4.3 Article

Real-time quantification and supplementation of bioreactor amino acids to prolong culture time and maintain antibody product quality

期刊

BIOTECHNOLOGY PROGRESS
卷 35, 期 6, 页码 -

出版社

WILEY
DOI: 10.1002/btpr.2894

关键词

amino acids; bioprocessing; glycosylation; MVDA; PCA; process analytical technology

资金

  1. U.S. Food and Drug Administration
  2. Oak Ridge Institute for Science and Education
  3. CDER Critical Path Program

向作者/读者索取更多资源

Real-time monitoring of cell cultures in bioreactors can enable expedited responses necessary to correct potential batch failure perturbations which may normally go undiscovered until the completion of the batch and result in failure. Currently, analytical technologies are dedicated to real-time monitoring of bioreactor parameters such as pH, dissolved oxygen, and temperature, nutrients such as glucose and glutamine, or metabolites such as lactate. Despite the importance of amino acids as the building blocks of therapeutic protein products, other than glutamine their concentrations are not commonly measured. Here, we present a study into amino acid monitoring, supplementation strategies, and how these techniques may impact the cell growth profiles and product quality. We used preliminary bioreactor runs to establish baselines by determining initial amino acid consumption patterns, the results of which were used to select a pool of amino acids which gets depleted in the bioreactor. These amino acids were combined into blends which were supplemented into bioreactors during a subsequent run, the concentrations of which were monitored using a mass spectrometry based at-line method we developed to quickly assess amino acid concentrations from crude bioreactor media. We found that these blends could prolong culture life, reversing a viable cell density decrease that was leading to batch death. Additionally, we assessed how these strategies might impact protein product quality, such as the glycan profile. The amino acid consumption data were aligned with the final glycan profiles in principal component analysis to identify which amino acids are most closely associated with glycan outcomes.

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