SciTransfer
EUCAN-Connect · Project

Privacy-Safe Health Data Analysis Across Borders Without Moving Sensitive Records

healthTestedTRL 5
eucanconnect.eu

Imagine hospitals and research institutes across Europe and Canada each holding valuable patient records, but nobody is allowed to pool them together because of privacy laws. EUCAN-Connect built a system where the data never leaves its home — instead, the analysis travels to the data. Think of it like accountants visiting each bank branch to do calculations, rather than shipping all the money to one vault. The result is that researchers can study millions of health records across 9 countries to find disease patterns, without anyone's personal information ever crossing a border.

By the numbers
15
consortium partners across the platform
9
countries connected (AT, CA, DK, ES, FI, FR, NL, PT, UK)
26
total project deliverables produced
2
digital risk estimation tools developed
2
SME partners in the consortium
The business problem

What needed solving

Healthcare and pharma companies need to analyze patient data spread across hospitals and countries, but strict privacy laws like GDPR make it illegal or impractical to move sensitive health records into a single database. This creates a massive bottleneck: valuable insights about disease patterns and treatment outcomes remain locked inside institutional silos, slowing down drug development, clinical research, and personalized medicine.

The solution

What was built

The project built a federated data platform with the DataSHIELD open data API (demonstrated with MOLGENIS), at least two digital risk estimation tools, and a bioinformatics toolbox — all designed so analyses travel to distributed data sources rather than centralizing sensitive records. A total of 26 deliverables were produced, including governance documentation and a sustainability roadmap.

Audience

Who needs this

Health data analytics companies managing multi-site clinical datasetsPharmaceutical companies running cross-border real-world evidence studiesHealth IT vendors wanting to add federated analytics to their platformsPublic health agencies analyzing population cohort data across jurisdictionsBiobanks and research infrastructure networks seeking interoperable data tools
Business applications

Who can put this to work

Health Data Analytics
mid-size
Target: Health data platform or analytics company handling multi-site clinical data

If you are a health data analytics company struggling to combine patient datasets across hospitals or countries due to GDPR and privacy regulations — this project developed DataSHIELD, a federated analysis system that lets you run computations on distributed data without the data ever leaving its source. It was tested across 15 partner organizations in 9 countries, with at least two digital risk estimation tools ready for deployment.

Pharmaceutical Research
enterprise
Target: Pharma or biotech company running multi-center clinical studies

If you are a pharmaceutical company needing to analyze real-world patient cohort data from multiple countries for drug development or post-market surveillance — this project built an open API that lets software providers connect to the DataSHIELD federated network. This means your existing analytics tools can plug into a privacy-safe data mesh spanning 9 countries, accelerating evidence generation without regulatory headaches.

Health IT & Software
any
Target: EHR or clinical data management software vendor

If you are a health IT vendor looking to add federated analytics to your platform — this project created the DataSHIELD open data API, demonstrated with MOLGENIS, that enables third-party software to interface with federated health data networks. With 26 deliverables including a bioinformatics toolbox, you gain a proven integration path to offer cross-border analytics as a feature without building from scratch.

Frequently asked

Quick answers

What would it cost to adopt this federated data platform?

The DataSHIELD platform and bioinformatics toolbox are open source, meaning no licensing fees for the core software. However, integration costs depend on your existing infrastructure and data formats. Contact the coordinator through SciTransfer for a tailored assessment.

Can this scale to handle large datasets across many sites?

Yes. The platform was designed and tested across 15 partner organizations in 9 countries, handling cohort data for genome-wide complex trait analysis. The architecture is explicitly described as open and scalable, built to work with federated nodes where data stays local.

What is the IP and licensing situation?

The project emphasizes open source development and FAIR principles (Findable, Accessible, Interoperable, Reusable). The DataSHIELD open data API is designed as an open standard for third-party software integration. Specific licensing terms for individual tools should be confirmed with the development team.

Does this comply with GDPR and cross-border data regulations?

This is the core design principle. Sensitive data never leaves its source location — only aggregated results are shared and integrated. The project explicitly addressed ELSI (Ethical, Legal, Social Implications) and international governance guidelines across EU and Canadian jurisdictions.

How long would integration take for our existing systems?

The DataSHIELD open data API was specifically built so software providers can extend their existing tools to interface with the federated network. Feasibility was demonstrated with MOLGENIS, suggesting integration is practical. The project ran from 2019 to 2023 and produced 26 deliverables documenting the process.

Is there ongoing support and maintenance after the project ended?

Long-term sustainability is coordinated through BBMRI-ERIC in Europe and Maelstrom Research in Canada, both established research infrastructure organizations. The project also delivered a report on what would be required to take the bioinformatics toolbox beyond EUCAN-Connect.

What health domains does this cover?

The platform was validated on early-life origins of cardio-metabolic, developmental, musculoskeletal, and respiratory health and disease across the human life course. At least two digital risk estimation tools were developed for these domains.

Consortium

Who built it

The 15-partner consortium spans 9 countries and is heavily research-oriented, with 7 universities and 6 research organizations making up 87% of partners. Only 2 industry partners (both SMEs) are involved, giving a 13% industry ratio — which signals this is still closer to research infrastructure than a commercial product. The coordinator is Academisch Ziekenhuis Groningen, a Dutch university hospital, reinforcing the clinical research focus. For a business looking to adopt this technology, the low industry involvement means you would likely be among early commercial adopters, with the advantage of shaping how these tools enter the market but the need to invest in adaptation from research to production environments.

How to reach the team

Academisch Ziekenhuis Groningen, Netherlands — contact via SciTransfer for warm introduction

Order a report on this consortiumSee ACADEMISCH ZIEKENHUIS GRONINGEN profile →
Next steps

Talk to the team behind this work.

Want to connect with the EUCAN-Connect team to explore federated health data analytics for your organization? SciTransfer can arrange an introduction and help you evaluate fit.

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