Research & Analyses
Comprehensive analyses of de novo antibody design platforms and developability prediction.
Does Developability Come For Free?
FLAb Dataset Analysis
Testing whether de novo antibody design models learn therapeutic-like developability without explicit training. Analysis of 160 FLAb datasets reveals training data bias as the explanation for "emergent" developability.
DADB-v1.0: A Therapeutic Decathlon
De Novo Antibody Design Benchmark
The first comprehensive benchmark measuring what actually matters for therapeutic antibodies: binding, structure, developability, and immunogenicity. A composite scoring system for the field.
Antibodies from Thin Air
Five AI Platforms Rewriting Cancer Drug Discovery
A comprehensive comparison of JAM-2, Chai-2, Origin-1, RFAntibody, and Latent-X2. Covers hit rates, binding affinities, oncology targets, and the first immunogenicity data for AI-designed antibodies. Includes a primer on antibody biology for newcomers.