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Trends in Biotechnology
Volume 38 (8), 2020, Pages 846-856

Developing a Computational Framework To Advance Bioprocess Scale-Up

Guan Wang1, Cees Haringa2, Henk Noorman2,3, Ju Chu1, Yingping Zhuang1

State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology (ECUST), Shanghai, People’s Republic of China.

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, metabolomics, metabolic model, population heterogeneity, scale-down.

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