Dynamic Optimization for Monoclonal Antibody Production

Morten Wahlgreen Kaysfeld, Deepak Kumar, Marcus Krogh Nielsen, John Bagterp Jørgensen*

*Corresponding author for this work

Research output: Contribution to journalConference articleResearchpeer-review

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This paper presents a dynamic optimization numerical case study for Monoclonal Antibody (mAb) production. The fermentation is conducted in a continuous perfusion reactor. We represent the existing model in terms of a general modeling methodology well-suited for simulation and optimization. The model consists of six ordinary differential equations (ODEs) for the non-constant volume and the five components in the reactor. We extend the model with a glucose inhibition term to make the model feasible for optimization case studies. We formulate an optimization problem in terms of an optimal control problem (OCP) and consider four different setups for optimization. Compared to the base case, the optimal operation of the perfusion reactor increases the mAb yield with 44% when samples are taken from the reactor and with 52% without sampling. Additionally, our results show that multiple optimal feeding trajectories exist and that full glucose utilization can be forced without loss of mAb formation.

Original languageEnglish
Issue number2
Pages (from-to)6229-6234
Publication statusPublished - 2023
Event22nd IFAC World Congress
- Pacific Convention Plaza Yokohama, Yokohama, Japan
Duration: 9 Jul 202314 Jul 2023
Conference number: 22


Conference22nd IFAC World Congress
LocationPacific Convention Plaza Yokohama
SponsorAzbil Corporation, Fujita Corporation, Hitachi, Ltd., Kumagai Gumi Co., Ltd., The Society of Instrument and Control Engineers (SICE)


  • Monoclonal antibody production
  • Optimal control
  • Process modeling
  • Perfusion reactor
  • Fermentation


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