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AEGLE · Project

Big Data Platform That Turns Messy Hospital Records Into Fast Clinical Decisions

healthPilotedTRL 7
aegle-uhealth.eu

Imagine every hospital, lab, and clinic generates mountains of patient data — but none of it talks to each other. AEGLE built a cloud-based engine that pulls all that scattered health data together, crunches it at high speed, and gives doctors clear visual dashboards to make faster treatment decisions. Think of it like a Google Translate for medical data: it takes information in different formats and languages and turns it into something a doctor can actually act on in real time.

By the numbers
15
consortium partners across Europe
8
countries in the validation network
3
clinical use cases tested (biostreams, non-malignant diseases, chronic diseases)
5
industry partners including SMEs
13
total project deliverables produced
3
prototype iterations including final certified product
The business problem

What needed solving

Hospitals and healthcare organizations drown in patient data from dozens of incompatible systems — electronic health records, genomic sequencing, real-time monitoring, medication logs — but can't use it to make timely clinical decisions. The data is too big, too varied, and arrives too fast for existing tools, which means doctors miss patterns that could save lives and money.

The solution

What was built

AEGLE built a cloud-based big data analytics platform for healthcare that went through 3 prototype iterations and achieved certification. The final product integrates cloud computing, high-performance computing acceleration, and advanced visualization to process health data across 3 clinical domains: real-time biostreams, genomic/molecular data for non-malignant diseases, and chronic disease EHRs with medication tracking.

Audience

Who needs this

Hospital IT directors managing multi-site electronic health record systemsPharmaceutical companies processing large-scale genomic and molecular datasetsHealth insurance companies building integrated care programs for chronic diseasesNational health services modernizing their data infrastructureClinical research organizations needing faster big data analytics
Business applications

Who can put this to work

Hospital IT & Health Informatics
enterprise
Target: Hospital chains or health IT departments managing electronic health records across multiple sites

If you are a hospital network struggling with patient data scattered across departments and legacy systems — this project developed a cloud-based analytics platform tested across 3 clinical use cases (critical biostreams, non-malignant diseases, chronic diseases with EHRs) that can unify and visualize patient data for faster clinical decisions. The consortium of 15 partners across 8 countries validated this in real clinical settings.

Pharmaceutical & Life Sciences
enterprise
Target: Pharma companies or CROs needing to analyze large-scale genomic and molecular datasets

If you are a pharma company dealing with massive next-generation sequencing and molecular data that takes too long to process — this project built high-performance computing acceleration specifically for big biodata analytics, combining cloud resources with local data visualization. With 6 university partners contributing clinical domain expertise, the platform handles the volume, versatility, and velocity of modern biomedical datasets.

Health Insurance & Integrated Care
mid-size
Target: Health insurers or integrated care organizations managing chronic disease populations

If you are a care organization managing chronic disease patients across borders and languages — this project developed multi-lingual analytics for EHRs and medication data, extracting clinical parameters and handling regulatory requirements for integrated care. The platform was designed for cross-border deployment, validated with partners from 8 European countries.

Frequently asked

Quick answers

What would it cost to license or deploy this platform?

Based on available project data, AEGLE was developed as an Innovation Action with a business ecosystem for wider exploitation. The project went through certification (a dedicated deliverable exists for this). Specific licensing costs are not published — contact the coordinator for commercial terms.

Can this scale to handle our hospital network's data volume?

AEGLE was specifically designed to handle the 3Vs of health big data: volume, versatility, and velocity. It uses cloud computing for dynamic resource allocation and HPC infrastructure for computational acceleration, meaning it can scale up processing power on demand. It was validated across 3 distinct clinical use cases with different data characteristics.

Who owns the intellectual property and how is it licensed?

The coordinator is EXODUS, a Greek SME in the IT sector. With 5 industry partners including 5 SMEs in the 15-partner consortium, IP is likely shared among partners. A dedicated certification deliverable suggests the product was prepared for commercial deployment. Contact the coordinator for specific IP and licensing arrangements.

Does this comply with healthcare data regulations like GDPR?

The project objective explicitly mentions handling regulatory issues for integrated care, particularly around EHRs and medication data. The certification deliverable further suggests regulatory compliance was addressed. Given the project ended in 2018 (when GDPR took effect), specific compliance details should be verified with the consortium.

How long would integration with our existing systems take?

AEGLE was designed for integration with existing open databases and built to handle heterogeneous, multi-modal, multi-lingual data sources. The project produced 13 deliverables including 3 prototype iterations, suggesting a mature integration approach. However, timeline depends on your specific IT environment.

Was this actually tested in real clinical environments?

Yes. AEGLE was evaluated in 3 real clinical scenarios: critical biostreams requiring real-time clinical decision support, non-malignant diseases with genomic data, and chronic diseases with EHR and medication data. The project produced a third integrated prototype and a final product deliverable, indicating iterative real-world testing.

Is there ongoing support or has the project ended?

The project officially ended in August 2018. The coordinator EXODUS is an active Greek IT company (SME). The project website aegle-uhealth.eu may have current information on post-project availability and support arrangements.

Consortium

Who built it

The AEGLE consortium brings together 15 partners from 8 European countries, with a balanced mix of 6 universities providing clinical and research expertise, 5 industry players (all SMEs) bringing commercial focus, and 2 research organizations plus 2 other entities. The 33% industry ratio is solid for a health data project — enough commercial drive to push toward a real product, which is confirmed by the certification and final product deliverables. The coordinator EXODUS is a Greek IT company (SME), which means the commercial lead is a nimble, tech-focused firm rather than a slow-moving institution. Partners span Belgium, Greece, France, Italy, Netherlands, Portugal, Sweden, and the UK, giving the platform built-in multi-lingual and cross-border validation — critical for any company wanting to deploy health analytics across European markets.

How to reach the team

EXODUS is a Greek IT company (SME) that coordinated the project. Search for EXODUS Anonymos Etaireia Pliroforikis to find current contact details.

Order a report on this consortiumSee EXODUS ANONYMOS ETAIREIA PLIROFORIKIS profile →
Next steps

Talk to the team behind this work.

Want an introduction to the AEGLE team? SciTransfer can connect you with the right person for licensing, integration, or pilot discussions.

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