Rare haematological diseases affect millions of people in Europe, yet more than 70% of these conditions are classified as rare, meaning that clinical data are scarce, fragmented and often locked within isolated hospitals or national registries. This lack of accessible, high-quality data slows medical research, limits the development of innovative treatments, and hampers the use of artificial intelligence (AI) methods that rely on large, diverse datasets. At the same time, strict European data protection rules are essential to safeguard patients’ privacy, creating additional challenges for cross-border research.
Against this background, the SYNTHEMA Research and Innovation Action was launched under Horizon Europe to address a central challenge in modern healthcare: how to unlock the value of sensitive health data for research and innovation, while fully respecting privacy, ethics and European regulations. The project focuses on rare haematological diseases, using two representative clinical cases: sickle cell disease, a non-oncological condition, and acute myeloid leukaemia, a haematological malignancy.
The overall objective of SYNTHEMA is to enable secure, privacy-preserving reuse of health data by developing advanced methods to anonymise data and generate high-quality synthetic data. Synthetic data are artificially generated datasets that reproduce the statistical and clinical properties of real patient data without revealing personal information. By combining synthetic data generation with federated learning – an approach that allows AI models to be trained across multiple institutions without moving raw data – SYNTHEMA aims to overcome data silos and support GDPR-compliant research across Europe.
The project pathway to impact is built around three interconnected elements. First, SYNTHEMA establishes a cross-border federated computing infrastructure connecting health data centres, research organisations and technology providers. Second, it develops and validates innovative AI pipelines for anonymisation and synthetic data generation, ensuring an optimal balance between data utility and privacy protection. Third, it embeds ethical, legal and social considerations into the technical design, ensuring trustworthy AI and responsible data governance.
By widening access to realistic, privacy-safe data, SYNTHEMA is expected to significantly increase the scale and quality of research in rare haematological diseases. Its results support European health data strategies, contribute to the development of the European Health Data Space and provide reusable tools and standards that can be transferred to other disease areas beyond haematology.
