Tag: AI drug discovery
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The commercial landscape of AI protein design — funding is at the $10^9 scale, but the number of approved de novo AI-designed protein drugs is zero
Evidence-first notes on bioscience and deep tech, at the edge of the lab and the market. Information only — not investment advice, not medical advice. All funding, valuation and milestone totals are attributed to each company’s press releases or media reports; many details cannot be independently verified and are marked as such. Vendor blog/preprint performance…
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The Real Bottleneck in AI Drug Discovery Is Biology: Where the Capital Is, Where the Clinic Isn’t, and Why They Point in Opposite Directions
Evidence-first notes on bioscience and deep tech, at the edge of the lab and the market. Information only — not investment advice. The 30-second version What. Capital and clinical proof in AI drug discovery point in opposite directions. The best-financed pure-AI drug shops — Isomorphic Labs (a $2.1B Series B in May 2026), Xaira ($1B+…
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How much of “AI-discovered drugs succeed more” is evidence and how much is narrative: attribution, sample size and the survivorship trap
Evidence-first notes on bioscience and deep tech, at the edge of the lab and the market. Information only — not investment advice. The 30-second version What. The widely quoted claim that “AI-discovered drugs succeed at roughly twice the rate” traces back, in practice, to a single aggregation by one BCG-adjacent author team (Jayatunga et al.,…
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Same primary endpoint, opposite headlines: reading AI-designed drug readouts (rentosertib, EXS-21546, BEN-2293) — Part 3
Evidence-first notes on bioscience and deep tech, at the edge of the lab and the market. Information only — not investment advice. The 30-second version What. This part dissects individual AI-designed clinical readouts along a single axis: primary endpoint vs. headline. The decisive fact of framing asymmetry: rentosertib (headlined “positive”) and BEN-2293 (headlined “failed”) both…
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Structure-based and generative drug design in the clinic: elegant molecules, but whose efficacy?
Evidence-first notes on bioscience and deep tech, at the edge of the lab and the market. Information only — not investment advice. The 30-second version What. Structure-based and generative design engines (Insilico’s Chemistry42, Isomorphic’s IsoDDE, Schrödinger’s FEP+, Relay’s motion-based platform) have demonstrably done one thing: designed and optimized molecules well enough to enter the clinic,…
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Recursion and Exscientia: the phenotypic engine can discover, but the clinic has not confirmed it
Evidence-first notes on bioscience and deep tech, at the edge of the lab and the market. Information only — not investment advice. The 30-second version What. Recursion’s phenotypic engine (Recursion OS, a phenomics data universe of more than 25 petabytes) has demonstrated a real capability: to surface candidates from cellular phenotypes without knowing the target…
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The landscape of AI drug-discovery platforms: the design is proven, but is the clinic?
Evidence-first notes on bioscience and deep tech, at the edge of the lab and the market. Information only — not investment advice. The 30-second version What. AI drug-discovery platforms (Recursion, Insilico, Isomorphic, Schrödinger, Relay, Nimbus and others) have partly proven that they can design and optimize molecules — many candidates have entered the clinic and…