| Literature DB >> 35104168 |
Rahul Khetan1, Robin Curtis1, Charlotte M Deane2, Johannes Thorling Hadsund3, Uddipan Kar4, Konrad Krawczyk5, Daisuke Kuroda6,7,8, Sarah A Robinson2, Pietro Sormanni9, Kouhei Tsumoto6,7,8,10, Jim Warwicker1, Andrew C R Martin11.
Abstract
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.Entities:
Keywords: antibody engineering; biopharmaceutical informatics; computational prediction; developability assessment; developability guidelines; therapeutic antibodies
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Year: 2022 PMID: 35104168 PMCID: PMC8812776 DOI: 10.1080/19420862.2021.2020082
Source DB: PubMed Journal: MAbs ISSN: 1942-0862 Impact factor: 5.857