Amazon Science reports AI models for designing and characterizing antibodies

Amazon Science describes three papers on AI for antibody discovery: MochiBind ranks antibody binding strength from sequence alone, CA-MAP predicts developability properties using batch-aware context, and an agent-guided pipeline designed nanobody binders against a novel cancer target.

In the pipeline, 116 candidates survived lab screening, and 46 were identified as strong binders, which are being used to train the next design cycle.