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PMID: 32493657 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Review

Developing a Computational Framework To Advance Bioprocess Scale-Up.

Trends in biotechnology ·Vol. 38 ·No. 8 ·2020-00-00 ·页码 846-856

Wang G, Haringa C, Noorman H, Chu J, Zhuang Y

Abstract

Bioprocess scale-up is a critical step in process development. However, loss of production performance upon scaling-up, including reduced titer, yield, or productivity, has often been observed, hindering the commercialization of biotech innovations. Recent developments in scale-down studies assisted by computational fluid dynamics (CFD) and powerful stimulus-response metabolic models afford better process prediction and evaluation, enabling faster scale-up with minimal losses. In the future, an ideal bioprocess design would be guided by an in silico model that integrates cellular physiology (spatiotemporal multiscale cellular models) and fluid dynamics (CFD models). Nonetheless, there are challenges associated with both establishing predictive metabolic models and CFD coupling. By highlighting these and providing possible solutions here, we aim to advance the development of a computational framework to accelerate bioprocess scale-up.

Keywords
computational fluid dynamics industrial metabolic model metabolomics population heterogeneity scale-down
MeSH 主题词
Bioreactors Computational Chemistry/trends Computer Simulation Humans Hydrodynamics
作者与单位
共 5 位作者,点击展开单位 / ORCID
Wang Guan
State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology (ECUST), Shanghai, People's Republic of China. Electronic address: [email protected].
Haringa Cees
DSM Biotechnology Center, Delft, The Netherlands.
Noorman Henk
DSM Biotechnology Center, Delft, The Netherlands; Department of Biotechnology, Delft University of Technology, Delft, The Netherlands.
Chu Ju
State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology (ECUST), Shanghai, People's Republic of China.
Zhuang Yingping
State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology (ECUST), Shanghai, People's Republic of China. Electronic address: [email protected].
Article Info
Journal
Trends in biotechnology
Abbr.
Trends Biotechnol
ISSN
1879-3096
Published
2020-00-00
电子出版
2020-00-25
页码
846-856
Language
English
Country/Region
England
NLM ID
8310903
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