Paris Startup Rivercell Raises $25M to Build AI Virtual Cells

Jan de Vries · 2026-10-07

Rivercell just stepped out of stealth with $25 million, and they're not shy about their ambitions. The Paris-based biotech and AI company wants to build a world model of the human cell — a simulation that predicts how cells respond to drugs and genetic changes. If they pull it off, drug discovery could look completely different. ### The $25 Million Bet on Cellular Data The seed round was led by HV, with HCVC, Alven, and Bpifrance Digital Venture also chipping in. That cash will scale up Rivercell's data generation platform, expand their wet lab in Paris, and kick off their AI Virtual Cell program. Yann Fleureau, co-founder and CEO, puts it bluntly: "A world model of the cell is the opportunity of the century in medicine. The missing piece is data." He's talking about how cells change over time and under treatment — captured at scale, across multiple layers. Building that data engine in Europe isn't just smart for Rivercell; it's strategic for the continent's place in AI and biology. ### Europe's AI Drug Discovery Scene Is Heating Up Rivercell isn't alone. This year, European startups in this space have raised around $108 million across related financings. That includes: - Lausanne-based Adaptyv Bio's $37 million Series A for an automated AI-native wet lab - London-based Helical's $9 million seed for a virtual AI lab - Antwerp-based Sightera Biosciences' $3.2 million pre-seed for an AI drug-discovery platform - Paris-based Generare's $21.5 million to scale molecular-data and drug-discovery - WhiteLab Genomics' $25 million to expand AI-driven genomic medicine The pattern is clear: investors are betting on the combo of biological data generation, computational models, and experimental validation. ### How Rivercell's AI Virtual Cell Works Founded in 2026, Rivercell is building a data engine and an AI model that predict how living cells respond to drugs and genetic changes. Their in-house platform produces interventional, time-resolved, multimodal single-cell data at scale. That data trains their AI world model — the "AI virtual cell" (AIVC). The goal? Predict how human cells respond to a drug or genetic change in silico, reducing the need for physical wet-lab experiments. Developing a single drug can take years and cost a fortune. The industry spends nearly $300 billion on R&D every year. If Rivercell can shave time and cost off that process, it's a game-changer. > "AI is already rewriting how we understand the chemistry of life, from protein structure to molecular design. The next frontier is predicting how cells behave." — Maxi Pethö-Schramm, Principal at HV ### The Team Behind the Vision Yann Fleureau isn't new to this. He co-founded and led AI diagnostics company Cardiologs, which Philips acquired in a nine-figure deal in 2021. His co-founder, Eric Durand, was director of oncology data science at Novartis and Chief Data Science Officer at Owkin before co-founding Bioptimus, a bio foundation model company that raised $76 million. With roots in both Paris's AI ecosystem and Basel's pharma cluster, Rivercell is positioning itself at the intersection of two worlds. And they're doing it with a full-stack approach: novel platform, automated wet labs, and world models. ### What This Means for Drug Discovery If Rivercell succeeds, drug discovery could become faster, cheaper, and more precise. Instead of testing thousands of compounds in physical labs, researchers could run simulations first — narrowing down the best candidates before ever touching a pipette. That's the promise of AI virtual cells. And with $25 million in fresh funding, Rivercell is now racing to make it real. The question isn't whether AI will transform biotech — it's how quickly startups like this can turn bold ideas into working technology.