Impact
STRATA-FIT introduces a new way of using real-world health data to improve care for people with difficult-to-treat rheumatoid arthritis (D2T RA). By using federated learning, the project securely connects electronic health records from multiple rheumatology health units and registries without patient data ever leaving its original location. This privacy-preserving approach fully respects data protection laws such as GDPR and serves as a model for safe data sharing in healthcare.
Using this large, real-world dataset, STRATA-FIT develops and validates advanced data-driven models to identify, classify, and predict difficult-to-treat disease. These models enable the stratification of patients into clinically meaningful subgroups, supporting more personalised and effective treatment strategies. The models are translated into a clinical decision-support tool, aligned with EULAR recommendations, and tested in a clinical pilot study to assess feasibility, effectiveness, and cost-effectiveness in routine care.
The project also explores the biological mechanisms behind difficult-to-treat disease by combining clinical data with biomarker research and clinical trial data. This work lays the foundation for future preventive strategies, aiming to identify patients at risk earlier and intervene more effectively.
STRATA-FIT works closely with regulatory authorities, patients, clinicians, and professional societies to ensure that the developed tools are transparent, trustworthy, and suitable for regulatory approval. By embedding its results into European clinical guidelines, the project supports broad adoption in clinical practice.
At scale, STRATA-FIT has the potential to significantly reduce the health and economic burden of difficult-to-treat rheumatoid arthritis, improving patient quality of life while contributing to the sustainability of healthcare systems. Beyond rheumatoid arthritis, the project serves as a blueprint for learning healthcare systems, demonstrating how secure data sharing, artificial intelligence, and patient involvement can drive innovation across healthcare.
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Funded by the European Union (grant agreement no. 101080243). Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or the European Health and Digital Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.
The project has also received funding from the Swiss State Secretariat for Education, Research and Innovation (SERI) and from Hungary’s National Research, Development and Innovation (NRDI) Fund.