• Ingenix's Biological Reasoning Engine fuses biological data through Modality Fusion, a new architecture for AI in drug development.
• In a recent oncology engagement, the Biological Reasoning Engine accomplished in minutes what had taken the partner biotech several years and millions of euros of research.
• The team brings together frontier AI researchers and senior pharma scientists, including the founders of Applica, the AI company acquired by Snowflake in 2022, whose TILT model contributed to the GPT-4 benchmark.

WARSAW, June 3, 2026 /CNW/ -- Ingenix, the AI and biology company built around a single question - "What would it take for AI to truly understand biology?" - has today announced a €13m seed-extension funding round led by Sofinnova Partners, with participation from Inovo VC and OTB VC.

The funding will scale development of Ingenix's Biological Reasoning Engine and broaden its work with pharma and biotech partners through the Qualified Access Program, launching today.

The dominant approach in AI for drug development, which trains larger models on larger datasets assuming biology will yield to scale, faces a structural problem. Biology is profoundly complex, fundamentally non-linguistic, and runs across modalities and biological scales. No single model, however large, can capture that on its own. Moreover, no single company holds all the data, across every modality and biological scale, to train one. Ingenix has built a different architecture, Modality Fusion, which integrates best-in-class models across modalities and biological scales, then reasons across their representations directly. The Biological Reasoning Engine is what Modality Fusion enables.

"This funding lets us extend the Biological Reasoning Engine to the partners and questions where it can do the most useful work," said Piotr Surma, CEO and co-founder of Ingenix. "We built Ingenix on the conviction that biology needs an AI architecture designed for biology and not a general-purpose model retrofitted to it. The early results have been stronger than we forecast, and we're excited to extend the Engine to a select number of partners through the Qualified Access Program."

"It is no longer enough to just build models," added Simon Turner, Partner at Sofinnova Partners. "Ingenix is building the reasoning layer, the part that actually connects the biology, the chemistry, and the clinical data into something a scientist can interrogate and act on. That's the hard bit, and that's where the value compounds. We're thrilled to back a team that gets that."

The Engine in Action: ADC Payload Prioritization

In a recent engagement, Ingenix applied its Biological Reasoning Engine to a dual-payload ADC prioritization problem for an oncology biotech which had thousands of possible payload configurations but lacked the experimental capacity to test them.

The Engine produced 15 candidate combinations. Under blind expert review by the biotech's translational science team, the predictions broke down as follows:

• 5 were publicly known hypotheses.
• 2 were supported in existing literature but not widely cited.
• 3 had been confirmed by the biotech through internal experiments but never published and never disclosed to Ingenix.
• 5 were novel hypotheses not previously considered by the biotech team. Of these, the biotech flagged 3 as actionable candidates.

The double-payload ADC space is too new for any AI system to have seen meaningful training data on it. The engine reached its predictions by reasoning from first principles about the underlying biology, rather than by pattern-matching against prior examples.

In short, insights that had taken the biotech several years of research and millions of euros to develop were accomplished by the Engine in a matter of minutes.

Applications to the Qualified Access Program are now open at ingenix.ai/qap.

For all media enquiries, please contact:

Barnaby Pickering, Director, 59 North Communications Barnaby.Pickering@59north.bio

Jo Shorthouse, Director, 59 North Communications Jo.Shorthouse@59north.bio

About Ingenix

Ingenix was founded around a single question: what would it take for AI to truly understand biology? The Ingenix Biological Reasoning Engine is the company's answer.  Built on Modality Fusion, a novel AI architecture that integrates best-in-class models across modalities and biological scales, then reasons across their representations directly. Ingenix is the first to name this approach and the first to bring it to biology. The engine is built for translational and clinical R&D decisions, and every output arrives with the reasoning trace behind it: mechanism, evidence, and the caveats laid out alongside the conclusions. Founded in 2023 and headquartered in Warsaw, Ingenix is led by AI researchers and engineers from the founding team of Applica, the AI company acquired by Snowflake in 2022, whose TILT model contributed to the GPT-4 benchmark. For more information, visit ingenix.ai.

About Sofinnova Partners

Sofinnova Partners is a leading European venture capital firm in life sciences, specializing in healthcare and sustainability. Based in Paris, London and Milan, the firm brings together a team of professionals from all over the world with strong scientific, medical and business expertise. Sofinnova Partners is a hands-on company builder across the entire value chain of life sciences investments, from seed to later-stage. Founded in 1972, Sofinnova Partners is a deeply established venture capital firm in Europe, with 50 years of experience backing over 500 companies and creating market leaders around the globe. Today, Sofinnova Partners manages over €4 billion in assets. For more information, please visit: sofinnovapartners.com.

About OTB VC

OTB Ventures is a pan-European deep tech VC fund specializing in Series A and late seed rounds. Its focus lies in supporting startups that pioneer unique technologies across three key verticals: AI and Novel Computing, SpaceTech and Robotics and Physical AI. Established in 2017, OTB Ventures currently manages c. EUR350 million and has offices in Warsaw, Luxembourg and Amsterdam.

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SOURCE Ingenix