Xu Yan, Xiaoxiao Dong, Yuxiang Wan, Dong Gao, Zhenhua Chen, Ying Zhang, Zhilong Zheng, Kaifeng Chen, Jingyu Jiao, Yan Sun, Zhuohong He, Lei Nie, Xiaohui Fan, Haibin Wang, Haibin Qu

Development of an in‐line Raman analytical method for commercial‐scale CHO cell culture process monitoring: Influence of measurement channels and batch number on model performance

  • Molecular Medicine
  • Applied Microbiology and Biotechnology
  • General Medicine

AbstractThe mammalian cell culture process is a key step in commercial therapeutic protein production and needs to be monitored and controlled due to its complexity. Raman spectroscopy has been reported for cell culture process monitoring by analysis of many important parameters. However, studies on in‐line Raman monitoring of the cell culture process were mainly conducted on small or pilot scale. Developing in‐line Raman analytical methods for commercial‐scale cell culture process monitoring is more challenging. In this study, an in‐line Raman analytical method was developed for monitoring glucose, lactate, and viable cell density (VCD) in the Chinese hamster ovary (CHO) cell culture process during commercial production of biosimilar adalimumab (1500 L). The influence of different Raman measurement channels was considered to determine whether to merge data from different channels for model development. Raman calibration models were developed and optimized, with minimum root mean square error of prediction of 0.22 g L−1 for glucose in the range of 1.66–3.53 g L−1, 0.08 g L−1 for lactate in the range of 0.15–1.19 g L−1, 0.31 E6 cells mL−1 for VCD in the range of 0.96–5.68 E6 cells mL−1 on test sets. The developed analytical method can be used for cell culture process monitoring during manufacturing and meets the analytical purpose of this study. Further, the influence of the number of batches used for model calibration on model performance was also studied to determine how many batches are needed basically for method development. The proposed Raman analytical method development strategy and considerations will be useful for monitoring of similar bioprocesses.

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