1
|
Pareek A, Buddhiraju VS, Masampally VS, Premraj K, Runkana V. Comparison of multi-column chromatography configurations through model-based optimization. Biotechnol Prog 2023; 39:e3376. [PMID: 37454372 DOI: 10.1002/btpr.3376] [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: 09/07/2022] [Revised: 05/30/2023] [Accepted: 06/30/2023] [Indexed: 07/18/2023]
Abstract
Integrated continuous bioprocessing has been identified as the next important phase of evolution in biopharmaceutical manufacturing. Multiple platform technologies to enable continuous processing are being developed. Multi-column counter-current chromatography is a step in this direction to provide increased productivity and capacity utilization to capture biomolecules like monoclonal antibodies (mAbs) present in the reactor harvest and remove impurities. Model-based optimization of two prevalent multi-column designs, 3-column and 4-column periodic counter-current chromatography (PCC) was carried out for different concentrations of mAbs in the feed, durations of cleaning-in-place and equilibration protocols. The multi-objective optimization problem comprising three performance measures, namely, product yield, productivity, and capacity utilization was solved using the Radial basis function optimization technique. The superficial velocities during load, wash, and elute operations, along with durations of distinct stages present in the multi-column operations were considered as decision variables. Optimization results without the constraint on number of wash volumes showed that 3-Column PCC performs better than 4-Column PCC. For example, at a feed concentration of 1.2 mg/mL, productivity, yield and capacity utilization, respectively, were 0.024 mg/mL.s, 0.94, and 0.94 for 3-Column PCC and 0.017 mg/mL.s, 0.87, and 0.83 for 4-column PCC. Similar trends were observed at higher feed concentrations also. However, when the constraint on number of wash volumes is included, 4-Column PCC was found to result in consistent productivity and product yield under different operating conditions but at the expense of reduced capacity utilization.
Collapse
Affiliation(s)
- Aditya Pareek
- TCS Research, Tata Research Development and Design Centre, Tata Consultancy Services, Pune, India
| | | | | | - Karundev Premraj
- TCS Research, Tata Research Development and Design Centre, Tata Consultancy Services, Pune, India
| | - Venkataramana Runkana
- TCS Research, Tata Research Development and Design Centre, Tata Consultancy Services, Pune, India
| |
Collapse
|
2
|
Benedini LJ, Furlan FF, Figueiredo D, Cabrera-Crespo J, Ribeiro MPA, Campani G, Gonçalves VM, Zangirolami TC. A comprehensive method for modeling and simulating ion exchange chromatography of complex mixtures. Protein Expr Purif 2023; 205:106228. [PMID: 36587709 DOI: 10.1016/j.pep.2022.106228] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 12/09/2022] [Accepted: 12/22/2022] [Indexed: 12/31/2022]
Abstract
In recent years, many biological-based products have been developed, representing a significant fraction of income in the pharmaceutical market. Ion exchange chromatography is an important downstream step for the purification of target recombinant proteins present in clarified cell extracts, together with many other unknown impurities. This work develops a robust approach to model and simulate the purification of untagged heterologous proteins, so that the improved conditions to carry out an ion exchange chromatography are identified in a rational basis prior to the real purification run itself. Purification of the pneumococcal surface protein A (PspA4Pro) was used as a case study. This protein is produced by recombinant Escherichia coli and is a candidate for the manufacture of improved pneumococcal vaccines. The developed method combined experimental and computational procedures. Different anion exchange operating conditions were mapped in order to gather a broad range of representative experimental data. The equilibrium dispersive and the steric mass action equations were used to model and simulate the process. A training strategy to fit the model and separately describe the elution profiles of PspA4Pro and other proteins of the cell extract was applied. Based on the simulation results, a reduced ionic strength was applied for PspA4Pro elution, leading to increases of 14.9% and 11.5% for PspA4Pro recovery and purity, respectively, compared to the original elution profile. These results showed the potential of this method, which could be further applied to improve the performance of ion exchange chromatography in the purification of other target proteins under real process conditions.
Collapse
Affiliation(s)
- Leandro J Benedini
- Graduate Program in Chemical Engineering (PPGEQ), Federal University of São Carlos (UFSCar), São Carlos, Brazil; Federal Institute of São Paulo (IFSP), Catanduva, Brazil.
| | - Felipe F Furlan
- Graduate Program in Chemical Engineering (PPGEQ), Federal University of São Carlos (UFSCar), São Carlos, Brazil; Chemical Engineering Department, Federal University of São Carlos (UFSCar), São Carlos, Brazil
| | - Douglas Figueiredo
- Butantan Institute, Laboratory of Vaccine Development, São Paulo, Brazil
| | | | - Marcelo P A Ribeiro
- Graduate Program in Chemical Engineering (PPGEQ), Federal University of São Carlos (UFSCar), São Carlos, Brazil; Chemical Engineering Department, Federal University of São Carlos (UFSCar), São Carlos, Brazil
| | - Gilson Campani
- Department of Engineering, Federal University of Lavras, Lavras, Brazil
| | | | - Teresa C Zangirolami
- Graduate Program in Chemical Engineering (PPGEQ), Federal University of São Carlos (UFSCar), São Carlos, Brazil; Chemical Engineering Department, Federal University of São Carlos (UFSCar), São Carlos, Brazil
| |
Collapse
|
3
|
Wei F, Sang J, Zhao Y. Theoretical study of twin-column recycling chromatography with a solvent-gradient for preparative binary separations. J Chromatogr A 2021; 1651:462306. [PMID: 34139387 DOI: 10.1016/j.chroma.2021.462306] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 05/12/2021] [Accepted: 05/31/2021] [Indexed: 12/01/2022]
Abstract
Twin-column recycling chromatography with a solvent gradient (TCRC-SG) was investigated with the equilibrium-dispersive chromatography model. The solvent gradient caused by constant addition of a modifier between the two columns created a band compression effect to counterbalance band broadening, so that the target component band neither broadened nor shrunk. Meanwhile, band compression accelerated the separation but prevented excessive separation. Increasing the volume fraction of weak solvent in the modifier and reducing the modifier flowrate enhanced band compression and improved the separation. The effect of column efficiency (number of theoretical plates: 500-1500) on the separation was not significant. According to the separation behavior, a simple operation scheme is proposed to automatically control column switching without needing to determine the adsorption isotherm and designing operating conditions in advance. In comparison with simulated moving bed, TCRC-SG had a higher feed throughput, but consumed more solvent. The results showed that TCRC-SG is favorable for preparative separation.
Collapse
Affiliation(s)
- Feng Wei
- NingboTech University, Ningbo 315100, China.
| | | | | |
Collapse
|
4
|
Model-based process development of continuous chromatography for antibody capture: A case study with twin-column system. J Chromatogr A 2020; 1619:460936. [DOI: 10.1016/j.chroma.2020.460936] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 01/15/2020] [Accepted: 01/29/2020] [Indexed: 01/06/2023]
|
5
|
Benedini LJ, Figueiredo D, Cabrera-Crespo J, Gonçalves VM, Silva GG, Campani G, Zangirolami TC, Furlan FF. Modeling and simulation of anion exchange chromatography for purification of proteins in complex mixtures. J Chromatogr A 2020; 1613:460685. [DOI: 10.1016/j.chroma.2019.460685] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 10/09/2019] [Accepted: 11/05/2019] [Indexed: 01/01/2023]
|
6
|
Stamatis C, Goldrick S, Gruber D, Turner R, Titchener-Hooker NJ, Farid SS. High throughput process development workflow with advanced decision-support for antibody purification. J Chromatogr A 2019; 1596:104-116. [PMID: 30885400 DOI: 10.1016/j.chroma.2019.03.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Revised: 02/28/2019] [Accepted: 03/03/2019] [Indexed: 10/27/2022]
Abstract
Chromatography remains the workhorse in antibody purification; however process development and characterisation still require significant resources. The high number of operating parameters involved requires extensive experimentation, traditionally performed at small- and pilot-scale, leading to demands in terms of materials and time that can be a challenge. The main objective of this research was the establishment of a novel High Throughput Process Development (HTPD) workflow combining scale-down chromatography experimentation with advanced decision-support techniques in order to minimise the consumption of resources and accelerate the development timeframe. Additionally, the HTPD workflow provides a framework to rapidly manipulate large datasets in an automated fashion. The central component of the HTPD workflow is the systematic integration of a microscale chromatography experimentation strategy with an advanced chromatogram evaluation method, design of experiments (DoE) and multivariate data analysis. The outputs of this are leveraged into the screening and optimisation components of the workflow. For the screening component, a decision-support tool was developed combining different multi-criteria decision-making techniques to enable a fair comparison of a number of CEX resin candidates and determine those that demonstrate superior purification performance. This provided a rational methodology for screening chromatography resins and process parameters. For the optimisation component, the workflow leverages insights provided through screening experimentation to guide subsequent DoE experiments so as to tune significant process parameters for the selected resin. The resulting empirical correlations are linked to a stochastic modelling technique so as to predict the optimal and most robust chromatographic process parameters to achieve the desired performance criteria.
Collapse
Affiliation(s)
- Christos Stamatis
- The Advanced Centre for Biochemical Engineering, Department of Biochemical Engineering, University College London, Gower Street, London WC1E 6BT, UK; MedImmune Limited, Milstein Building, Granta Park, Cambridge CB1 6GH, UK
| | - Stephen Goldrick
- The Advanced Centre for Biochemical Engineering, Department of Biochemical Engineering, University College London, Gower Street, London WC1E 6BT, UK; MedImmune Limited, Milstein Building, Granta Park, Cambridge CB1 6GH, UK
| | - David Gruber
- MedImmune Limited, Milstein Building, Granta Park, Cambridge CB1 6GH, UK
| | - Richard Turner
- MedImmune Limited, Milstein Building, Granta Park, Cambridge CB1 6GH, UK
| | - Nigel J Titchener-Hooker
- The Advanced Centre for Biochemical Engineering, Department of Biochemical Engineering, University College London, Gower Street, London WC1E 6BT, UK
| | - Suzanne S Farid
- The Advanced Centre for Biochemical Engineering, Department of Biochemical Engineering, University College London, Gower Street, London WC1E 6BT, UK.
| |
Collapse
|
7
|
Faraji N, Zhang Y, Ray AK. Determination of adsorption isotherm parameters for minor whey proteins by gradient elution preparative liquid chromatography. J Chromatogr A 2015; 1412:67-74. [DOI: 10.1016/j.chroma.2015.08.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2015] [Accepted: 08/03/2015] [Indexed: 11/26/2022]
|
8
|
Creasy A, Barker G, Yao Y, Carta G. Systematic interpolation method predicts protein chromatographic elution from batch isotherm data without a detailed mechanistic isotherm model. Biotechnol J 2015; 10:1400-11. [PMID: 26015091 DOI: 10.1002/biot.201500089] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2015] [Revised: 04/21/2015] [Accepted: 05/19/2015] [Indexed: 01/09/2023]
Abstract
Predicting protein elution for overloaded ion exchange columns requires models capable of describing protein binding over broad ranges of protein and salt concentrations. Although approximate mechanistic models are available, they do not always have the accuracy needed for precise predictions. The aim of this work is to develop a method to predict protein chromatographic behavior from batch isotherm data without relying on a mechanistic model. The method uses a systematic empirical interpolation (EI) scheme coupled with a lumped kinetic model with rate parameters determined from HETP measurements for non-binding conditions, to numerically predict the column behavior. For two experimental systems considered in this work, predictions based on the EI scheme are in excellent agreement with experimental elution profiles under highly overloaded conditions without using any adjustable parameters. A qualitative study of the sensitivity of predicting protein elution profiles to the precision, granularity, and extent of the batch adsorption data shows that the EI scheme is relatively insensitive to the properties of the dataset used, requiring only that the experimental ranges of protein and salt concentrations overlap those under which the protein actually elutes from the column and possess a ± 10% measurement precision.
Collapse
Affiliation(s)
- Arch Creasy
- Department of Chemical Engineering, University of Virginia, Charlottesville, VA, USA
| | - Gregory Barker
- Biologics Process Development, Bristol-Myers Squibb, Hopewell, NJ, USA
| | - Yan Yao
- Biologics Process Development, Bristol-Myers Squibb, Hopewell, NJ, USA
| | - Giorgio Carta
- Department of Chemical Engineering, University of Virginia, Charlottesville, VA, USA.
| |
Collapse
|
9
|
Liu S, Simaria AS, Farid SS, Papageorgiou LG. Optimising chromatography strategies of antibody purification processes by mixed integer fractional programming techniques. Comput Chem Eng 2014. [DOI: 10.1016/j.compchemeng.2014.05.005] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
|
10
|
Yan X, Wang Q. Comparative analysis of chromatography dynamic models in predicting the plate height contributed by interphase mass transfer. Chem Eng Sci 2013. [DOI: 10.1016/j.ces.2013.10.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
|
11
|
A high-throughput 2D-analytical technique to obtain single protein parameters from complex cell lysates for in silico process development of ion exchange chromatography. J Chromatogr A 2013; 1318:84-91. [DOI: 10.1016/j.chroma.2013.09.043] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2013] [Revised: 09/09/2013] [Accepted: 09/12/2013] [Indexed: 11/16/2022]
|
12
|
Nfor BK, Ahamed T, Pinkse MW, van der Wielen LA, Verhaert PD, van Dedem GW, Eppink MH, van de Sandt EJ, Ottens M. Multi-dimensional fractionation and characterization of crude protein mixtures: Toward establishment of a database of protein purification process development parameters. Biotechnol Bioeng 2012; 109:3070-83. [DOI: 10.1002/bit.24576] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2011] [Revised: 04/20/2012] [Accepted: 05/30/2012] [Indexed: 11/08/2022]
|
13
|
Osberghaus A, Drechsel K, Hansen S, Hepbildikler S, Nath S, Haindl M, von Lieres E, Hubbuch J. Model-integrated process development demonstrated on the optimization of a robotic cation exchange step. Chem Eng Sci 2012. [DOI: 10.1016/j.ces.2012.04.004] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
|
14
|
Ng CK, Osuna-Sanchez H, Valéry E, Sørensen E, Bracewell DG. Design of high productivity antibody capture by protein A chromatography using an integrated experimental and modeling approach. J Chromatogr B Analyt Technol Biomed Life Sci 2012; 899:116-26. [DOI: 10.1016/j.jchromb.2012.05.010] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2012] [Revised: 05/02/2012] [Accepted: 05/06/2012] [Indexed: 11/28/2022]
|
15
|
Optimizing a chromatographic three component separation: A comparison of mechanistic and empiric modeling approaches. J Chromatogr A 2012; 1237:86-95. [DOI: 10.1016/j.chroma.2012.03.029] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2011] [Revised: 02/29/2012] [Accepted: 03/09/2012] [Indexed: 11/18/2022]
|
16
|
Osberghaus A, Hepbildikler S, Nath S, Haindl M, von Lieres E, Hubbuch J. Determination of parameters for the steric mass action model—A comparison between two approaches. J Chromatogr A 2012; 1233:54-65. [DOI: 10.1016/j.chroma.2012.02.004] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2011] [Revised: 01/18/2012] [Accepted: 02/01/2012] [Indexed: 10/14/2022]
|
17
|
Lienqueo ME, Mahn A, Salgado JC, Shene C. Mathematical Modeling of Protein Chromatograms. Chem Eng Technol 2011. [DOI: 10.1002/ceat.201100282] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
|
18
|
SMB chromatography design using profile advancement factors, miniplant data, and rate-based process simulation. AIChE J 2009. [DOI: 10.1002/aic.11938] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
|