Chemically defined (CD) media are routinely used in the production of biologics in Chinese Hamster Ovary (CHO) cell culture and provide enhanced raw material control. Nutrient optimized CD media is an important path to increase cell growth and monoclonal antibody (mAb) productivity in recombinant CHO cell lines. However, nutrient optimization efforts for CD media typically rely on multi-factorial and experimental design of experiment (DoE) approaches or complex mathematical models of cellular metabolism or gene expression systems. Moreover, the majority of these efforts are aimed at amino acids since they constitute essential nutrients in CD media as they directly contribute to biomass and protein production. In this study, we demonstrate the utilization of multi-variate data analytics (MVDA) coupled with amino acid stoichiometric balances (SBs) to increased cell growth and mAb productivity in efforts to reduce CD media development efforts. SBs measure the difference between theoretical demand of amino acids and the empirically measured fluxes to identify metabolic states of the cell. When coupled with MVDA, the statistical models were not only able to highlight key amino acids towards cell growth or productivity, but also provided direction on metabolic favorability of the amino acid. Experimental validation of our approach resulted in a 55% increase in total cell growth and about an 80% increase in total mAb productivity. Increased specific consumption of stoichiometrically balanced amino acids and decreased specific consumption of glucose was also observed in optimized CD media suggesting favorable consumption of desired nutrients and a potential for energy redistribution towards increased cellular growth or mAb productivity.

A robust monoclonal antibody (mAb) bioprocess requires physiological parameters such as temperature, pH, or dissolved oxygen (DO) to be well-controlled as even small variations in them could potentially impact the final product quality. For instance, pH substantially affects N-glycosylation, protein aggregation and charge variant profiles, as well as mAb productivity. However, relatively less is known about how pH jointly influences product quality and titer. In this study, we investigated the effect of pH on culture performance, product titer and quality profiles by applying longitudinal multi-omics profiling, including transcriptomics, proteomics, metabolomics and glycomics, at three different culture pH set points. The subsequent systematic analysis of multi-omics data showed that pH set points differentially regulated various intracellular pathways including intracellular vesicular trafficking, cell cycle, and apoptosis, thereby resulting in differences in specific productivity, product titer and quality profiles. In addition, a time-dependent variation in mAb N-glycosylation profiles, independent of pH was identified to be mainly due to the accumulation of mAb proteins in the endoplasmic reticulum (ER) over culture time, disrupting cellular homeostasis. Overall, this multi-omics-based study provides an in-depth understanding of the intracellular processes in mAb-producing CHO cell line under varied pH conditions and could serve as a baseline for enabling the quality optimization and control of mAb production.