Owkin

Owkin integrates human and artificial intelligence to deliver better drugs and diagnostics at scale. The company has unparalleled access to multimodal patient data, including privacy-enhanced access to up-to-date patient data and samples. Owkin’s AI engines leverage expertise in AI, biology, and medicine to understand biological interactions and deliver novel drug targets. Their AI diagnostics help pre-screen for biomarkers and predict outcomes, aiding healthcare providers in treatment decisions. Owkin has locations in Boston, New York, London, Paris, Nantes, Geneva, and Berlin, and has strategic deals with top biopharma companies like Sanofi, BMS, and MSD. Owkin’s MSIntuit® CRC is a CE-marked AI diagnostic tool for screening MSI in colorectal cancer. The company has raised over $300 million from leading biopharma companies and venture funds. Owkin’s federated learning technology allows for collaborative research without sharing data between partners, and their MOSAIC project aims to create the largest spatial omics atlas for cancer research. Owkin’s AI external control arms provide early efficacy estimates for single-arm phase I/II clinical trials, and their inclusion criteria models help define patient subgroups to improve trial recruitment. Their data-driven covariate adjustment increases the probability of phase III trial success. Owkin’s federated research network includes top academic centers and provides access to research-grade patient data. The company’s AI-powered drug discovery engines identify new drug targets and optimize drug positioning. Owkin’s RlapsRisk® BC is an AI diagnostic tool to assess the risk of relapse in early breast cancer patients. Their AI diagnostics integrate seamlessly into digital pathology workflows, and their AI models are designed to be interpretable by researchers and medical experts. Owkin’s federated learning software, Substra, enables training and validation of machine learning models on distributed datasets. The company’s AI ethics and safety team focuses on minimizing bias, validating AI models, and ensuring responsible AI deployment.