AI drug discovery hits data bottleneck as costs soar

Drug development costs double every nine years, a trend called Eroom's Law, with new drugs taking 10-15 years and billions to bring to market. AI-driven discovery promises to cut timelines but faces a critical data loop problem: models need high-quality, proprietary data that pharma companies guard closely. Closing this loop could unlock faster, cheaper drug development, but requires unprecedented data sharing and collaboration.