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Cited by 171

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

Apoptosis: A mammalian cell bioprocessing perspective

Open access
Grilo, Antonio L., Mantalaris, Athanasios·2019·Biotechnology Advances

Abstract

Apoptosis is a form of programmed and controlled cell death that accounts for the majority of cellular death in bioprocesses. Cell death affects culture longevity and product quality; it is instigated by several stresses experienced by the cells within a bioreactor. Understanding the factors that cause apoptosis as well as developing strategies that can protect cells is crucial for robust bioprocess development. This review aims to a) address apoptosis from a bioprocess perspective; b) describe the significant apoptotic mechanisms linking them to the most relevant stresses encountered in bioreactors; c) discuss the design of operating conditions in order to avoid cell death; d) focus on industrially relevant cell lines; and e) present anti-apoptosis strategies including cell engineering and model-based optimization of bioprocesses. In addition, the importance of apoptosis in quality-by-design bioprocess development from clone screening to production scale are highlighted.

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Crossref · 10.1016/j.biotechadv.2019.02.012

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Metadata

Authors
Grilo, A. L., & Mantalaris, A.
Venue
Biotechnology Advances
Publisher
Elsevier BV
Published
2019-05
Volume
37
Issue
3
Pages
459-475
ISSN
0734-9750 (ISSN-L)
OpenAlex
W2915763610
Cited by
171
References
11
FWCI
6.87
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Apoptosis: A mammalian cell bioprocessing perspective. https://app.cochat.ai/papers/10.1016/j.biotechadv.2019.02.012
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Grilo, A. L., & Mantalaris, A. (2019). Apoptosis: A mammalian cell bioprocessing perspective. Biotechnology Advances. https://doi.org/10.1016/j.biotechadv.2019.02.012

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.