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For: Narayanan H, Seidler T, Luna MF, Sokolov M, Morbidelli M, Butté A. Hybrid Models for the simulation and prediction of chromatographic processes for protein capture. J Chromatogr A 2021;1650:462248. [PMID: 34087519 DOI: 10.1016/j.chroma.2021.462248] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 04/29/2021] [Accepted: 05/07/2021] [Indexed: 12/11/2022]
Number Cited by Other Article(s)
1
Taguado Menza S, Prestia R, Fioretti I, Sponchioni M. Model-based optimization strategy for intensification in the chromatographic purification of oligonucleotides. J Chromatogr A 2024;1736:465321. [PMID: 39255651 DOI: 10.1016/j.chroma.2024.465321] [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: 06/03/2024] [Revised: 08/26/2024] [Accepted: 08/27/2024] [Indexed: 09/12/2024]
2
Keulen D, Apostolidi M, Geldhof G, Le Bussy O, Pabst M, Ottens M. Comparing in silico flowsheet optimization strategies in biopharmaceutical downstream processes. Biotechnol Prog 2024:e3514. [PMID: 39425493 DOI: 10.1002/btpr.3514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 08/25/2024] [Accepted: 10/02/2024] [Indexed: 10/21/2024]
3
Keulen D, Hagen EVD, Geldhof G, Le Bussy O, Pabst M, Ottens M. Using artificial neural networks to accelerate flowsheet optimization for downstream process development. Biotechnol Bioeng 2024;121:2318-2331. [PMID: 37256724 DOI: 10.1002/bit.28454] [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: 02/27/2023] [Revised: 05/11/2023] [Accepted: 05/17/2023] [Indexed: 06/02/2023]
4
Dürauer A, Jungbauer A, Scharl T. Sensors and chemometrics in downstream processing. Biotechnol Bioeng 2024;121:2347-2364. [PMID: 37470278 DOI: 10.1002/bit.28499] [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: 03/15/2023] [Revised: 06/14/2023] [Accepted: 07/07/2023] [Indexed: 07/21/2023]
5
González-Hernández Y, Perré P. Building blocks needed for mechanistic modeling of bioprocesses: A critical review based on protein production by CHO cells. Metab Eng Commun 2024;18:e00232. [PMID: 38501051 PMCID: PMC10945193 DOI: 10.1016/j.mec.2024.e00232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 02/12/2024] [Accepted: 02/23/2024] [Indexed: 03/20/2024]  Open
6
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]
7
Ardakani MH, Rezadoost H, Norouzi HR. Sequential purification of cannabidiol by two-dimensional liquid chromatography combined with modeling and simulation of elution profiles. J Chromatogr A 2024;1717:464702. [PMID: 38310701 DOI: 10.1016/j.chroma.2024.464702] [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: 09/02/2023] [Revised: 12/15/2023] [Accepted: 01/30/2024] [Indexed: 02/06/2024]
8
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]
9
Bhoyar S, Kumar V, Foster M, Xu X, Traylor SJ, Guo J, Lenhoff AM. Predictive mechanistic modeling of loading and elution in protein A chromatography. J Chromatogr A 2024;1713:464558. [PMID: 38096684 DOI: 10.1016/j.chroma.2023.464558] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 12/01/2023] [Accepted: 12/03/2023] [Indexed: 01/08/2024]
10
Drobnjakovic M, Hart R, Kulvatunyou BS, Ivezic N, Srinivasan V. Current challenges and recent advances on the path towards continuous biomanufacturing. Biotechnol Prog 2023;39:e3378. [PMID: 37493037 DOI: 10.1002/btpr.3378] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 05/13/2023] [Accepted: 06/21/2023] [Indexed: 07/27/2023]
11
Sun YN, Chen WW, Yao SJ, Lin DQ. Model-assisted process development, characterization and design of continuous chromatography for antibody separation. J Chromatogr A 2023;1707:464302. [PMID: 37607430 DOI: 10.1016/j.chroma.2023.464302] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 08/10/2023] [Accepted: 08/14/2023] [Indexed: 08/24/2023]
12
Singh YR, Shah DB, Maheshwari DG, Shah JS, Shah S. Advances in AI-Driven Retention Prediction for Different Chromatographic Techniques: Unraveling the Complexity. Crit Rev Anal Chem 2023;54:3559-3569. [PMID: 37672314 DOI: 10.1080/10408347.2023.2254379] [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: 09/07/2023]
13
Ding C, Gerberich C, Ierapetritou M. Hybrid model development for parameter estimation and process optimization of hydrophobic interaction chromatography. J Chromatogr A 2023;1703:464113. [PMID: 37267655 DOI: 10.1016/j.chroma.2023.464113] [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: 03/26/2023] [Revised: 05/26/2023] [Accepted: 05/27/2023] [Indexed: 06/04/2023]
14
Rathore AS, Nikita S, Thakur G, Mishra S. Artificial intelligence and machine learning applications in biopharmaceutical manufacturing. Trends Biotechnol 2023;41:497-510. [PMID: 36117026 DOI: 10.1016/j.tibtech.2022.08.007] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 07/08/2022] [Accepted: 08/22/2022] [Indexed: 11/30/2022]
15
Subraveti SG, Li Z, Prasad V, Rajendran A. Can a Computer “Learn” Nonlinear Chromatography?: Experimental Validation of Physics-Based Deep Neural Networks for the Simulation of Chromatographic Processes. Ind Eng Chem Res 2023. [DOI: 10.1021/acs.iecr.2c04355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/30/2023]
16
Bayer B, Duerkop M, Pörtner R, Möller J. Comparison of mechanistic and hybrid modeling approaches for characterization of a CHO cultivation process: Requirements, pitfalls and solution paths. Biotechnol J 2023;18:e2200381. [PMID: 36382343 DOI: 10.1002/biot.202200381] [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: 07/26/2022] [Revised: 11/07/2022] [Accepted: 11/08/2022] [Indexed: 11/17/2022]
17
Bader J, Narayanan H, Arosio P, Leroux JC. Improving extracellular vesicles production through a Bayesian optimization-based experimental design. Eur J Pharm Biopharm 2023;182:103-114. [PMID: 36526027 DOI: 10.1016/j.ejpb.2022.12.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 12/05/2022] [Accepted: 12/09/2022] [Indexed: 12/15/2022]
18
Khanal O. Mathematical modeling and process analytical technology for continuous chromatography of biopharmaceutical products. Curr Opin Biotechnol 2022;78:102796. [PMID: 36152423 DOI: 10.1016/j.copbio.2022.102796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 08/13/2022] [Accepted: 08/25/2022] [Indexed: 12/14/2022]
19
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
20
Taylor C, Pretzner B, Zahel T, Herwig C. Architectural and Technological Improvements to Integrated Bioprocess Models towards Real-Time Applications. Bioengineering (Basel) 2022;9:bioengineering9100534. [PMID: 36290502 PMCID: PMC9598293 DOI: 10.3390/bioengineering9100534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/02/2022] [Accepted: 10/06/2022] [Indexed: 11/16/2022]  Open
21
Nogueira IBR, Santana VV, Ribeiro AM, Rodrigues AE. Using Scientific Machine Learning to Develop Universal Differential Equation for Multicomponent Adsorption Separation Systems. CAN J CHEM ENG 2022. [DOI: 10.1002/cjce.24495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
22
Li S, Wang S. Establishment of Fuzzy Langmuir Adsorption Model and Prediction of Chromatographic Behavior. ADVANCED THEORY AND SIMULATIONS 2022. [DOI: 10.1002/adts.202200050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
23
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]
24
Subraveti SG, Li Z, Prasad V, Rajendran A. Can a computer “learn” nonlinear chromatography?: Physics-based deep neural networks for simulation and optimization of chromatographic processes. J Chromatogr A 2022;1672:463037. [DOI: 10.1016/j.chroma.2022.463037] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 04/04/2022] [Accepted: 04/05/2022] [Indexed: 11/30/2022]
25
Holistic Process Models: A Bayesian Predictive Ensemble Method for Single and Coupled Unit Operation Models. Processes (Basel) 2022. [DOI: 10.3390/pr10040662] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]  Open
26
Narayanan H, Sponchioni M, Morbidelli M. Integration and digitalization in the manufacturing of therapeutic proteins. Chem Eng Sci 2022. [DOI: 10.1016/j.ces.2021.117159] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
27
Bayer B, Duerkop M, Striedner G, Sissolak B. Model Transferability and Reduced Experimental Burden in Cell Culture Process Development Facilitated by Hybrid Modeling and Intensified Design of Experiments. Front Bioeng Biotechnol 2022;9:740215. [PMID: 35004635 PMCID: PMC8733703 DOI: 10.3389/fbioe.2021.740215] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 11/22/2021] [Indexed: 12/22/2022]  Open
28
Hybrid modeling — a key enabler towards realizing digital twins in biopharma? Curr Opin Chem Eng 2021. [DOI: 10.1016/j.coche.2021.100715] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
29
Ding C, Ierapetritou M. A novel framework of surrogate-based feasibility analysis for establishing design space of twin-column continuous chromatography. Int J Pharm 2021;609:121161. [PMID: 34624445 DOI: 10.1016/j.ijpharm.2021.121161] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 09/30/2021] [Accepted: 10/03/2021] [Indexed: 11/30/2022]
30
A Hybrid Modeling Framework for Membrane Separation Processes: Application to Lithium-Ion Recovery from Batteries. Processes (Basel) 2021. [DOI: 10.3390/pr9111939] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]  Open
31
Narayanan H, Dingfelder F, Condado Morales I, Patel B, Heding KE, Bjelke JR, Egebjerg T, Butté A, Sokolov M, Lorenzen N, Arosio P. Design of Biopharmaceutical Formulations Accelerated by Machine Learning. Mol Pharm 2021;18:3843-3853. [PMID: 34519511 DOI: 10.1021/acs.molpharmaceut.1c00469] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
32
Narayanan H, Luna M, Sokolov M, Arosio P, Butté A, Morbidelli M. Hybrid Models Based on Machine Learning and an Increasing Degree of Process Knowledge: Application to Capture Chromatographic Step. Ind Eng Chem Res 2021. [DOI: 10.1021/acs.iecr.1c01317] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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