Founded in 2023 as a spin-out of the Gustave Roussy cancer campus in France, Orakl bridges wet-lab experimental biology and machine learning by constructing cohorts of virtual cancer patients. Rather than training algorithms exclusively on static, retrospective genomic databases, the company cultures real patients’ tumors in the laboratory as three-dimensional organoids, pairing experimental drug-response screening with deep multi-omic profiling and longitudinal clinical records. This architecture generates proprietary, causal biological evidence showing how specific tumor subtypes respond to therapeutic compounds years before human trials begin.

Orakl’s predictive engine has demonstrated 90 percent accuracy in predicting cancer clinical trial outcomes, including prospective predictions that closely anticipated recent pancreatic cancer trial results. Beyond forecasting aggregate clinical endpoints such as progression-free survival, the platform identifies predictive biomarkers to stratify likely responders and uncovers biological mechanisms of drug sensitivity and resistance. Candidate discoveries are continuously validated on Orakl’s patient-derived models through a closed, lab-in-the-loop feedback cycle that refines model accuracy with every experiment. To expand this dataset, Orakl is actively negotiating contracts with more than 15 additional cancer centers across Europe, North America, and Asia to build one of the most comprehensive multimodal repositories in oncology.

With 18 of the world’s top 20 pharmaceutical companies already in its commercial pipeline—and early engagements converting into multi-year partnerships, including evaluating oncology assets for Sanofi—Orakl will deploy its Series A capital across four operational expansion fronts.

First, the company is expanding its proprietary dataset and growing its artificial intelligence research organization in Paris to deepen its foundational predictive models in cancer biology.

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