N-linked glycosylation profile is a critical quality attribute in therapeutic monoclonal antibody (mAb) production. Despite its importance, the complex and multi-level regulation of glycosylation during biopharmaceutical production remains incompletely understood. In this work, we introduce Glycosylation Control Analysis (GCA), a novel sensitivity analysis framework for glycosylation reaction networks (GRNs). GCA builds upon an improved formulation of Glycosylation Flux Analysis (iGFA) that applies constraint-based modeling to GRNs. Specifically, the iGFA employs Michaelis-Menten kinetics to derive dynamic factors describing enzyme processing capacity, substrate concentration, and Golgi residence time effects on glycosylation fluxes. By calculating glycosylation control coefficients (gCCs), GCA quantifies how perturbations to specific enzyme activities propagate through the network to affect glycosylation fluxes in a GRN. Application to data from CHO cell cultures producing IgG under different pH conditions revealed dynamic insights into the regulation of glycosylation fluxes. The results highlighted Galactosyltransferase (GalT) as the primary regulator of the dominant G0F glycoform, with its influence decreasing over cultivation time. At a more granular reaction level, we identified the galactosylation reaction G0F→G1Fa/b as exerting the highest control over network dynamics. Notably, pH significantly altered control patterns, with Fucosyltransferase exerting stronger influence at higher pH levels, suggesting pH-dependent reorganization of flux control mechanisms. These findings demonstrate GCA's ability to identify critical control points in glycosylation networks, providing potential targets for bioprocess engineering to optimize glycan profiles in therapeutic protein production.
