OwkinNEW

Owkin is a leading AI biotech company leveraging artificial intelligence and federated learning to accelerate drug discovery, development, and diagnostics. By integrating multimodal patient data from top-tier global academic medical centers, Owkin builds highly accurate biological models. The company focuses primarily on unraveling complex disease mechanisms in oncology, immunology, and cardiovascular diseases.

At the core of Owkin's technology is a decentralized federated learning architecture. Powered by the open-source Substra framework, it allows researchers to train AI models on sensitive clinical datasets directly within hospital infrastructure without transferring raw patient data. This guarantees strict privacy compliance while unlocking rich, global biomedical data repositories.

Owkin supports the full continuum of biopharmaceutical R&D, including target discovery, digital biomarker identification, and clinical trial optimization. Biopharmaceutical partners utilize Owkin's solutions to de-risk late-stage clinical trials and advance personalized precision medicine tailored to specific patient subpopulations.

• Federated Learning via Substra — Enables training AI models across distributed patient datasets natively within hospital servers. This maintains patient privacy while leveraging massive global data stores without data centralization.
• Multimodal Data Integration — Fuses digital pathology images, genomic profiles, and real-world clinical records into comprehensive disease models. This unlocks deeper biological insights into complex tumor microenvironments.
• Digital Biomarkers & Patient Stratification — Identifies novel digital biomarkers using deep learning to predict treatment response and disease prognosis. This assists researchers in stratifying patients effectively for targeted clinical trials.

Biopharmaceutical corporations, clinical researchers, oncologists, and academic medical centers focused on data-driven drug discovery and precision medicine.

A global biopharmaceutical company aims to develop a novel targeted cancer therapy but lacks sufficient internal clinical datasets. By partnering with Owkin and tapping into its federated network of academic hospitals, the company trains predictive AI models across data from dozens of cancer centers worldwide. This reveals key biomarkers for patient selection, reducing clinical trial failure rates and shortening the time required to bring the drug to market.

• Biopharmaceutical corporations, clinical researchers, oncologists, and academic medical centers focused on data-driven drug discovery and precision medicine.
• A global biopharmaceutical company aims to develop a novel targeted cancer therapy but lacks sufficient internal clinical datasets.
• Federated Learning via Substra: Enables training AI models across distributed patient datasets natively within hospital servers. This maintains patient privacy while leveraging massive global data stores without data centralization.
• Multimodal Data Integration: Fuses digital pathology images, genomic profiles, and real-world clinical records into comprehensive disease models. This unlocks deeper biological insights into complex tumor microenvironments.
• Digital Biomarkers & Patient Stratification: Identifies novel digital biomarkers using deep learning to predict treatment response and disease prognosis. This assists researchers in stratifying patients effectively for targeted clinical trials.

Not suitable for individual clinicians seeking routine medical reference tools, non-life sciences organizations, or businesses looking for generic generative AI solutions.

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