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Journal article : Review

Systematic review and data-driven insights into CHO cell engineering for next-generation antibody production

Abstract:
Chinese hamster ovary (CHO) cells remain the dominant platform for therapeutic antibody and biopharmaceutical production, yet productivity bottlenecks persist, particularly for complex molecules. To identify overarching trends in host cell optimization, a systematic review and quantitative cross-study analysis of 164 publications (2011-2024) reporting CHO cell engineering strategies with effects on titer or specific productivity was conducted. Data from 466 engineered targets were extracted and analyzed by strategy, pathway, and production context. The field - driven largely by antibody production - has evolved from simple overexpression toward CRISPR-mediated knockouts, while combinatorial approaches, and engineering of nuclear, epigenetic, and apoptotic/proliferative targets achieved the greatest gains. Despite technological advances, reported improvement folds remained stable, highlighting the need for pathway-informed, multi-target engineering. Future progress in predictive modeling of engineering strategies will depend on standardized models and structured datasets. This review provides a data-driven framework for rational CHO design to support next-generation biotherapeutic production.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1080/19420862.2026.2615475

Authors

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Role:
Author
ORCID:
0009-0002-3738-7563
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Role:
Author
ORCID:
0000-0003-1987-2020
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Institution:
University of Oxford
Division:
MSD
Department:
Pathology Dunn School
Sub department:
Pathology Dunn School
Role:
Author
ORCID:
0000-0002-2473-1145


Publisher:
Taylor and Francis Group
Journal:
mAbs More from this journal
Volume:
18
Issue:
1
Pages:
2615475
Publication date:
2026-01-18
Acceptance date:
2026-01-06
DOI:
EISSN:
1942-0870
ISSN:
1942-0862
Pmid:
41548093


Language:
English
Keywords:
Subtype:
Review
Pubs id:
2363287
UUID:
uuid_a8698aad-1f85-4ab6-8433-c063fecd52d0
Local pid:
pubs:2363287
Source identifiers:
3692744
Deposit date:
2026-01-26
ARK identifier:
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