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Translate-AD


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Added by:   National contact point
Added on:   02 Oct 2025
Updated by:   OECD analyst
Updated on:   25 Dec 2025

The Translate-AD project unites six universities and university hospitals (VUB, UZ Brussel, ULB, Hôpital Erasme, Université Catholique de Louvain (UCL), and Cliniques Universitaires St. Luc) in developing digital platform designed to streamline the exchange patient data among these institutions. Initially tailored to Alzheimer’s patients in Brussels, the platform is envisioned to expand in the long term to other Belgian and international centers.

Name in original language

VUB, UZ Brussel, ULB, Hôpital Erasme, Université Catholique de Louvain (UCL), and Cliniques Universitaires St. Luc

Initiative overview

In Belgium, an estimated 200,000 people suffer from dementia, with around 6% of them being under 65 years of age. The most common cause is Alzheimer’s disease, responsible for 70% of dementia cases in the region. Alzheimer’s is also the leading cause of death in Belgium. The disease causes the loss of brain cells and the breakdown of connections between them, leading to memory loss and cognitive decline. However, many questions about the origins of Alzheimer’s remain unanswered, partly because privacy laws have made the sharing of patient data for collaborative research challenging.

To address this need, researchers in the Translate-AD project will develop a digital platform to facilitate the exchange of expertise and patient data between university hospitals. This will enable the identification of biomarkers – the ‘fingerprints’ of diseases that predict whether someone has or will develop a condition. The project will improve diagnosis and prognosis, a milestone in treating a disease whose progression is difficult to predict. Additionally, a better understanding of the disease will likely lead to new therapeutic possibilities.

The platform will allow researchers to tackle even the most complex research questions together, without the need to exchange patient data. A research question will be translated into a script, which is then sent from a central research computer to local hospital servers. All data analyses will be conducted on these local servers, where anonymised patient data is stored. Once complete, the results of the data analysis are sent from the local servers back to the central research computer. This approach makes research collaboration far easier while fully respecting privacy regulations.

Name of responsible organisation (in English)

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About the policy initiative


Organisation:

  • -

Category:

  • AI policy initiatives, programmes and projects

Initiative type:

  • Initiative to promote data access and sharing

Status:

  • Active

Start Year:

  • 2024

Binding:

  • Non-binding