Model‐based optimization of antibody galactosylation in CHO cell culture

Exerting control over the glycan moieties of antibody therapeutics is highly desirable from a product safety and batch‐to‐batch consistency perspective. Strategies to improve antibody productivity may compromise quality, while interventions for improving glycoform distribution can adversely affect c...

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Bibliographic Details
Published in:Biotechnology and bioengineering 2019-07, Vol.116 (7), p.1612-1626
Main Authors: Kotidis, Pavlos, Jedrzejewski, Philip, Sou, Si Nga, Sellick, Christopher, Polizzi, Karen, del Val, Ioscani Jimenez, Kontoravdi, Cleo
Format: Article
Language:English
Subjects:
Antibodies
antibody glycosylation
Cell culture
Cell density
Chinese hamster ovary (CHO) cells
Design
Design optimization
Feeding
Galactose
galactosylation
Glycan
Glycosylation
mathematical modeling
Metabolism
nucleotide sugars
process optimization
Product safety
Productivity
Uridine
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Summary:Exerting control over the glycan moieties of antibody therapeutics is highly desirable from a product safety and batch‐to‐batch consistency perspective. Strategies to improve antibody productivity may compromise quality, while interventions for improving glycoform distribution can adversely affect cell growth and productivity. Process design therefore needs to consider the trade‐off between preserving cellular health and productivity while enhancing antibody quality. In this work, we present a modeling platform that quantifies the impact of glycosylation precursor feeding – specifically that of galactose and uridine – on cellular growth, metabolism as well as antibody productivity and glycoform distribution. The platform has been parameterized using an initial training data set yielding an accuracy of ±5% with respect to glycoform distribution. It was then used to design an optimized feeding strategy that enhances the final concentration of galactosylated antibody in the supernatant by over 90% compared with the control without compromising the integral of viable cell density or final antibody titer. This work supports the implementation of Quality by Design towards higher‐performing bioprocesses. Exerting control over the glycan moieties of antibody therapeutics is highly desirable from a product safety and batch‐to‐batch consistency perspective. Strategies to improve antibody productivity may compromise quality, while interventions for improving glycoform distribution can adversely affect cell growth and productivity.
ISSN:0006-3592
1097-0290
DOI:10.1002/bit.26960