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Biotechnology and Bioengineering
Article . 2022 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
https://doi.org/10.22541/au.16...
Article . 2022 . Peer-reviewed
Data sources: Crossref
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Mechanistic modeling of viral particle production

Authors: Christopher T. Canova; Pavan K. Inguva; Richard D. Braatz;

Mechanistic modeling of viral particle production

Abstract

AbstractViral systems such as wild‐type viruses, viral vectors, and virus‐like particles are essential components of modern biotechnology and medicine. Despite their importance, the commercial‐scale production of viral systems remains highly inefficient for multiple reasons. Computational strategies are a promising avenue for improving process development, optimization, and control, but require a mathematical description of the system. This article reviews mechanistic modeling strategies for the production of viral particles, both at the cellular and bioreactor scales. In many cases, techniques and models from adjacent fields such as epidemiology and wild‐type viral infection kinetics can be adapted to construct a suitable process model. These process models can then be employed for various purposes such as in‐silico testing of novel process operating strategies and/or advanced process control.

Country
United States
Keywords

Bioreactors, Virus Diseases, Virion, Humans, Biotechnology

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    12
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Average
Top 10%
Green
hybrid