AI-driven drug discovery
We judge drug-discovery tools by the medicines that get through clinical testing. Takeda reports that zasocitinib, originally developed by Nimbus, entered FDA priority review in September after positive Phase 3 results. That is progress for one drug. Whether AI raises success rates across the industry, and whether one business model takes all the value, is still unproven.
Research snapshot · updated Nov 12, 2026
Cost and time compression driving pharma adoption
AI platforms compress hit-to-lead timelines from 4-5 years to roughly 12-18 months in preclinical stages. Big Pharma now treats AI-assisted discovery as a core R&D lever rather than a speculative bet: deal flow roughly doubled year-on-year into 2026, with multi-billion templates such as Insilico-Eli Lilly (up to $2.75B) and GSK-Flagship (up to $7B+). The economics increasingly favour incumbents and the software-licence layer over standalone AI-native biotechs.
Clinical results so far
The best test of a drug-discovery tool is whether its medicines get through clinical trials. On 18 December 2025 Takeda announced positive headline results from two pivotal Phase 3 trials of zasocitinib in plaque psoriasis. The drug was first developed by Nimbus. In September 2026 the FDA accepted Takeda's application under priority review. The drug is not yet approved. These results support one compound in one disease. They do not show that AI raises success rates across the industry.
State of the art — two trajectories, opposite outcomes
Two clinical trajectories now sit inside what was a single category. The first – AI-and-physics-assisted lead optimisation embedded inside Big Pharma R&D – has produced its first Phase 3 win in zasocitinib (TAK-279), discovered through Nimbus/Schrödinger, sold to Takeda December 2022, positive Phase 3 readout March 2026, NDA in FY2026, decision by Q4 2027. The second – wholly generative-AI-designed small molecules owned by AI-native biotechs – remains at Phase 2a (Insilico Medicine rentosertib for IPF, Nature Medicine June 2025) or Phase 1 (Isomorphic Labs first cancer programme, Hassabis Davos January 2026). The first trajectory accrues to pharma incumbents and the software-licence layer (Schrödinger Q1 2026 revenue $58.6M, mostly software and discovery services). The second trajectory has not produced a commercial win for any AI-native biotech and, in public-equity terms, the cohort is disconfirmed at this point – Recursion-Exscientia $3.27 on 7 May 2026, BenevolentAI delisted from Euronext Amsterdam 13 March 2025.
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Signal stack
Evidence stacked leading → lagging
8 signals
Signal stack
Evidence stacked leading → lagging
Technology-native KPIs
Metrics that predict trajectory, tracked over time
5 tracked
Technology-native KPIs
Metrics that predict trajectory, tracked over time
Landscape map
Who builds what, and who depends on whom
66 players · 6 layers
Landscape map
Who builds what, and who depends on whom
Catalyst calendar
Dated events that will move the position
8 ahead
Catalyst calendar
Dated events that will move the position
Technology roadmap
Milestones on the path to maturity
8 milestones
Technology roadmap
Milestones on the path to maturity
Watchlists
Companies, people and papers, each with a condition for removing it
20 · 20
Watchlists
Companies, people and papers, each with a condition for removing it
Decision frameworks
What our view means for your job
Locked
Decision frameworks
What our view means for your job
Thesis changelog
When our view changed, and why
10 updates
Thesis changelog
When our view changed, and why
Change our mind
6 disconfirming conditions
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The full signal stack, technology-native KPIs tracked over time, the landscape of who depends on whom, the dated catalyst calendar, decision frameworks for every desk, live watchlists and a record of every time our view on AI-driven drug discovery has changed. All of it is in CanaryIQ.