$34m · Series A · Healthtech · Villejuif, France
Orakl Oncology has raised $34m in Series A funding to scale its platform for predicting how cancer drugs will perform before clinical trials. Norrsken VC and Singular co-led the round.
Orakl grows patient-derived tumour organoids, tests drugs against them and combines the experimental results with molecular measurements and clinical histories. Its O-Predict product is designed to help biopharma teams identify likely responders, understand resistance and choose more promising drug programmes or combinations.
The new investors are InfraVia, Serena, the Patient Autonome Fund managed by Bpifrance, teampact.ventures and Plug and Play. Existing investors Verve Ventures, Speedinvest and HCVC also participated. Orakl says the round brings total funding to $50m.
Data generation is the moat and the constraint
Orakl's commercial argument depends on biology that cannot be scraped from public datasets. Each patient sample, organoid experiment, drug response and clinical history adds evidence connecting a treatment to a particular tumour context. That can make the dataset harder to reproduce, while also making growth capital-intensive: samples, laboratory capacity, hospital relationships and consistent experimental protocols all have to scale together.
The company says its predictive engine achieved 90% accuracy in prospectively predicting cancer clinical-trial outcomes. That is an investor-reported performance claim, not independent clinical validation. Pharmaceutical customers will ultimately judge the platform by whether its predictions improve programme selection and patient stratification across different drugs, cancer types and trial settings.
The funding will support a fivefold increase in data generation, expansion from colorectal and pancreatic cancer into lung and gastric cancer, and teams in the US and UK. Orakl also plans to apply predictions across more than 10 drug programmes and add co-target discovery, using patient biology and experimental screens to identify combinations that may overcome resistance.
That expansion turns the Series A into an operating test. More cancer types increase the potential market, but every new indication requires representative samples and evidence that the model transfers. If Orakl can reproduce its predictive value across those programmes, its platform can sit earlier in pharma decision-making, before companies commit the time and cost of clinical trials.
Related reading
TechBio x AI Drug Discovery: From Concept to Reality — Speedinvest & Estelle Botbol / EUVC · 4 December 2025. The analysis explains how Orakl's avatar biobank fits a broader move from computational promise to evidence-generating infrastructure.
