生物制药
信息学
计算机科学
计算生物学
数据科学
生物技术
生物
政治学
法学
作者
Rahul Khetan,Robin Curtis,Charlotte M. Deane,Johannes Thorling Hadsund,Uddipan Kar,Konrad Krawczyk,Daisuke Kuroda,Sarah A. Robinson,Pietro Sormanni,Kouhei Tsumoto,Jim Warwicker,Andrew C.R. Martin
出处
期刊:mAbs
[Landes Bioscience]
日期:2022-02-01
卷期号:14 (1)
被引量:59
标识
DOI:10.1080/19420862.2021.2020082
摘要
Therapeutic monoclonal antibodies and their derivatives are key components of clinical pipelines in the global biopharmaceutical industry. The availability of large datasets of antibody sequences, structures, and biophysical properties is increasingly enabling the development of predictive models and computational tools for the "developability assessment" of antibody drug candidates. Here, we provide an overview of the antibody informatics tools applicable to the prediction of developability issues such as stability, aggregation, immunogenicity, and chemical degradation. We further evaluate the opportunities and challenges of using biopharmaceutical informatics for drug discovery and optimization. Finally, we discuss the potential of developability guidelines based on in silico metrics that can be used for the assessment of antibody stability and manufacturability.
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