AI FOR SCIENCE · ON THE RECORD
Unnatural Products
Designs macrocyclic peptides, ring-shaped molecules meant to reach hard targets and be taken as pills, with a platform that pairs parallel synthesis and screening with machine learning; partners include argenx, Novartis, Merck and BridgeBio.
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Timeline
People
Only people the AI4S.fyi record has named: in a round, a timeline entry, commentary, an interview or a sourced role. Not the full team.
Named on AI4S.fyi
Cameron PyeFounder argenx agrees to buy Unnatural Products, which designs ring-shaped peptide drugs with machine learning and parallel chemistry, for $550 million upfront and up to about $1.15 billion
Joshua SchwochertFounder argenx agrees to buy Unnatural Products, which designs ring-shaped peptide drugs with machine learning and parallel chemistry, for $550 million upfront and up to about $1.15 billion
Funding rounds tracked
- 2026-03-16Series B · $45MconfirmedLed by The Venture Collective · With Droia Ventures · Existing investors argenx, Merck Global Health Innovation Fund, ARTIS Ventures, First Spark VenturesStated use: building a wholly owned pipeline and taking at least one programme into the clinic, as CEO Cameron Pye put it
- 2023-12-20Series A · $32MreportedLed by Merck Global Health Innovation Fund, ARTIS Ventures · With First Spark Ventures, The Venture Collective, Humain Ventures, LongeVC, Not Boring CapitalStated use: advancing its platform and widening its focus beyond oncology
- 2019-09-17Seed · $6 million ("more than $6 million" in Santa Cruz Tech Beat's copy)reportedLed by ARTIS Ventures · With Abstract Ventures, Asset Management Ventures, Better Ventures, Blue Bear Ventures, Rising Tide FundStated use: growing the team, developing the platform and advancing its oncology programmes
Each round links to its line on the funding record, with its source.
Also in Drug discovery on the funding board
The other companies the funding board files under the same field, latest round first. A list of what the record tracks, not a ranking or a market map.
- 2026-11-13Orakl OncologySeries A · $34MA Gustave Roussy spin-out that grows tumour organoids from real patients, screens them against drugs and links each result to the patient's clinical history and molecular data, to train models that predict how cancer drugs will perform in trials and to find new drug targets.
- 2026-11-05Potential SciencesSeed · eight-figure sum (capital and compute)Runs gold-standard quantum chemistry (CCSD(T)) on GPUs, at what it says is a hundredth of the usual cost, to compute training data for atomistic models of how molecules bind and react, starting with small-molecule drug discovery for AI-first labs.
- 2026-11-04Isomorphic LabsRound (unnamed) · $5BAlphabet's drug-design company, spun out of DeepMind to build on AlphaFold: it builds AI models to design drug candidates for its own pipeline and for pharma partners.
- 2026-10-29ALLOXSeed · US$10.5M (€9.4M)Measures the effects of thousands of protein mutations at once to map allosteric and other regulatory sites, and builds AI models on that data to find drug-binding spots on hard targets such as protein-protein interactions and transcription factors, for its own small molecules.
- 2026-10-29PerturbMindAngel and Angel+ · tens of millions of yuanBuilds AlphaCell, a model meant to predict how a cell's gene expression changes when a gene or a drug perturbs it, to help find disease mechanisms, new targets and new kinds of drugs; it plans to sell on-device service subscriptions and private deployments and to co-run drug programmes.
- 2026-10-27Atlas BioSeed · $10MRuns in silico clinical trials, starting in immunology: a foundation model trained on about 2 million RNA readouts from human tissue predicts each virtual patient's response to several treatments and diseases, to help drug developers choose what to take into Phase II.
This page compiles what AI4S.fyi has recorded and links each item to its source. It is not a grade of the organization and not its complete history: a blank means the record has not caught up as often as it means nothing happened.