Mannose metabolism in recombinant CHO cells and its effect on IgG glycosylation.

Understanding the causes of high-mannose (HM) glycosylation of recombinant IgG in CHO cells would facilitate the production of therapeutics. CHO cells grown with mannose as the major carbon source demonstrated a dramatic increase in total HM glycosylation in recombinant IgG, with no effect on cell growth, viability, or titer. Quantitative metabolomics and (13) C flux analysis were used to explore the mechanism for increased HM glycosylation and understand the metabolism of mannose in CHO cells. It was demonstrated that mannose was a good carbon source for CHO cell growth and IgG production, readily entering both glycolysis and the TCA Cycle. Previous mechanisms for increased HM glycosylation during antibody production have been attributed to changes in pH, osmolality, increased specific productivity, and nutrient limitation. The results from this study propose a novel mechanism where an increased carbon flux in the GDP-mannose synthetic pathway increased the intracellular concentration of mannose-containing metabolites. The abnormally high concentration of mannose and mannose-metabolites were shown to inhibit α-mannosidase activity and it was proposed that this inhibition in the ER and Golgi caused the production of IgG with increased high-mannose glycosylation. Biotechnol. Bioeng. 2016;113: 1468-1480. © 2016 Wiley Periodicals, Inc.

Real-time product attribute control to manufacture antibodies with defined N-linked glycan levels.

Pressures for cost-effective new therapies and an increased emphasis on emerging markets require technological advancements and a flexible future manufacturing network for the production of biologic medicines. The safety and efficacy of a product is crucial, and consistent product quality is an essential feature of any therapeutic manufacturing process. The active control of product quality in a typical biologic process is challenging because of measurement lags and nonlinearities present in the system. The current study uses nonlinear model predictive control to maintain a critical product quality attribute at a predetermined value during pilot scale manufacturing operations. This approach to product quality control ensures a more consistent product for patients, enables greater manufacturing efficiency, and eliminates the need for extensive process characterization by providing direct measures of critical product quality attributes for real time release of drug product.