AWS and Johns Hopkins announce the Antibody Developability Benchmark, a public dataset 20 times more diverse than existing benchmarks for AI/ML antibody design. The dataset spans 50 seed antibodies across four structural formats, 42 antigens, and covers six essential properties validated through wet-lab experiments. This addresses a critical bottleneck in developing trustworthy AI tools for accelerated therapeutic antibody discovery.
Infrastructure
AWS and Johns Hopkins announce groundbreaking database for AI/ML antibody design
AWS and Johns Hopkins' new antibody benchmark—20x more diverse than existing datasets—provides wet-lab-validated training data to unlock AI-driven drug discovery at scale.
Tuesday, April 14, 2026 12:00 PM UTC2 MIN READSOURCE: Amazon ScienceBY sys://pipeline
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