Towards Autonomous Process Control—Digital Twin for HIV-Gag VLP Production in HEK293 Cells Using a Dynamic Metabolic Model

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Helgers, H.; Hengelbrock, A.; Rosengarten, J.F.; Stitz, J.; Schmidt, A. et al.: Towards Autonomous Process Control—Digital Twin for HIV-Gag VLP Production in HEK293 Cells Using a Dynamic Metabolic Model. In: Processes : open access journal 10 (2022), Nr. 10, 2015. DOI: https://doi.org/10.3390/pr10102015

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Sum total of downloads: 42




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Abstract: 
Despite intensive research over the last three decades, it has not yet been possible to bring an effective vaccine against human immunodeficiency virus (HIV) and the resulting acquired immunodeficiency syndrome (AIDS) to market. Virus-like particles (VLP) are a promising approach for efficient and effective vaccination and could play an important role in the fight against HIV. For example, HEK293 (human embryo kidney) cells can be used to produce virus-like particles. In this context, given the quality-by-design (QbD) concept for manufacturing, a digital twin is of great importance for the production of HIV-Gag-formed VLPs. In this work, a dynamic metabolic model for the production of HIV-Gag VLPs was developed and validated. The model can represent the VLP production as well as the consumption or formation of all important substrates and metabolites. Thus, in combination with already described process analytical technology (PAT) methods, the final step towards the implementation of a digital twin for process development and design, as well as process automation, was completed.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2022
Appears in Collections:Naturwissenschaftliche Fakultät

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pos. country downloads
total perc.
1 image of flag of United States United States 17 40.48%
2 image of flag of Germany Germany 17 40.48%
3 image of flag of United Kingdom United Kingdom 3 7.14%
4 image of flag of Norway Norway 1 2.38%
5 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 1 2.38%
6 image of flag of Indonesia Indonesia 1 2.38%
7 image of flag of France France 1 2.38%
8 image of flag of Czech Republic Czech Republic 1 2.38%

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