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Constrained global sensitivity analysis for bioprocess design space identification

Kotidis, Pavlos, Demis, Panagiotis, Goey, Cher H., Correa, Elisa, McIntosh, Calum, Trepekli, Stefania, Shah, Nilay, Klymenko, Oleksiy V. and Kontoravdi, Cleo (2019) Constrained global sensitivity analysis for bioprocess design space identification Computers and Chemical Engineering, 125. pp. 558-568.

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The manufacture of protein-based therapeutics presents unique challenges due to limited control over the biotic phase. This typically gives rise to a wide range of protein structures of varying safety and in vivo efficacy. Herein we propose a computational methodology, enabled by the application of constrained Global Sensitivity Analysis, for efficiently exploring the operating range of process inputs in silico and identifying a design space that meets output constraints. The methodology was applied to an antibody- producing Chinese hamster ovary (CHO) cell culture system: we explored > 80 0 0 feeding strategies to identify a subset of manufacturing conditions that meet constraints on antibody titre and glycan distri- bution as an attribute of product quality. Our computational findings were then verified experimentally, confirming the applicability of this approach to a challenging production system. We envisage that this methodology can significantly expedite bioprocess development and increase operational flexibility.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :
Kotidis, Pavlos
Goey, Cher H.
Correa, Elisa
McIntosh, Calum
Trepekli, Stefania
Shah, Nilay
Klymenko, Oleksiy
Kontoravdi, Cleo
Date : 9 June 2019
Funders : The Engineering and Physical Sciences Research Council (EPSRC), Biotechnology and Biological Sciences Research Council, BioProNET network in Industrial Biotechnology
DOI : 10.1016/j.compchemeng.2019.01.022
Copyright Disclaimer : © 2019 Elsevier Ltd. All rights reserved.
Uncontrolled Keywords : Monoclonal antibodies; Glycosylation; Chinese hamster ovary cells; Design space identification; Global sensitivity analysis; Kinetic modeling
Depositing User : Diane Maxfield
Date Deposited : 05 Sep 2019 14:29
Last Modified : 05 Sep 2019 14:29

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