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Döring L, Winderl J, Kron M, Hubbuch J. Mechanistic modeling of minute virus of mice surrogate removal by anion exchange chromatography in micro scale. J Chromatogr A 2024; 1734:465261. [PMID: 39216284 DOI: 10.1016/j.chroma.2024.465261] [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: 06/05/2024] [Revised: 08/02/2024] [Accepted: 08/11/2024] [Indexed: 09/04/2024]
Abstract
Biopharmaceutical products are often produced in Chinese hamster ovary (CHO) cell cultures that are vulnerable to virus infections. Therefore, it is a regulatory requirement that downstream purification steps for biopharmaceuticals can remove viruses from feedstocks. Anion exchange chromatography (AEX) is one of the downstream unit operations that is most frequently used for this purpose and claimed for its capability to remove viruses. However, the impact of various process parameters on virus removal by AEX is still not fully understood. Mechanistic modeling could be a promising way to approach this gap, as these models require comparatively few experiments for calibration. This makes them a valuable tool to improve understanding of viral clearance, especially since virus spiking studies are costly and time consuming. In this study, we present how the virus clearance of a MVM mock virus particle by Q Sepharose FF resin can be described by mechanistic modeling. A lumped kinetic model was combined with a steric mass action model and calibrated at micro scale using three linear gradient experiments and an incremental step elution gradient. The model was subsequently verified for its capability to predict the effect of different sodium chloride concentrations, as well as residence times, on virus clearance and was in good agreement with the LRVs of the verification runs. Overall, models like this could enhance the mechanistic understanding of viral clearance mechanisms and thereby contribute to the development of more efficient and safer biopharmaceutical downstream processes.
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Affiliation(s)
- Lukas Döring
- Process Science, Rentschler Biopharma SE, Erwin-Rentschler-Str. 21 88471 Laupheim, Germany; Karlsruhe Institute of Technology (KIT), Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Fritz-Haber-Weg 2 76131 Karlsruhe, Germany
| | - Johannes Winderl
- Process Science, Rentschler Biopharma SE, Erwin-Rentschler-Str. 21 88471 Laupheim, Germany
| | - Matthias Kron
- Process Science, Rentschler Biopharma SE, Erwin-Rentschler-Str. 21 88471 Laupheim, Germany
| | - Jürgen Hubbuch
- Karlsruhe Institute of Technology (KIT), Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Fritz-Haber-Weg 2 76131 Karlsruhe, Germany.
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2
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Che Hussian CHA, Leong WY. Factors affecting therapeutic protein purity and yield during chromatographic purification. Prep Biochem Biotechnol 2024; 54:150-158. [PMID: 37233514 DOI: 10.1080/10826068.2023.2217507] [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] [Indexed: 05/27/2023]
Abstract
Therapeutic proteins are recombinant proteins generated through recombinant DNA technology and have attracted a great deal of interest in numerous applications, including pharmaceutical, cosmetic, human and animal health, agriculture, food, and bioremediation. Producing therapeutic proteins on a large scale, mainly in the pharmaceutical industry, necessitates a cost-effective, straightforward, and adequate manufacturing process. In industry, a protein separation technique based mainly on protein characteristics and modes of chromatography will be applied to optimize the purification process. Typically, the downstream process of biopharmaceutical operations may involve multiple chromatography phases that require the use of large columns pre-packed with resins that must be inspected before use. Approximately 20% of the proteins are assumed to be lost at each purification stage during the production of biotherapeutic products. Hence, to produce a high quality product, particularly in the pharmaceutical industry, the correct approach and understanding of the factors influencing purity and yield during purification are necessary.
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Affiliation(s)
| | - Wai Yie Leong
- INTI International University & Colleges, Nilai, Negeri Sembilan, Malaysia
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3
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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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4
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Samaras JJ, Micheletti M, Ding W. Transformation of Biopharmaceutical Manufacturing Through Single-Use Technologies: Current State, Remaining Challenges, and Future Development. Annu Rev Chem Biomol Eng 2022; 13:73-97. [PMID: 35700527 DOI: 10.1146/annurev-chembioeng-092220-030223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Single-use technologies have transformed conventional biopharmaceutical manufacturing, and their adoption is increasing rapidly for emerging applications like antibody-drug conjugates and cell and gene therapy products. These disruptive technologies have also had a significant impact during the coronavirus disease 2019 pandemic, helping to advance process development to enable the manufacturing of new monoclonal antibody therapies and vaccines. Single-use systems provide closed plug-and-play solutions and enable process intensification and continuous processing. Several challenges remain, providing opportunities to advance single-use sensors and their integration with single-use systems, to develop novel plastic materials, and to standardize design for interchangeability. Because the industry is changing rapidly, a holistic analysis of the current single-use technologies is required, with a summary of the latest advancements in materials science and the implementation of these technologies in end-to-end bioprocesses.
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Affiliation(s)
- Jasmin J Samaras
- Advanced Centre for Biochemical Engineering, University College London, London, United Kingdom
| | - Martina Micheletti
- Advanced Centre for Biochemical Engineering, University College London, London, United Kingdom
| | - Weibing Ding
- Manufacturing Science & Technology, GSK, King of Prussia, Pennsylvania, USA;
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5
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Jiang Q, Seth S, Scharl T, Schroeder T, Jungbauer A, Dimartino S. Prediction of the performance of pre-packed purification columns through machine learning. J Sep Sci 2022; 45:1445-1457. [PMID: 35262290 PMCID: PMC9310636 DOI: 10.1002/jssc.202100864] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 01/31/2022] [Accepted: 03/01/2022] [Indexed: 11/11/2022]
Abstract
Pre-packed columns have been increasingly used in process development and biomanufacturing thanks to their ease of use and consistency. Traditionally, packing quality is predicted through rate models, which require extensive calibration efforts through independent experiments to determine relevant mass transfer and kinetic rate constants. Here we propose machine learning as a complementary predictive tool for column performance. A machine learning algorithm, extreme gradient boosting, was applied to a large data set of packing quality (plate height and asymmetry) for pre-packed columns as a function of quantitative parameters (column length, column diameter, and particle size) and qualitative attributes (backbone and functional mode). The machine learning model offered excellent predictive capabilities for the plate height and the asymmetry (90 and 93%, respectively), with packing quality strongly influenced by backbone (∼70% relative importance) and functional mode (∼15% relative importance), well above all other quantitative column parameters. The results highlight the ability of machine learning to provide reliable predictions of column performance from simple, generic parameters, including strategic qualitative parameters such as backbone and functionality, usually excluded from quantitative considerations. Our results will guide further efforts in column optimization, for example, by focusing on improvements of backbone and functional mode to obtain optimized packings.
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Affiliation(s)
- Qihao Jiang
- Institute of BioengineeringSchool of EngineeringThe University of EdinburghEdinburghUK
| | - Sohan Seth
- School of InformaticsThe University of EdinburghEdinburghUK
| | - Theresa Scharl
- Austrian Centre of Industrial BiotechnologyViennaAustria
- Institute of StatisticsUniversity of Natural Resources and Life Sciences ViennaViennaAustria
| | | | - Alois Jungbauer
- Austrian Centre of Industrial BiotechnologyViennaAustria
- Department of BiotechnologyUniversity of Natural Resources and Life SciencesViennaAustria
| | - Simone Dimartino
- Institute of BioengineeringSchool of EngineeringThe University of EdinburghEdinburghUK
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6
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Javidanbardan A, Chu V, Conde JP, Azevedo AM. Microchromatography integrated with impedance sensor for bioprocess optimization: Experimental and numerical study of column efficiency for evaluation of scalability. J Chromatogr A 2021; 1661:462678. [PMID: 34879308 DOI: 10.1016/j.chroma.2021.462678] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 11/03/2021] [Accepted: 11/05/2021] [Indexed: 10/19/2022]
Abstract
In the last decade, there has been a growing interest in developing microfluidic systems as new scale-down models for accelerated and cost-effective biopharmaceutical process development. Nonetheless, the research in this field is still in its infancy and requires further investigation to simplify and accelerate the microfabrication process. In addition, integration of different label-free sensors into the microcolumn systems has utmost importance to minimize result discrepancies during the scale-up process. In this study, we developed a simple, low-cost integrated microcolumn (26 µl). Micromilling technology was employed to define the geometry and shape of microfluidic structures using poly(methylmethacrylate) (PMMA). The design of PMMA microstructure was transferred to polydimethylsiloxane (PDMS), and interdigitated planar microelectrodes (IDE) were integrated into the system. To evaluate the scalability of the developed microcolumn column, column performance was assessed and compared with a conventional 1-ml prepacked column. Computational Fluid Dynamics (CFD) studies were performed for both columns to understand the differences between theoretical and experimental results regarding retention time and peak broadening. Despite obtaining an acceptable asymmetric factor for the microcolumn (1.03 ± 0.02), the reduced plate height value was still higher than the recommended range with the value of 4.14 ± 0.18. Nevertheless, the consistency and significant improvement of microcolumn efficiency compared to previous studies provide the possibility of developing robust simulation tools for transferring acquired experimental data for larger-scale units.
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Affiliation(s)
- Amin Javidanbardan
- IBB - Institute for Bioengineering and Biosciences, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal; Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Virginia Chu
- Instituto de Engenharia de Sistemas e Computadores - Microsistemas e Nanotecnologias (INESC MN), Lisbon, Portugal
| | - João P Conde
- Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal; Instituto de Engenharia de Sistemas e Computadores - Microsistemas e Nanotecnologias (INESC MN), Lisbon, Portugal.
| | - Ana M Azevedo
- IBB - Institute for Bioengineering and Biosciences, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal; Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal.
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7
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Bishop LDC, Misiura A, Landes CF. A new metric for relating macroscopic chromatograms to microscopic surface dynamics: the distribution function ratio (DFR). Analyst 2021; 146:4268-4279. [PMID: 34105529 DOI: 10.1039/d1an00370d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Heterogeneous stationary phase chemistry causes chromatographic tailing that lowers separation efficiency and complicates optimizing mobile phase conditions. Model-free metrics are attractive for assessing optimal separation conditions due to the low quantity of information required, but often do not reveal underlying mechanisms that cause tailing, for example, heterogeneous retention modes. We report a new metric, which we call the Distribution Function Ratio (DFR), based on a graphical comparison between the chromatogram and Gaussian cumulative distribution functions, achieving correspondence to ground truth surface dynamics with a single chromatogram. Using a Monte Carlo framework, we show that the DFR can predict the prevalence of heterogeneous retention modes with high precision when the relative desorption rate between modes is known, as in during surface dynamics experiments. Ground truth comparisons reveal that the DFR outperforms both the asymmetry factor and skewness by yielding a one-to-one correspondence with heterogeneous retention mode prevalence over a broad range of experimentally realistic values. Perhaps of more value, we illustrate that the DFR, when combined with the asymmetry factor and skewness, can estimate microscopic surface dynamics, providing valuable insights into surface chemistry using existing chromatographic instrumentation. Connecting ensemble results to microscopic quantities through the lens of simulation establishes a new chemistry-driven route to measuring and advancing separations.
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Affiliation(s)
- Logan D C Bishop
- Department of Chemistry, Rice University, Houston, Texas 77251, USA.
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8
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Roberts JA, Carta G. Relationship between HETP measurements and breakthrough curves in short chromatography columns. Biotechnol Prog 2020; 37:e3065. [PMID: 32790055 DOI: 10.1002/btpr.3065] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 08/04/2020] [Accepted: 08/07/2020] [Indexed: 12/13/2022]
Abstract
An analysis of the relationship between the number of plates measured with a small molecule tracer and the breakthrough curve of a strongly bound protein in short laboratory chromatography columns (1-5 cm) considering flow nonuniformity is presented. For practical conditions, while axial dispersion has only a small impact on the breakthrough curve, radial flow nonuniformity has a profound effect. Radial parabolic velocity profiles lead to tailing tracer peaks and broader breakthrough curves. Profiles where the velocity varies radially only in a thin region near the column wall lead to fronting tracer peaks and early breakthrough when the velocity at the wall is higher than the average and to tailing peaks and tailing breakthrough curves when the velocity at the wall is lower than the average. Experiments conducted in laboratory minicolumns (0.5-1 cm diameter, 0.5-1 ml volume) show tracer peaks and protein breakthrough curves that are consistent with higher velocities at the wall. The model presented in this work provides a tool to model experimental breakthrough data and to assess the degree of flow uniformity required to obtain meaningful dynamic binding capacity measurements using minicolumns in a high-throughput lab setting.
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Affiliation(s)
- Joey A Roberts
- Department of Chemical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Giorgio Carta
- Department of Chemical Engineering, University of Virginia, Charlottesville, Virginia, USA
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9
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Dissecting peak broadening in chromatography columns under non-binding conditions. J Chromatogr A 2019; 1599:55-65. [DOI: 10.1016/j.chroma.2019.03.065] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Revised: 03/27/2019] [Accepted: 03/28/2019] [Indexed: 10/27/2022]
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10
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Packing quality, protein binding capacity and separation efficiency of pre-packed columns ranging from 1 mL laboratory to 57 L industrial scale. J Chromatogr A 2019; 1591:79-86. [DOI: 10.1016/j.chroma.2019.01.014] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Revised: 09/28/2018] [Accepted: 01/07/2019] [Indexed: 11/19/2022]
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11
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Salmean C, Dimartino S. 3D-Printed Stationary Phases with Ordered Morphology: State of the Art and Future Development in Liquid Chromatography. Chromatographia 2018. [DOI: 10.1007/s10337-018-3671-5] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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12
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Fekete S, Codesido S, Rudaz S, Guillarme D, Horváth K. Apparent efficiency of serially coupled columns in isocratic and gradient elution modes. J Chromatogr A 2018; 1571:121-131. [DOI: 10.1016/j.chroma.2018.08.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Revised: 07/27/2018] [Accepted: 08/01/2018] [Indexed: 02/01/2023]
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13
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Pabst TM, Thai J, Hunter AK. Evaluation of recent Protein A stationary phase innovations for capture of biotherapeutics. J Chromatogr A 2018; 1554:45-60. [DOI: 10.1016/j.chroma.2018.03.060] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Revised: 03/26/2018] [Accepted: 03/29/2018] [Indexed: 11/29/2022]
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14
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Scalability of pre-packed preparative chromatography columns with different diameters and lengths taking into account extra column effects. J Chromatogr A 2018; 1537:66-74. [DOI: 10.1016/j.chroma.2018.01.022] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 12/20/2017] [Accepted: 01/08/2018] [Indexed: 11/18/2022]
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