AWS and Hopkins Engineering announce groundbreaking database for AI/ML antibody design

Amazon Science · 3 months ago

AWS and Johns Hopkins Engineering launched the Antibody Developability Benchmark, a public database for evaluating AI and machine learning models used in antibody drug design. The dataset contains 50 seed antibodies across four structural formats targeting 42 antigens, with up to 99 engineered variants per seed, making it 20 times more diverse than existing public benchmarks. The benchmark enables researchers to rigorously compare computational antibody prediction models against experimentally validated data before expensive wet-lab testing, potentially accelerating therapeutic antibody discovery and reducing costs.