The N-linked glycan profiles on recombinant monoclonal antibody therapeutics significantly affect antibody biological functions and are largely determined by host cell genotypes and culture conditions. A key step in bioprocess development for monoclonal antibodies (mAbs) involves optimization and control of N-glycan profiles. With pressure from pricing and biosimilars looming, more efficient and effective approaches are sought in the field of glycoengineering. Metabolic studies and mathematical modeling are two such approaches that optimize bioprocesses by better understanding and predicting glycosylation. In this review, we summarize a group of strategies currently used for glycan profile modulation and control. Metabolic analysis and mathematical modeling are then explored with an emphasis on how these two techniques can be utilized to advance glycoengineering.
Keywords: N-glycosylation; glycoengineering; mathematical modeling; metabolic characterization; monoclonal antibody.
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