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Updated: Jun 6, 2026

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation
Published on: May 18, 2020
Increasing batch-to-batch reproducibility of CHO cultures by robust open-loop control
M Aehle1, A Kuprijanov, S Schaepe
1Institute of Biochemistry and Biotechnology, Martin-Luther-University Halle-Wittenberg, Weinbergweg 22, 06120, Halle (Saale), Germany.
Process reproducibility in recombinant protein production is crucial. This study introduces a robust fed-batch strategy for Chinese hamster ovary (CHO) cells, ensuring consistent biomass trajectories despite initial cell density variations.
Area of Science:
- Biotechnology
- Bioprocess Engineering
- Mammalian Cell Culture
Background:
- Ensuring recombinant therapeutic protein quality relies on reproducible mammalian cell culture processes.
- Current industrial processes exhibit significant deviations when initial cell density varies, impacting biomass trajectory.
- Variations in initial cell mass can lead to severe disruptions in desired biomass development.
Purpose of the Study:
- To design a fed-batch production process robust against viable cell density variations.
- To demonstrate a novel open-loop control strategy for enhanced process consistency.
- To validate the proposed method in Chinese hamster ovary (CHO) cell cultures.
Main Methods:
- Implementation of an open-loop control strategy.
- Utilizing an optimized glutamine feed rate profile F(t).
- Maintaining cells at a predefined specific growth rate below the maximum (μmax) while preserving high viability.
Main Results:
- Demonstrated for the first time in CHO cell cultures that the proposed strategy leads to converging viable cell count profiles.
- Achieved robustness against initial viable cell density variations.
- Successfully controlled CHO cells at specific growth rates below μmax with high viability.
Conclusions:
- The proposed glutamine feed rate strategy ensures robust fed-batch processes for recombinant protein production in CHO cells.
- This method mitigates the impact of initial cell density fluctuations on biomass trajectory.
- The strategy allows for precise control over cell growth rates, enhancing process predictability and quality.
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