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Paris-based Rivercell has emerged from stealth with a €22M seed round led by HV Capital, aiming to build AI models that predict how human cells respond to drugs.
Key Takeaways
- Rivercell raised a €22M ($25M) seed round, announced October 7, 2026, led by HV Capital.
- HCVC, Alven and Bpifrance Digital Venture also joined. The valuation was not disclosed.
- Funds go to a proprietary data platform, a larger Paris wet lab and an "AI Virtual Cell" programme.
Lead
Rivercell, a Paris biotech and AI company, announced on October 7, 2026 that it had raised a €22M (about $25M) seed round. HV Capital led. HCVC, Alven and Bpifrance Digital Venture participated, along with angel investors drawn from founders and executives at Twist Bioscience, DNA Script and Agilent.
The company was founded in the summer of 2025. It is building what it calls an AI Virtual Cell (AIVC), a model meant to simulate in silico how a human cell reacts to a drug or genetic change. Rivercell did not disclose a valuation or any earlier funding.
Who Is Behind Rivercell?
Rivercell is led by CEO and co-founder Yann Fleureau, a graduate of École Polytechnique and UC Berkeley. He previously co-founded Cardiologs, an AI cardiac diagnostics company that Philips acquired in 2021. That exit gives the company a founder with a completed sale in a regulated health field.
Eric Durand joined in 2026 as co-founder and chief scientific officer. His earlier employers include Novartis, Owkin and Bioptimus, which puts him in both big pharma and French AI-biology startups.
What Does Rivercell Actually Build?
Rivercell builds two linked things: a lab that generates cell-response data and a model trained on that data. The company's automated wet lab in Paris measures individual cells after an intervention. It takes multiple biological readouts over time, so the data records how a cell changes rather than a single snapshot.
Fleureau has described the equipment as a "GPU for the bio data centre" of the future. His stated view of the field is that "a world model of the cell is the opportunity of the century in medicine. The missing piece is data."
That emphasis on data is the company's main bet. Many AI drug-discovery efforts train on public datasets assembled from different labs, protocols and cell lines. Rivercell is producing its own, with consistent conditions, and the aim is to cut the number of physical experiments a drug program needs. Target areas named so far are oncology, immunology, rare diseases and cardiometabolic conditions.
Why Is a €22M Seed Round Notable?
A €22M seed is large by European standards, and it reflects how capital-intensive a data-generating biotech is. Software-only AI startups can reach a product with a few engineers and cloud credits. A company running an automated wet lab has to pay for instruments, reagents and lab staff before it has a model to show.
Investors are therefore funding infrastructure, not a finished product. The round says little about the performance of the virtual cell itself, because Rivercell has not published benchmarks or named drug-discovery partners. The disclosed facts are a team, a lab and a thesis.
The investor mix also matters. HV Capital is a Munich-based venture firm that backs European technology companies, and Alven and HCVC are Paris-based. Bpifrance Digital Venture brings the French state investment bank. Taken together, the syndicate points to French deep-tech backing with a German lead.
How Does Rivercell Fit Into AI Drug Discovery?
Rivercell enters a field where virtual-cell models are a recognized research goal and several well-funded groups are pursuing them. Other European AI drug-discovery companies, including Adaptyv Bio, Generare and WhiteLab Genomics, work on adjacent problems, though each takes a different approach.
The risk is the same one that has followed earlier AI-for-biology claims. A model can fit its training data well and still fail to predict what happens in a new cell type or with a new compound. Rivercell's answer is to control data quality at the source, but that answer has to be proven with predictions that hold up in prospective experiments.
Commercial terms are also unclear. The company has not said whether it will sell data, license models, run discovery programmes with partners or develop its own drug candidates. Each path implies a different revenue timeline and a different set of customers.
What Comes Next for Rivercell?
The seed money will pay for three things: scaling the proprietary data platform, expanding the Paris wet lab and launching the AI Virtual Cell programme. The first test is likely to be whether the lab can produce data at a volume and consistency that a large model needs.
A plausible next milestone is a first set of validation results or a pharma partnership. Either would show whether the virtual cell predicts outcomes in a form that drug developers will pay for. A Series A would probably depend on that evidence, since a seed investor's patience for infrastructure spending tends to be shorter than the time it takes to prove a model.
Outlook
Rivercell has secured €22M, a lead investor with a track record in European deep tech, and a founding team with one prior exit. What it has not yet shown is a validated model or a commercial customer. Over the coming year, the measures to watch are lab throughput, published validation of the AI Virtual Cell and the first partnership announcements.
