OWKINUnprecedented collaborations for precision medicine
The Owkin Platform
We connect life sciences companies with world-class academic researchers and hospitals to share deep medical insights for drug discovery and development. Using Federated Learning, and breakthrough collaborative AI technology, we enable our partners to unlock siloed datasets while protecting patient privacy and securing proprietary data. Through sharing high-value insights we power unprecedented collaboration to improve patient outcomes.Get in touch
We help life sciences develop the most effective treatments at scale. Faster.
Owkin unlocks medical insights from siloed, multimodal datasets to help life science companies discover new drugs and novel biomarkers, optimize clinical trials, and rapidly identify patient populations of interest.Learn more about Owkin AI Drug Development Solutions.
Discover how machine learning can predict genomic phenotypes from images, across cancer types. Learn more about our AI Patient Identification Tool that predicts best responders to PARP inhibitor treatment in patients with ovarian cancer.
We help researchers collaborate with our Federated Learning technology
Deploy our privacy-preserving infrastructure to implement partnerships with your network of research collaborators.
Discover how 10 of the world’s largest pharma companies are combining the power of their data to accelerate drug discovery without sharing proprietary information. Owkin collaborative Federated Learning technology is making it happen.
We help you solve the most challenging research questions through our Data Alliances
We Believe in Connections
Owkin technologies connect the dots between raw medical data and ultimate patient outcomes. The COVID-19 pandemic has shown the need for unparalleled collaboration to accelerate breakthrough connections and arrive at actionable insights faster.
We bring a multimodal approach to cancer research in order to rapidly & efficiently identify specific biomarkers in patients. We believe the future of medicine lies in using machine learning on multimodal datasets with a focus on histo-genomic connections in oncology.