Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-19791
Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: Model uncertainty-based evaluation of process strategies during scale-up of biopharmaceutical processes
Authors: Möller, Johannes
Hernández Rodríguez, Tanja
Müller, Jan
Arndt, Lukas
Kuchemüller, Kim B.
Frahm, Björn
Eibl-Schindler, Regine
Eibl, Dieter
Pörtner, Ralf
et. al: No
DOI: 10.1016/j.compchemeng.2019.106693
10.21256/zhaw-19791
Published in: Computers & Chemical Engineering
Volume(Issue): 134
Page(s): 106693
Issue Date: 23-Dec-2019
Publisher / Ed. Institution: Elsevier
ISSN: 0098-1354
1873-4375
Language: English
Subjects: Monte Carlo method; Process modeling; Parameter distribution; Process validation; Model-assisted design of experiments; Quality by design
Subject (DDC): 660: Chemical engineering
Abstract: Reliable scale-up of biopharmaceutical production processes is key in Quality by Design. In this study, a model-based workflow is described to evaluate the bioprocess dynamics during process transfer and scale-up computationally. First, a mathematical model describes the bioprocess dynamics of different state variables (e.g., cell density, titer). Second, the model parameter probability distributions are determined at different scales due to measurement uncertainty. Third, the quantified parameter distributions are statistically compared to evaluate if the process dynamics have been changed. This workflow was tested for the scale-up of an antibody-producing CHO fed-batch process. Significant differences were identified between the process development (30 ml) and implementation (250 ml) scale, and the feeding strategy was validated using model-assisted Design of Experiments. Then, the validated process strategy was successfully scaled up to 2 l laboratory and 50 l pilot scale. In summary, the proposed workflow enables a knowledge-driven evaluation tool for bioprocess development.
URI: https://digitalcollection.zhaw.ch/handle/11475/19791
Fulltext version: Submitted version
License (according to publishing contract): Licence according to publishing contract
Departement: Life Sciences and Facility Management
Organisational Unit: Institute of Chemistry and Biotechnology (ICBT)
Appears in collections:Publikationen Life Sciences und Facility Management

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Möller, J., Hernández Rodríguez, T., Müller, J., Arndt, L., Kuchemüller, K. B., Frahm, B., Eibl-Schindler, R., Eibl, D., & Pörtner, R. (2019). Model uncertainty-based evaluation of process strategies during scale-up of biopharmaceutical processes. Computers & Chemical Engineering, 134, 106693. https://doi.org/10.1016/j.compchemeng.2019.106693
Möller, J. et al. (2019) ‘Model uncertainty-based evaluation of process strategies during scale-up of biopharmaceutical processes’, Computers & Chemical Engineering, 134, p. 106693. Available at: https://doi.org/10.1016/j.compchemeng.2019.106693.
J. Möller et al., “Model uncertainty-based evaluation of process strategies during scale-up of biopharmaceutical processes,” Computers & Chemical Engineering, vol. 134, p. 106693, Dec. 2019, doi: 10.1016/j.compchemeng.2019.106693.
MÖLLER, Johannes, Tanja HERNÁNDEZ RODRÍGUEZ, Jan MÜLLER, Lukas ARNDT, Kim B. KUCHEMÜLLER, Björn FRAHM, Regine EIBL-SCHINDLER, Dieter EIBL und Ralf PÖRTNER, 2019. Model uncertainty-based evaluation of process strategies during scale-up of biopharmaceutical processes. Computers & Chemical Engineering. 23 Dezember 2019. Bd. 134, S. 106693. DOI 10.1016/j.compchemeng.2019.106693
Möller, Johannes, Tanja Hernández Rodríguez, Jan Müller, Lukas Arndt, Kim B. Kuchemüller, Björn Frahm, Regine Eibl-Schindler, Dieter Eibl, and Ralf Pörtner. 2019. “Model Uncertainty-Based Evaluation of Process Strategies during Scale-up of Biopharmaceutical Processes.” Computers & Chemical Engineering 134 (December): 106693. https://doi.org/10.1016/j.compchemeng.2019.106693.
Möller, Johannes, et al. “Model Uncertainty-Based Evaluation of Process Strategies during Scale-up of Biopharmaceutical Processes.” Computers & Chemical Engineering, vol. 134, Dec. 2019, p. 106693, https://doi.org/10.1016/j.compchemeng.2019.106693.


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