@article{HelgersHengelbrockRosengartenetal.2022,
  author    = {Heribert Helgers and Alina Hengelbrock and Jamila Franca Rosengarten and J{\"o}rn Stitz and Axel Schmidt and Jochen Strube},
  title     = {Towards Autonomous Process Control—Digital Twin for HIV-Gag VLP Production in HEK293 Cells Using a Dynamic Metabolic Model},
  series   = {Processes},
  volume    = {10},
  number    = {10},
  editor    = {Tao Sun},
  publisher = {MDPI},
  issn      = {2227-9717},
  doi       = {10.3390/pr10102015},
  url       = {https://nbn-resolving.org/urn:nbn:de:hbz:832-epub4-20649},
  year      = {2022},
  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.},
  language  = {en}
}