AIRIS will provide biomedical and clinical researchers with reusable Generative AI tools for multimodal data harmonisation, synthetic data generation, hypothesis generation, predictive modelling and cross-scale analysis.

AIRIS will establish benchmarks for Generative AI in biomedical research, providing reference metrics for validity, robustness, fairness, transparency, explainability and usability. Together with reusable mechanism-informed models and methodologies, these resources will strengthen Europe’s capacity in biologically grounded, transparent and trustworthy AI for health.

Ultimately, AIRIS aims to help translate advances in AI and biomedical research into benefits for patients and society. Faster and more targeted research, improved prediction and earlier identification of disease risk could support more personalised approaches to prevention, diagnosis and treatment, contributing to better health outcomes and more effective healthcare – particularly for chronic, complex and hard-to-treat diseases.

Through researcher-friendly interfaces, training, open documentation and benchmarking, AIRIS will support the critical and responsible use of Generative AI in biomedical research. Transparency, explainability, bias monitoring, ethical oversight and responsible data governance will help build trust and address potential risks. By providing open resources and transferable methodologies, AIRIS will strengthen Europe’s ecosystem for trustworthy AI in health, support more efficient and personalised healthcare innovation, improve research productivity and help build confidence in AI-enabled healthcare among researchers, clinicians and citizens.