Automated shape and process parameter optimization for scaling up geometrically non-similar bioreactors

Seidel, Stefan; Mozaffari, Fruhar; Maschke, Rüdiger W.; Kraume, Matthias; Eibl-Schindler, Regine; Eibl, Dieter

doi:10.3390/pr11092703

Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-29323

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DC Field	Value	Language
dc.contributor.author	Seidel, Stefan	-
dc.contributor.author	Mozaffari, Fruhar	-
dc.contributor.author	Maschke, Rüdiger W.	-
dc.contributor.author	Kraume, Matthias	-
dc.contributor.author	Eibl-Schindler, Regine	-
dc.contributor.author	Eibl, Dieter	-
dc.date.accessioned	2023-12-08T11:45:12Z	-
dc.date.available	2023-12-08T11:45:12Z	-
dc.date.issued	2023-09	-
dc.identifier.issn	2227-9717	de_CH
dc.identifier.uri	https://digitalcollection.zhaw.ch/handle/11475/29323	-
dc.description.abstract	Scaling bioprocesses remains a major challenge. Since it is physically impossible to increase all process parameters equally, a suitable scale-up strategy must be selected for a successful bioprocess. One of the most widely used criteria when scaling up bioprocesses is the specific power input. However, this represents only an average value. This study aims to determine the Kolmogorov length scale distribution by means of computational fluid dynamics (CFD) and to use it as an alternative scale-up criterion for geometrically non-similar bioreactors for the first time. In order to obtain a comparable Kolmogorov length scale distribution, an automated geometry and process parameter optimization was carried out using the open-source tools OpenFOAM and DAKOTA. The Kolmogorov–Smirnov test statistic was used for optimization. A HEK293-F cell expansion (batch mode) from benchtop (Infors Minifors 2 with 4 L working volume) to pilot scale (D-DCU from Sartorius with 30 L working volume) was carried out. As a reference cultivation, the classical scale-up approach with constant specific power input (233 W m−3) was used, where a maximum viable cell density (VCDmaxmax) of 5.02·1065.02·106 cells mL−1 was achieved (VCDmaxmax at laboratory scale 5.77·1065.77·106 cells mL−1). Through the automated optimization of the stirrer geometry (three parameters), position and speed, comparable cultivation results were achieved as in the small scale with a maximum VCD of 5.60·1065.60·106 cells mL−1. In addition, even on the pilot scale, cell aggregate size distribution was seen to strictly follow a geometric distribution and can be predicted with the help of CFD with the previously published correlation.	de_CH
dc.language.iso	en	de_CH
dc.publisher	MDPI	de_CH
dc.relation.ispartof	Processes	de_CH
dc.rights	http://creativecommons.org/licenses/by/4.0/	de_CH
dc.subject	Biochemical engineering	de_CH
dc.subject	Scale-up	de_CH
dc.subject	Optimization	de_CH
dc.subject	Open-source	de_CH
dc.subject	Kolmogorov length scale	de_CH
dc.subject	Hydrodynamic stress	de_CH
dc.subject	Energy dissipation rate	de_CH
dc.subject	HEK293	de_CH
dc.subject	Computational fluid dynamics (CFD)	de_CH
dc.subject.ddc	660: Technische Chemie	de_CH
dc.title	Automated shape and process parameter optimization for scaling up geometrically non-similar bioreactors	de_CH
dc.type	Beitrag in wissenschaftlicher Zeitschrift	de_CH
dcterms.type	Text	de_CH
zhaw.departement	Life Sciences und Facility Management	de_CH
zhaw.organisationalunit	Institut für Chemie und Biotechnologie (ICBT)	de_CH
dc.identifier.doi	10.3390/pr11092703	de_CH
dc.identifier.doi	10.21256/zhaw-29323	-
zhaw.funding.eu	No	de_CH
zhaw.issue	9	de_CH
zhaw.originated.zhaw	Yes	de_CH
zhaw.pages.start	2703	de_CH
zhaw.publication.status	publishedVersion	de_CH
zhaw.volume	11	de_CH
zhaw.publication.review	Peer review (Publikation)	de_CH
zhaw.author.additional	No	de_CH
zhaw.display.portrait	Yes	de_CH
zhaw.monitoring.costperiod	2023	de_CH
zhaw.relation.references	https://github.com/seideste/Automated-shape-and-process-parameter-optimization	de_CH
Appears in collections:	Publikationen Life Sciences und Facility Management

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Seidel, S., Mozaffari, F., Maschke, R. W., Kraume, M., Eibl-Schindler, R., & Eibl, D. (2023). Automated shape and process parameter optimization for scaling up geometrically non-similar bioreactors. Processes, 11(9), 2703. https://doi.org/10.3390/pr11092703

Seidel, S. et al. (2023) ‘Automated shape and process parameter optimization for scaling up geometrically non-similar bioreactors’, Processes, 11(9), p. 2703. Available at: https://doi.org/10.3390/pr11092703.

S. Seidel, F. Mozaffari, R. W. Maschke, M. Kraume, R. Eibl-Schindler, and D. Eibl, “Automated shape and process parameter optimization for scaling up geometrically non-similar bioreactors,” Processes, vol. 11, no. 9, p. 2703, Sep. 2023, doi: 10.3390/pr11092703.

SEIDEL, Stefan, Fruhar MOZAFFARI, Rüdiger W. MASCHKE, Matthias KRAUME, Regine EIBL-SCHINDLER und Dieter EIBL, 2023. Automated shape and process parameter optimization for scaling up geometrically non-similar bioreactors. Processes. September 2023. Bd. 11, Nr. 9, S. 2703. DOI 10.3390/pr11092703

Seidel, Stefan, Fruhar Mozaffari, Rüdiger W. Maschke, Matthias Kraume, Regine Eibl-Schindler, and Dieter Eibl. 2023. “Automated Shape and Process Parameter Optimization for Scaling up Geometrically Non-Similar Bioreactors.” Processes 11 (9): 2703. https://doi.org/10.3390/pr11092703.

Seidel, Stefan, et al. “Automated Shape and Process Parameter Optimization for Scaling up Geometrically Non-Similar Bioreactors.” Processes, vol. 11, no. 9, Sept. 2023, p. 2703, https://doi.org/10.3390/pr11092703.