Optimization of a pH-shift control strategy for producing monoclonal antibodies in Chinese hamster ovary cell cultures using a pH-dependent dynamic model

Tomoharu Hogiri, Hiroshi Tamashima, Akitoshi Nishizawa, Masahiro Okamoto

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

To optimize monoclonal antibody (mAb) production in Chinese hamster ovary cell cultures, culture pH should be temporally controlled with high resolution. In this study, we propose a new pH-dependent dynamic model represented by simultaneous differential equations including a minimum of six system component, depending on pH value. All kinetic parameters in the dynamic model were estimated using an evolutionary numerical optimization (real-coded genetic algorithm) method based on experimental time-course data obtained at different pH values ranging from 6.6 to 7.2. We determined an optimal pH-shift schedule theoretically. We validated this optimal pH-shift schedule experimentally and mAb production increased by approximately 40% with this schedule. Throughout this study, it was suggested that the culture pH-shift optimization strategy using a pH-dependent dynamic model is suitable to optimize any pH-shift schedule for CHO cell lines used in mAb production projects.

Original languageEnglish
Pages (from-to)245-250
Number of pages6
JournalJournal of Bioscience and Bioengineering
Volume125
Issue number2
DOIs
Publication statusPublished - Feb 2018

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Bioengineering
  • Applied Microbiology and Biotechnology

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