Cell Culture Glycosylation Multi-scale Data Driven Mechanistic Modeling (Phase 2)

Glycosylation, one of the most common post-translational modifications (PTMs) for proteins, occurs via a complex set of reactions by which sugars are added to and removed from proteins. These glycans can impact folding stability, intracellular and extracellular targeting, and mediation of binding to host cells. In therapies, the glycoform distribution can impact the immunogenicity, circulatory half-life, pharmacokinetics, and effector functions. To ensure consistent product quality and glycoform distribution, an understanding of factors that affect the glycoforms is required. These factors range from protein structure around the glycosylation site to various genetic mutations, to host enzyme expression levels to culture conditions. Hybrid models which combine mechanistic information and equations with data-driven model elements can embody the information related to glycosylation to enable accurate prediction of glycosylation CQA based on current cell-culture process conditions and process variable set-points. Unanticipated causes of glycosylation variation, such as trace media component variability, can be addressed by inclusion of data-driven model elements which are trained frequently to adapt the models predictions with current information.