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Owkin maximizes the value of your data and makes it actionable for AI
Our growing patient data and KOL network
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Our approach to data

Owkin works with top academic centers to curate, enrich, and generate deep, multimodal data that is AI-ready

Multimodal patient data
Multimodal patient data and samples

Research-grade patient data and samples including rich modalities like spatial omics for a full heterogeneous view of the disease. 

Access to up-to-date data
Continuous access to the most up-to-date data

Privacy-enhanced federated access to 8 of top 20 oncology and general hospitals in US and Europe with the latest Standard of Care (SoC) and longitudinal data.

Research-grade patient data curated by PIs
Research-grade patient data curated with PIs

Complete AI-ready datasets enabled and contextualized through close relationships with PIs including 118 KOLs with a mean H-index of 50.


Barriers to develop and validate AI across datasets


Data is distributed across several institutions, sites, and infrastructures with competing incentives


Healthcare data is private and/or proprietary


GDPR, HIPAA, EU AI Act, and country specific regulations

Care vs AI

Data is collected for patient care, not for use in machine learning research


Different systems have different labels and structures


Heterogeneous, missing data, lacks medical context

Different modalities

Integrating multimodal data from different sources


Accessing data that reflects the latest SoC and new modalities like spatial omics that offer new research opportunities

Owkin’s solutions

Data services for Owkin sponsored projects

Owkin helps academic partners to upgrade their data to accelerate their AI research in real world healthcare settings. Our data services:

Data curation

Make your existing data AI-ready and interoperable (enriched, harmonized, FAIRified)

Data generation

We help you generate and analyze new data in cutting-edge modalities

Abstra: Owkin's collaboration platform

Owkin is building a collaborative platform that will make research-grade biomedical data searchable and will connect academic partners with each other and with data scientists.

Data catalog

Comprehensive metadata catalog of public and private cancer, cardiovascular and inflammation & immunology datasets

Data science environment

Infrastructure to train models and facilitate collaboration between academic researchers and data scientists

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Collaborative research case studies

Accelerating research

We combine privacy-enhancing technologies, like federated learning, with critical clinical expertise and a network of academic researchers.

Federated learning software breaks medical silos and accelerates innovation in real-world healthcare settings.

What is federated learning?

Federated learning

Connect disjointed data to build accurate models without pooling data

Unlocking access

Federated learning powers precision medicine by unlocking access to the right quality and quantity of data to train high-performance models

Data stays local

With federated learning the data stays local - only models and insights travel between the servers, enhancing privacy and ensuring compliance

More accurate models

This technology allows research communities to benefit from access to more datasets; training on heterogenous data to generate more robust and accurate models

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“In terms of security, Owkin provided the methodology, as well as the external audits which, for us, are a guarantee of security. Owkin's philosophy of excellence and speed is closely aligned to that of cancer centers - there's a great cultural fit. Today, if we wanted to apply AI to our data, I wouldn't think twice - I'd call Owkin.”
Thierry Durand
Head of IT Systems at Centre Léon Bérard