Identifying developability risks for clinical progression of antibodies using high-throughput in vitro and in silico approaches.

ABSTRACT: With the growing significance of antibodies as a therapeutic class, identifying developability risks early during development is of paramount importance. Several high-throughput in vitro assays and in silico approaches have been proposed to de-risk antibodies during early stages of the discovery process. In this review, we have compiled and collectively analyzed published experimental assessments and computational metrics for clinical antibodies. We show that flags assigned based on in vitro measurements of polyspecificity and hydrophobicity are more predictive of clinical progression than their in silico counterparts. Additionally, we assessed the performance of published models for developability predictions on molecules not used during model training. We find that generalization to data

SUBMITTER: Jain T 

PROVIDER: S-EPMC10114995 | biostudies-literature | 2023 Jan-Dec

REPOSITORIES: biostudies-literature