Raman spectroscopy is a PAT fingerprinting tool at the cutting edge of bioprocess monitoring and control. The application of this technology is the analysis of the chemical bond signature of critical components utilizing chemometric models for bioreactor cell culture processes. The objective was to conduct proof of concept studies which use a Raman spectroscopic probe applied to reduced scale (1L & 5L) and manufacturing scale (2000L) bioreactor processes to monitor metabolites, cell growth and productivity. Spectroscopic Raman data is harnessed and interpreted through the use of predictive modeling (Partial Least Squares (PLS)).  Experiments were performed at reduced scale (1L & 5L) to monitor glucose, lactate, ammonia and other cellular process components.  Raman models were also successfully applied at commercial scale (2kL) and delivered solutions to real-time trouble shooting efforts. Previously gathered Raman spectral data highlighted fluctuations in glucose control attributed to the process of daily bolus feeding.  Experiments were performed at reduced scale (1L) to test the implementation of an automated feedback control loop for the feeding process.  A low glucose concentration was targeted using the predicted value from Raman spectra obtained in real-time. This proof of concept control study resulted in reducing the level of glucose variation over the duration of the production run and demonstrated an improvement to protein productivity in the region of 20%. Raman spectroscopy can be used to increase visibility and process knowledge of important variables such as cellular metabolites, cell growth and productivity in the bioreactor process. These studies demonstrate application of Raman and chemometric models increases the likelihood of early event detection on the manufacturing floor, and the proof of concept studies show how increasing process control by automated feeding can result in a positive response in the bioreactor.<br/>

Monitoring and controlling critical components in cell culture process using PAT Tool, Raman spectroscopy

2019 Spring National Meeting

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