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On-Line Reoptimization of Mammalian Fed-Batch Culture Using a Nonlinear Model Predictive Controller

New Generation Computing (2023)Cite this article

Abstract

Fed-batch culture is widely used in biopharmaceutical production owing to its superior productivity; however, optimizing feeding trajectories remains a challenge. In this study, we investigated the feasibility and benefits of using a nonlinear model predictive controller (NLMPC) for on-line reoptimization in mammalian fed-batch culture to compensate for process-model mismatch (PMM). We simulated a monoclonal antibody production process using a standard kinetic model and deliberately introduced PMM via parameter errors. The NLMPC optimized feeding trajectories for a single-feed case, in which a mixture of glucose and glutamine is fed, and for a multiple-feed case, in which glucose and glutamine are fed independently. Our results demonstrate that on-line reoptimization successfully compensates for PMM, improving the final product mass compared to off-line optimization. This study highlights the potential of on-line reoptimization using NLMPCs in mammalian fed-batch culture, which can enhance product yield even in the presence of insufficient parameter estimation.

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Code Availability

The computer code used in this study are available at GitHub (https://github.com/kkunida/202212_Ohkubo_bioRxiv.git).

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Acknowledgements

We would like to thank Dr. Masaaki Nagahara from the University of Kitakyushu for helpful technical comments. We thank Editage (www.editage.com) for English language editing. This study was supported by the Next Generation Interdisciplinary Research Project of Nara Institute of Science and Technology (NAIST) and AMED under Grant Numbers JP23wm0425008.

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Authors and Affiliations

  1. Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Nara, 8916-5, Japan

    Tomoki Ohkubo, Yuichi Sakumura & Katsuyuki Kunida

  2. Data Science Center, Nara Institute of Science and Technology, Ikoma, Nara, 8916-5, Japan

    Yuichi Sakumura

  3. School of Medicine, Fujita Health University, Toyoake, Aichi, 470-1192, Japan

    Katsuyuki Kunida

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  1. Tomoki Ohkubo
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Correspondence to Katsuyuki Kunida.

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Ohkubo, T., Sakumura, Y. & Kunida, K. On-Line Reoptimization of Mammalian Fed-Batch Culture Using a Nonlinear Model Predictive Controller. New Gener. Comput. (2023). https://doi.org/10.1007/s00354-023-00235-0

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