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Cited by 42Viral Infectious Diseases and Gene Expression in InsectsMicrobial Metabolic Engineering and BioproductionGlycosylation and Glycoproteins Research

Synergising stoichiometric modelling with artificial neural networks to predict antibody glycosylation patterns in Chinese hamster ovary cells

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Antonakoudis, Athanasios, Strain, Benjamin, Barbosa, Rodrigo, Jimenez del Val, Ioscani, Kontoravdi, Cleo·2021·Computers & Chemical Engineering
DOI 10.1016/j.compchemeng.2021.107471
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Crossref · 10.1016/j.compchemeng.2021.107471

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5 of 5 references verified0 citation errors · 0 not checkable

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  • Two-step frameworks for indirect NSD inference rely on pseudo-steady-state assumptions and therefore do not explicitly capture the transient dynamics of intracellular NSD pools over the course of a fed-batch culture.

    “Although this approach enables indirect inference of NSDs from extracellular data and alleviates some parametrisation challenges, it relies on pseudo-steadystate assumptions.It therefore does not explicitly capture the transient dynamics of intracellular NSD pools over the course of a fed-batch culture.”

    From Soft sensing of intracellular states for CHO cell bioprocessing with Ensemble Kalman Filters (2026) · cites this paper as [28]

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Authors
Antonakoudis, A., Strain, B., Barbosa, R., Jimenez del Val, I., & Kontoravdi, C.
Affiliations
Imperial College London (GB)
Corresponding author
Kontoravdi, Cleo
ORCID
Venue
Computers & Chemical Engineering
Publisher
Elsevier BV
Published
2021-11
Volume
154
Pages
107471
ISSN
0098-1354 (ISSN-L)
DOI
10.1016/j.compchemeng.2021.107471
OpenAlex
W3193910802
Cited by
42
References
5
Citations by year
2026: 4 · 2025: 8 · 2024: 11 · 2023: 11 · 2022: 8
FWCI
2.35
Type
journal article
Language
en
Open access
Licence
Locations
  • Computers & Chemical Engineering (publishedVersion)
  • Spiral (Imperial College London) (submittedVersion, cc-by-nc-nd)
Funders
  • Science Foundation Ireland (12/RC/2275_P2)
  • GlaxoSmithKline
  • Engineering and Physical Sciences Research Council
  • Biotechnology and Biological Sciences Research Council
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Viral Infectious Diseases and Gene Expression in Insects
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Glycosylation and Glycoproteins Research
Keywords
antibody glycosylation, artificial neural networks, hybrid process models, monoclonal antibodies, in-process quality control, critical quality attributes, biologic therapy

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