AI Article Synopsis

  • The study focuses on developing an in-line Raman spectroscopy method to monitor key parameters like glucose, lactate, and viable cell density (VCD) during the commercial production of biosimilar adalimumab using Chinese hamster ovary (CHO) cells in a 1500 L bioreactor.
  • The researchers optimized Raman calibration models to achieve low prediction errors for glucose, lactate, and VCD, making the method effective for real-time monitoring of the cell culture process.
  • Additionally, the study explored how the number of batches used for model calibration affects model performance, providing insights for similar bioprocess monitoring in the future.

Article Abstract

The 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 for glucose in the range of 1.66-3.53 g L , 0.08 g L for lactate in the range of 0.15-1.19 g L , 0.31 E6 cells mL for VCD in the range of 0.96-5.68 E6 cells mL 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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http://dx.doi.org/10.1002/biot.202300395DOI Listing

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