NextGen is a Horizon Europe research initiative, co-funded by UKRI (United Kingdom) and SERI (Switzerland) that develops multimodal, multiomic data integration, i.e.  and federated analytics in personalised cardiovascular medicine.

Multimodal data combine different data formats – text, images, audio, or sensor readings – from varied sources or technologies, to provide a richer analytical perspective, while multiomic data integrate distinct biological datasets (e.g. genomics, transcriptomics, proteomics) to offer a comprehensive view of molecular processes underlying physiological or pathological states.

The project addresses the need to securely access and process sensitive health data owned by different institutions, including genomics, across jurisdictions and organisations, without moving the underlying data to protect privacy of highly sensitive information.

At the core of the project is the development and demonstration of the Pathfinder that functions as a prototype for the European Health Data Space (EHDS) in cardiovascular medicine with federated catalogues and analytics. It will serve as a proof-of-concept showing that secure, privacy-preserving, AI-supported health data analytics can be conducted at scale and across borders and across institutions.

The NextGen tools are integrated in the Pathfinder and are a suite of interoperable, AI-enabled software components designed to integrate and analyse multimodal, multiomic health data and that address the challenges in data linkage, portability, and governance to improve diagnosis, treatment, and research scalability across jurisdictions

Researchers, and the NextGen tools will not have direct access to the associated biobanks, but only to the outcomes of the implementation of the federated learning algorithms.

This first post launches a series on the tools developed in NextGen to provide an accessible and coordinate set of information on how they are capable of generating benefits for the diagnosis, prediction and treatment of cardiovascular disease.