The archive · Bio & Materials · Strategic decision · 2024–2026
Bioptimus' $76M bet: one foundation model for all of biology, open first
Owkin spin-off Bioptimus raised a $35M seed, open-sourced the largest pathology AI model, then added $41M to build a multimodal 'world model of biology'.
Bioptimus
What the business is
Paris-based startup training large AI foundation models on multimodal biological data — pathology slides, genomics, clinical records — to speed diagnosis and drug discovery, selling model access to pharma and researchers.
Starting capital：$35M seed (Feb 2024, led by Sofinnova Partners with Bpifrance, Cathay Innovation, Xavier Niel and Owkin), then a $41M Series A (Jan 2025, led by Cathay Innovation) — $76M total.
How it started
Bioptimus emerged from stealth on Feb 20, 2024 in Paris as a spin-off of Owkin, the French biotech unicorn, co-founded by Owkin's chief R&D officer Jean-Philippe Vert and ex-Google and DeepMind researchers including CTO Rodolphe Jenatton. It raised a $35M seed led by Sofinnova Partners, signed an AWS compute partnership, and set out to train a foundation model of biology on Owkin's multimodal patient data from leading academic hospitals.
What happened
In July 2024, less than five months after launch, Bioptimus released H-Optimus-0, the world's largest open-source pathology foundation model — 1.1B parameters trained on 500,000+ histopathology slides — claiming state-of-the-art results on diagnostic tasks from detecting cancer cells to tumor biomarkers. In Jan 2025 it raised a $41M Series A led by Cathay Innovation (with Sofinnova, Bpifrance, Andera, Hitachi Ventures, Boom Capital, Pomifer, Sunrise and angels), bringing total funding to $76M, and said it was preparing a multimodal model spanning the entire biological spectrum.
No ending yet — it is still running.
Background
Bioptimus emerged from stealth on Feb 20, 2024 in Paris as a spin-off of Owkin, the French biotech unicorn, co-founded by Owkin's chief R&D officer Jean-Philippe Vert and ex-Google and DeepMind researchers. It raised a $35M seed led by Sofinnova Partners, signed an AWS compute partnership, and bet that biology would become a foundation-model domain: one model trained on multimodal patient data — slides, genomes, clinical records — that could simulate disease and predict outcomes.
Less than five months later it released H-Optimus-0, the world's largest open-source pathology foundation model: 1.1 billion parameters trained on 500,000+ histopathology slides, with state-of-the-art results on tasks from detecting cancer cells to identifying tumor biomarkers. In Jan 2025 Bioptimus raised a $41M Series A led by Cathay Innovation — Sofinnova, Bpifrance, Andera Partners, Hitachi Ventures, Boom Capital, Pomifer and Sunrise joined — taking total funding to $76M before any commercial product, to build a multimodal model spanning the entire biological spectrum.
As of Aug 2026 Bioptimus is still private. Its site reports models used by 16 of the top 20 pharma companies and 1,000+ institutions, over 1.18M total downloads, 100+ papers published using its models, and a next-generation M-Optimus model that integrates histology, spatial transcriptomics and genomics in a single architecture, backed by STELA, a multi-institutional data engine.
What has to be true
- The bet was that biology would follow text and images as a domain where one big model beats many small ones — a 'GPT for biology'.
- Owkin's accumulated hospital data was the moat: sensitive clinical data is not public, so competitors could not easily copy the training set.
- Open-sourcing H-Optimus-0 first built scientific credibility and adoption, converting researchers into users before the commercial push.
- Spinning off from Owkin made sense because foundation models need their own capital, compute and data strategy — a 'pure player' could move faster.
What can be applied
Exclusive multimodal data can be a moat: Owkin's hospital network let a seed-stage startup train models rivals couldn't, and open-sourcing the first one built credibility before the commercial pitch.
Aftermath
As of Aug 2026, Bioptimus is still private with $76M raised and no further round publicly reported. Its website reports that its models are trusted by 16 of the top 20 pharma companies and 1,000+ institutions, with 1,184,533 total model downloads and 100+ papers published using its models. It has moved beyond its pathology beachhead with M-Optimus, which integrates histology, spatial transcriptomics and genomics in one architecture, and launched STELA, a multi-institutional data engine for generating deeply profiled, clinically linked patient data across geographies.
Sources
- Bioptimus raises $35 million seed round to develop AI foundational model focused on biology
- Bioptimus launches H-Optimus-0, the world's largest open-source AI foundation model for pathology
- Bioptimus raises $41M to develop a 'GPT for biology'
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