Case study: Covariate adjustment
Authors
Case study: Covariate adjustment
Authors
About Owkin
Owkin is an AI biotechnology company that uses AI to find the right treatment for every patient. We combine the best of human and artificial intelligence to answer the research questions shared by biopharma and academic researchers. By closing the translational gap between complex biology and new treatments, we bring new diagnostics and drugs to patients sooner.
We use AI to identify new treatments, de-risk and accelerate clinical trials and build diagnostic tools. Using federated learning, a pioneering collaborative AI framework, Owkin enables partners to unlock valuable insights from siloed datasets while protecting patient privacy and securing proprietary data.
Owkin was co-founded by Thomas Clozel MD, a former assistant professor in clinical onco-hematology, and Gilles Wainrib, a pioneer in the field of machine learning in biology, in 2016. Owkin has raised over $300 million and became a unicorn through investments from leading biopharma companies (Sanofi and BMS) and venture funds (Fidelity, GV and BPI, among others).
Deep learning to reduce sample size requirement for adjuvant HCC trials
Context
No treatment is yet approved in the hepatocellular carcinoma (HCC) adjuvant setting.
Methods
Owkin developed the HCCNet model for prognosis of resected hepatocellular carcinoma patients. Using public liver patient data, we evaluate the added value of HCCnet as an adjustment covariate.
Results
Results show the use of Owkin’s HCCNet model outputs as an additional adjustment in an adjuvant trial setting. HCCnet is added to tumor stage and ECOG to evaluate its added value.
Covariate adjustment on HCCNet achieves +6% statistical power with the same number of patients, and the same statistical power with 12% fewer patients.
Impact
De-risk phase 3 trial by maximizing the probability of achieving statistical significance.
Shorten timelines by reaching significance at an earlier interim analysis.
Reduce enrolment needs, hence trial timelines, costs and time to launch.