ByteDance's Anew Labs enters AI drug discovery with IL-17 inhibitor

The molecule targets a protein-protein interaction, a category of drug target that the pharmaceutical industry has spent decades calling undruggable because the binding surfaces are too large and flat for conventional small molecules to disrupt. Anew Labs says its AI found a way in. Anew Labs operates from Shanghai, Singapore, and San Jose, California, with 36 core team members and a scientific advisory board including former executives from Innovent Biologics, Amgen, and Takeda California. The unit's ambition is to replace injectable antibody therapies with oral pills, using generative AI to design small molecules that can do what antibodies do but in a form that patients can swallow. The molecule presented in Boston is a pan-spectrum IL-17 inhibitor, designed to block multiple forms of the IL-17 cytokine rather than a single variant. Existing IL-17 therapies, including Novartis's secukinumab and Eli Lilly's ixekizumab, are injectable antibodies that generated billions in annual revenue. An oral small molecule that achieves comparable efficacy would be commercially transformative. In March, Anew Labs published a preprint on bioRxiv describing AnewOmni, a generative AI framework trained on more than five million biomolecular complexes. The model is designed to work across molecular scales, from small chemical compounds to peptides to nanobodies. The researchers demonstrated that AnewOmni could design functional molecules targeting KRAS G12D and PCSK9, achieving success rates between 23 and 75 per cent with low-throughput laboratory validation. The technical approach attempts to solve a problem that has limited AI drug discovery across the industry: most generative models work well at one molecular scale but fail when asked to design across scales. AnewOmni claims to be the first framework to succeed at functional molecular design across all scales. What distinguishes More than 173 AI-discovered drug programmes are now in clinical development globally. Whether AI will revolutionise drug development depends on how it is used, and the industry's 90 per cent clinical failure rate has not yet demonstrably improved. The distance from a conference presentation to an approved oral therapy is measured in years and billions of dollars.