Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.2600
Publisher DOI: 10.1016/j.compchemeng.2019.106693
Title: Model uncertainty-based evaluation of process strategies during scale-up of biopharmaceutical processes
Language: English
Authors: Möller, Johannes 
Hernández Rodríguez, Tanja 
Müller, Jan 
Arndt, Lukas 
Kuchemüller, Kim Beatrice 
Frahm, Björn 
Eibl, Regine 
Eibl, Dieter 
Pörtner, Ralf  
Issue Date: 4-Mar-2020
Publisher: Elsevier Science
Source: Computers and Chemical Engineering (134): 106693 (2020-03-04)
Journal or Series Name: Computers & chemical engineering 
Abstract (english): 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 de- termined at different scales due to measurement uncertainty. Third, the quantified parameter distribu- tions 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. ©2020 Elsevier Ltd. All rights reserved.
URI: http://hdl.handle.net/11420/4596
DOI: 10.15480/882.2600
ISSN: 0098-1354
Institute: Bioprozess- und Biosystemtechnik V-1 
Type: (wissenschaftlicher) Artikel
Funded by: German Federal Ministry of Education and Research, projects: 031 B0305, 031 B0577A
Project: IBÖM04:mDoE-Toolbox2-Neue mDoE Software-Toolbox zur modellgestützten Optimierung biotechnologischer Prozesse 
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