Big Data Analytics For Productivity Improvement And Optimization Of mAb Production Process

The bioreactor’s environment and media contents affect the metabolism and productivity of a cell line. Traditional analytics like pH, temperature, dissolved gas levels, and titer reveals useful but incomplete information about the cells’ metabolism. Extracellular metabolites and nutrients in the cell media can be monitored to provide some information about the health of the cells. Additionally, that info can assist with identifying molecules that may promote or inhibit the cells’ metabolism and productivity, yielding insight into how to optimize future processes. For instance, lactate has long been known to be an inhibitor to a culture’s health, and it is closely monitored to ensure that levels are kept within an appropriate range. Also, monitoring amino acid levels in basal media and feed supplements confirms that their concentrations are suitable to promote a healthy and productive process.

A collaboration between the biologics process development team at Bristol-Myers Squibb and Seongkyu Yoon’s group at UMass Lowell investigated how amino acid and metabolite levels monitored by LC-MS coupled with transcriptome analysis could be used to identify promoters and inhibitors early during process development. They sought to perform multivariate analysis to correlate the changes in metabolite levels to specific metabolic pathway regulation. This would allow for faster optimization of an appropriate media strategy for increased titers. The teams used a CHO-K1 GS knockout cell line fed the same basal media across four 5-L bioreactors in a 14-day fed-batch process. In those four reactors, two levels of a selection agent (methionine sulfoximine) and two different feeds (standard and fortified with serine, threonine, tyrosine, and lysine) were evaluated. Daily samples were frozen and run after the processes were completed with a combination of LC-MS and HILIC-MS for metabolomics analysis.