BioPhi: A platform for antibody design, humanization, and humanness evaluation based on natural antibody repertoires and deep learning.

ABSTRACT: Despite recent advances in transgenic animal models and display technologies, humanization of mouse sequences remains one of the main routes for therapeutic antibody development. Traditionally, humanization is manual, laborious, and requires expert knowledge. Although automation efforts are advancing, existing methods are either demonstrated on a small scale or are entirely proprietary. To predict the immunogenicity risk, the human-likeness of sequences can be evaluated using existing humanness scores, but these lack diversity, granularity or interpretability. Meanwhile, immune repertoire sequencing has generated rich antibody libraries such as the Observed Antibody Space (OAS) that offer augmented diversity not yet exploited for antibody engineering. Here we present BioPhi, an open-source

SUBMITTER: Prihoda D 

PROVIDER: S-EPMC8837241 | biostudies-literature | 2022 Jan-Dec

REPOSITORIES: biostudies-literature