SDM). SDM chromatography columns typically have the identical bed height as the respective manufacturing-scale, but a significantly reduced inner diameter. While SDMs enable process development demanding less material and time, their comparability to manufacturing-scale can be affected by variability in feed composition, mobile phase and resin properties, or dispersion effects depending on the chromatography system at hand. Mechanistic models can help to close gaps between scales and reduce experimental efforts compared to experimental SDM applications. In this study, a multicomponent steric mass-action (SMA) adsorption model was applied to the scale-up of a CEX polishing step. Based on chromatograms and elution pool data ranging from laboratory- to manufacturing-scale, the proposed modeling workflow enabled early identification of differences between scales, for example, system dispersion effects or ionic capacity variability. A multistage model qualification approach was introduced to measure the model quality and to understand the model's limitations across scales. The experimental SDM and the in silico model were qualified against large-scale data using the identical state of the art equivalence testing procedure. The mechanistic chromatography model avoided limitations of the SDM by capturing effects of bed height, loading density, feed composition, and mobile phase properties. The results demonstrate the applicability of mechanistic chromatography models as a possible alternative to conventional SDM approaches.
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Affiliation(s)
- David Saleh
- Late Stage DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.,Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Institute of Engineering in Life Sciences, Karlsruhe, Germany
| | - Gang Wang
- Late Stage DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - Benedict Mueller
- Late Stage DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - Federico Rischawy
- Late Stage DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.,Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Institute of Engineering in Life Sciences, Karlsruhe, Germany
| | - Simon Kluters
- Late Stage DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - Joey Studts
- Late Stage DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - Jürgen Hubbuch
- Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Institute of Engineering in Life Sciences, Karlsruhe, Germany
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20
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Kumar V, Lenhoff AM. Mechanistic Modeling of Preparative Column Chromatography for Biotherapeutics. Annu Rev Chem Biomol Eng 2020; 11:235-255. [DOI: 10.1146/annurev-chembioeng-102419-125430] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Chromatography has long been, and remains, the workhorse of downstream processing in the production of biopharmaceuticals. As bioprocessing has matured, there has been a growing trend toward seeking a detailed fundamental understanding of the relevant unit operations, which for some operations include the use of mechanistic modeling in a way similar to its use in the conventional chemical process industries. Mechanistic models of chromatography have been developed for almost a century, but although the essential features are generally understood, the specialization of such models to biopharmaceutical processing includes several areas that require further elucidation. This review outlines the overall approaches used in such modeling and emphasizes current needs, specifically in the context of typical uses of such models; these include selection and improvement of isotherm models and methods to estimate isotherm and transport parameters independently. Further insights are likely to be aided by molecular-level modeling, as well as by the copious amounts of empirical data available for existing processes.
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Affiliation(s)
- Vijesh Kumar
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, USA
| | - Abraham M. Lenhoff
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, USA
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21
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Scale up of a chromatographic capture step for a clarified bacterial homogenate – Influence of mass transport limitation and competitive adsorption of impurities. J Chromatogr A 2020; 1618:460856. [DOI: 10.1016/j.chroma.2020.460856] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Revised: 12/28/2019] [Accepted: 01/06/2020] [Indexed: 11/20/2022]
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22
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Saleh D, Wang G, Müller B, Rischawy F, Kluters S, Studts J, Hubbuch J. Straightforward method for calibration of mechanistic cation exchange chromatography models for industrial applications. Biotechnol Prog 2020; 36:e2984. [DOI: 10.1002/btpr.2984] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 02/03/2020] [Accepted: 02/19/2020] [Indexed: 12/31/2022]
Affiliation(s)
- David Saleh
- Late Stage DSP DevelopmentBoehringer Ingelheim Pharma GmbH & Co. KG Biberach Germany
- Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT) Karlsruhe Germany
| | - Gang Wang
- Late Stage DSP DevelopmentBoehringer Ingelheim Pharma GmbH & Co. KG Biberach Germany
| | - Benedict Müller
- Late Stage DSP DevelopmentBoehringer Ingelheim Pharma GmbH & Co. KG Biberach Germany
| | - Federico Rischawy
- Late Stage DSP DevelopmentBoehringer Ingelheim Pharma GmbH & Co. KG Biberach Germany
- Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT) Karlsruhe Germany
| | - Simon Kluters
- Late Stage DSP DevelopmentBoehringer Ingelheim Pharma GmbH & Co. KG Biberach Germany
| | - Joey Studts
- Late Stage DSP DevelopmentBoehringer Ingelheim Pharma GmbH & Co. KG Biberach Germany
| | - Jürgen Hubbuch
- Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT) Karlsruhe Germany
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23
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Zhang H, Liu C, Chen L, Dai B. Control of ice crystal growth and its effect on porous structure of chitosan cryogels. Chem Eng Sci 2019. [DOI: 10.1016/j.ces.2019.02.026] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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24
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Shekhawat LK, Rathore AS. An overview of mechanistic modeling of liquid chromatography. Prep Biochem Biotechnol 2019; 49:623-638. [DOI: 10.1080/10826068.2019.1615504] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Lalita K. Shekhawat
- Department of Chemical Engineering, Indian Institute of Technology, New Delhi, India
| | - Anurag S. Rathore
- Department of Chemical Engineering, Indian Institute of Technology, New Delhi, India
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25
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Marek WK, Sauer D, Dürauer A, Jungbauer A, Piątkowski W, Antos D. Prediction tool for loading, isocratic elution, gradient elution and scaling up of ion exchange chromatography of proteins. J Chromatogr A 2018; 1566:89-101. [DOI: 10.1016/j.chroma.2018.06.057] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Revised: 06/20/2018] [Accepted: 06/22/2018] [Indexed: 11/28/2022]
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26
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Steinebach F, Wälchli R, Pfister D, Morbidelli M. Adsorption Behavior of Charge Isoforms of Monoclonal Antibodies on Strong Cation Exchangers. Biotechnol J 2017; 12. [DOI: 10.1002/biot.201700123] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 10/01/2017] [Indexed: 12/12/2022]
Affiliation(s)
- Fabian Steinebach
- Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences; ETH Zurich 8093 Zurich Switzerland
| | - Ruben Wälchli
- Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences; ETH Zurich 8093 Zurich Switzerland
| | | | - Massimo Morbidelli
- Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences; ETH Zurich 8093 Zurich Switzerland
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27
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Wang G, Briskot T, Hahn T, Baumann P, Hubbuch J. Estimation of adsorption isotherm and mass transfer parameters in protein chromatography using artificial neural networks. J Chromatogr A 2017; 1487:211-217. [DOI: 10.1016/j.chroma.2017.01.068] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Revised: 01/23/2017] [Accepted: 01/25/2017] [Indexed: 11/26/2022]
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28
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Khalaf R, Heymann J, LeSaout X, Monard F, Costioli M, Morbidelli M. Model-based high-throughput design of ion exchange protein chromatography. J Chromatogr A 2016; 1459:67-77. [DOI: 10.1016/j.chroma.2016.06.076] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2016] [Revised: 06/19/2016] [Accepted: 06/24/2016] [Indexed: 01/11/2023]
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