Model-assisted Design of Experiments as a concept for knowledge-based bioprocess development

Bioprocess and Biosystems Engineering
Johannes MöllerRalf Pörtner

Abstract

Design of Experiments methods offer systematic tools for bioprocess development in Quality by Design, but their major drawback is the user-defined choice of factor boundary values. This can lead to several iterative rounds of time-consuming and costly experiments. In this study, a model-assisted Design of Experiments concept is introduced for the knowledge-based reduction of boundary values. First, the parameters of a mathematical process model are estimated. Second, the investigated factor combinations are simulated instead of experimentally derived and a constraint-based evaluation and optimization of the experimental space can be performed. The concept is discussed for the optimization of an antibody-producing Chinese hamster ovary batch and bolus fed-batch process. The same optimal process strategies were found if comparing the model-assisted Design of Experiments (4 experiments each) and traditional Design of Experiments (16 experiments for batch and 29 experiments for fed-batch). This approach significantly reduces the number of experiments needed for knowledge-based bioprocess development.

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Citations

Jul 26, 2019·Biotechnology and Bioengineering·Johannes MöllerUwe Jandt
Feb 6, 2020·Biotechnology Journal·Benjamin BayerMark Duerkop
Sep 6, 2019·Biotechnology Journal·Harini NarayananMichael Sokolov
Sep 19, 2019·BioTechniques·Vincent WiegmannFrank Baganz
Jan 21, 2021·Bioprocess and Biosystems Engineering·André MoserJohannes Möller
Nov 17, 2020·Frontiers in Plant Science·Daniel TuséJohannes Felix Buyel
Mar 16, 2021·Engineering in Life Sciences·Johannes MöllerAn-Ping Zeng
Jun 21, 2021·European Journal of Pharmaceutics and Biopharmaceutics : Official Journal of Arbeitsgemeinschaft Für Pharmazeutische Verfahrenstechnik E.V·Alice KasemiireEric Ziemons

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