单克隆抗体
糖基化
聚糖
生物过程
生物仿制药
计算生物学
重组DNA
生物
抗体
生物技术
糖蛋白
免疫学
生物化学
基因
古生物学
作者
Sha Sha,Cyrus Agarabi,Kurt Brorson,Dong‐Yup Lee,Seongkyu Yoon
标识
DOI:10.1016/j.tibtech.2016.02.013
摘要
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.
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