---

description: 173 AI-discovered programs now in clinical development with 80-90 percent Phase I success and Insilicos rentosertib is first fully AI-designed drug to clear Phase IIa but overall clinical failure rates remain unchanged making later-stage success the key unknown
type: claim
domain: health
created: 2026-02-17
source: "AI drug discovery pipeline data 2026; Insilico Medicine rentosertib Phase IIa; Isomorphic Labs $3B partnerships; WEF drug discovery analysis January 2026"
confidence: likely
related:
  - "FDA is replacing animal testing with AI models and organ on chip as the default preclinical pathway which will compress drug development timelines and reduce the 90 percent clinical failure rate"
reweave_edges:
  - "FDA is replacing animal testing with AI models and organ on chip as the default preclinical pathway which will compress drug development timelines and reduce the 90 percent clinical failure rate|related|2026-03-28"
---

# AI compresses drug discovery timelines by 30-40 percent but has not yet improved the 90 percent clinical failure rate that determines industry economics

AI-discovered drug candidates entering clinical trials have grown exponentially: 3 in 2016, 17 in 2020, 67 in 2023, an estimated 173 by 2026. AI compresses preclinical candidate development from 3-4 years to 13-18 months and achieves 80-90% Phase I success rates compared to 40-65% for traditional compounds. The discovery phase has been shortened from 5-6 years to approximately 1 year in leading cases.

Insilico Medicine achieved the most significant milestone: positive Phase IIa results for rentosertib (ISM001-055) in idiopathic pulmonary fibrosis -- the first drug with both target and molecule designed entirely by AI to show efficacy. Isomorphic Labs (DeepMind spinoff) raised $600M with $3B in Eli Lilly and Novartis partnerships, expecting first Phase I trials by late 2026. Recursion merged with Exscientia to create an end-to-end platform.

The critical question is whether AI can move the needle beyond Phase I. The pharmaceutical industry's overall ~90% clinical failure rate has not demonstrably changed. "Faster to clinic" is proven; "more likely to work in patients" is not. If AI cracks later-stage success rates, the economic impact dwarfs everything else in healthcare -- a single percentage point improvement in Phase II/III success is worth billions. But the proof is still ahead of us.


### Additional Evidence (extend)
*Source: [[2026-03-19-vida-ai-biology-acceleration-healthspan-constraint]] | Added: 2026-03-19*

Smith 2026 provides concrete evidence of compression magnitude: Ginkgo Bioworks + GPT-5 compressed 150 years of protein engineering into weeks. This is consistent with Amodei's 10-20x prediction (50-100 years → 5-10 years) and confirms that discovery-phase compression is already happening at scale, not speculative.

---

Relevant Notes:
- recursive improvement is the engine of human progress because we get better at getting better -- AI drug discovery is recursive improvement applied to pharma R&D
- [[continuous health monitoring is converging on a multi-layer sensor stack of ambient wearables periodic patches and environmental sensors processed through AI middleware]] -- new drugs from AI discovery feed into the monitoring-driven care model
- clinical trials should use adaptive allocation to minimize harm to patients during the trial not just produce clean data for future patients -- adaptive trial designs could improve the 90% clinical failure rate by reallocating patients away from failing arms mid-trial rather than running fixed protocols to completion

Topics:
- livingip overview
- health and wellness
