Boost dynamic protocols for producing mammalian biopharmaceuticals with intensified DoE—a practical guide to analyses with OLS and hybrid modeling
Introduction: For the implementation of robust bioprocesses, understanding of temporal cell behavior with respect to relevant inputs is crucial. Intensified Design of Experiments (iDoE) is an efficient tool to assess the joint influence of input parameters by including intra-experimental changes.Met...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Chemical Engineering |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fceng.2022.1044245/full |
| _version_ | 1797961500066840576 |
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| author | V. Nold L. Junghans B. Bayer L. Bisgen M. Duerkop R. Drerup B. Presser T. Schwab E. Bluhmki S. Wieschalka B. Knapp |
| author_facet | V. Nold L. Junghans B. Bayer L. Bisgen M. Duerkop R. Drerup B. Presser T. Schwab E. Bluhmki S. Wieschalka B. Knapp |
| author_sort | V. Nold |
| collection | DOAJ |
| description | Introduction: For the implementation of robust bioprocesses, understanding of temporal cell behavior with respect to relevant inputs is crucial. Intensified Design of Experiments (iDoE) is an efficient tool to assess the joint influence of input parameters by including intra-experimental changes.Methods: We applied iDoE to the production phase of a monoclonal antibody in a mammalian bioprocess. The multidimensional design space spanned by temperature, dissolved oxygen (DO), timing of change, and growth category was investigated in 12 cultivations. We built ordinary least squares (OLS) and hybrid models (HM) on the iDoE-data, validated them with classical DoE (cDoE)-derived data, and used the models as in silico representation for process optimization.Results: If the complexity of interactions between changing setpoints of inputs is sufficiently captured during planning and modeling, iDoE proved to be valid for characterizing the mammalian biopharmaceutical production phase. For local behavior and flexible composition of optimization goals, OLS regressions can easily be implemented. To predict global and interconnected dynamics while incorporating mass balances, HM holds potential.Discussion: iDoE will boost protocols that optimize inputs for different bioprocess phases. The described key aspects of OLS- and HM-based analyses of iDoE-data shall guide future applications during manufacturing. |
| first_indexed | 2024-04-11T01:00:09Z |
| format | Article |
| id | doaj.art-bfe81ae0121042d9be6a35983a3dbd9c |
| institution | Directory Open Access Journal |
| issn | 2673-2718 |
| language | English |
| last_indexed | 2024-04-11T01:00:09Z |
| publishDate | 2023-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Chemical Engineering |
| spelling | doaj.art-bfe81ae0121042d9be6a35983a3dbd9c2023-01-04T18:25:42ZengFrontiers Media S.A.Frontiers in Chemical Engineering2673-27182023-01-01410.3389/fceng.2022.10442451044245Boost dynamic protocols for producing mammalian biopharmaceuticals with intensified DoE—a practical guide to analyses with OLS and hybrid modelingV. Nold0L. Junghans1B. Bayer2L. Bisgen3M. Duerkop4R. Drerup5B. Presser6T. Schwab7E. Bluhmki8S. Wieschalka9B. Knapp10Development Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, GermanyDevelopment Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, GermanyNovasign GmbH, Muthgasse, Vienna, AustriaDevelopment Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, GermanyNovasign GmbH, Muthgasse, Vienna, AustriaDevelopment Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, GermanyDevelopment Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, GermanyDevelopment Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, GermanyDevelopment Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, GermanyDevelopment Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, GermanyDevelopment Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, GermanyIntroduction: For the implementation of robust bioprocesses, understanding of temporal cell behavior with respect to relevant inputs is crucial. Intensified Design of Experiments (iDoE) is an efficient tool to assess the joint influence of input parameters by including intra-experimental changes.Methods: We applied iDoE to the production phase of a monoclonal antibody in a mammalian bioprocess. The multidimensional design space spanned by temperature, dissolved oxygen (DO), timing of change, and growth category was investigated in 12 cultivations. We built ordinary least squares (OLS) and hybrid models (HM) on the iDoE-data, validated them with classical DoE (cDoE)-derived data, and used the models as in silico representation for process optimization.Results: If the complexity of interactions between changing setpoints of inputs is sufficiently captured during planning and modeling, iDoE proved to be valid for characterizing the mammalian biopharmaceutical production phase. For local behavior and flexible composition of optimization goals, OLS regressions can easily be implemented. To predict global and interconnected dynamics while incorporating mass balances, HM holds potential.Discussion: iDoE will boost protocols that optimize inputs for different bioprocess phases. The described key aspects of OLS- and HM-based analyses of iDoE-data shall guide future applications during manufacturing.https://www.frontiersin.org/articles/10.3389/fceng.2022.1044245/fullintensified design of experimentsmammalian biopharmaceutical productionupstream process modelingmultivariate optimizationbioprocess phases |
| spellingShingle | V. Nold L. Junghans B. Bayer L. Bisgen M. Duerkop R. Drerup B. Presser T. Schwab E. Bluhmki S. Wieschalka B. Knapp Boost dynamic protocols for producing mammalian biopharmaceuticals with intensified DoE—a practical guide to analyses with OLS and hybrid modeling Frontiers in Chemical Engineering intensified design of experiments mammalian biopharmaceutical production upstream process modeling multivariate optimization bioprocess phases |
| title | Boost dynamic protocols for producing mammalian biopharmaceuticals with intensified DoE—a practical guide to analyses with OLS and hybrid modeling |
| title_full | Boost dynamic protocols for producing mammalian biopharmaceuticals with intensified DoE—a practical guide to analyses with OLS and hybrid modeling |
| title_fullStr | Boost dynamic protocols for producing mammalian biopharmaceuticals with intensified DoE—a practical guide to analyses with OLS and hybrid modeling |
| title_full_unstemmed | Boost dynamic protocols for producing mammalian biopharmaceuticals with intensified DoE—a practical guide to analyses with OLS and hybrid modeling |
| title_short | Boost dynamic protocols for producing mammalian biopharmaceuticals with intensified DoE—a practical guide to analyses with OLS and hybrid modeling |
| title_sort | boost dynamic protocols for producing mammalian biopharmaceuticals with intensified doe a practical guide to analyses with ols and hybrid modeling |
| topic | intensified design of experiments mammalian biopharmaceutical production upstream process modeling multivariate optimization bioprocess phases |
| url | https://www.frontiersin.org/articles/10.3389/fceng.2022.1044245/full |
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