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NEXT GENERATION TOOLS FOR GENOME-CENTRIC MULTIMODAL DATA INTEGRATION IN PERSONALISED CARDIOVASCULAR MEDICINE

Project description

Secured data integration in cardiovascular personalised medicine

Personalised medicine plays a crucial role in reducing the disease burden and enhancing quality of life. Integrating multiple data types, particularly genomic data, into AI models is essential for developing accurate interventions. However, this task is complex due to privacy and governance requirements, diverse standards, distinct data formats, and the sheer complexity and volume of the data involved. With this in mind, the EU-funded NextGen project will create tools to integrate data across various cardiovascular use cases. Project deliverables include tools for multimodal data integration, secure federated analytics, improved genomic data analysis, variant prioritisation, scalable genomic data curation, and enhanced data management. Additionally, the project will establish a governance framework and regulatory processes to ensure secure data access and alignment with EU initiatives.

Objective

Healthcare is the fasted growing EU27 expenditure. Personalised medicine, comprising tailored approaches for prevention, diagnosis, monitoring and treatment is essential to reduce the burden of disease and improve the quality of life. Integration of multiple data types (multimodal data) into artificial intelligence models is required for the development of accurate and personalised interventions. This is particularly true for the inclusion of genomic data, which is information-rich and individual-specific, and more routinely available as the cost of sequencing continues to fall. Multimodal data integration is complex due to privacy & governance requirements, the presence of multiple standards, distinct data formats, and underlying data complexity and volume. NextGen tools will remove barriers in data integration several cardiovascular use cases. NextGen deliverables will include tooling for multimodal data integration and research portability, extension of secure federated analytics to genomic computation, more effective federated learning over distributed infrastructures, more effective and accessible tools for genomic data analysis; improved clinical efficiency of variant prioritisation; scalable genomic data curation; and improved data discoverability and data management. A comprehensive gap analysis of the existing landscape, factoring ongoing initiatives will ensure NextGen deliverables are forward-looking and complementary. NextGen embedded governance framework and robust regulatory processes will ensure secure multi-jurisdictional multiomic multimodal data access aligned with initiatives including “1+ Million Genomes” and the European Health Data Space. Several real-world pilots will demonstrate the effectiveness of NextGen tools and will be integrated in the NextGen Pathfinder network of five collaborating clinical sites as a self-contained data ecosystem and comprehensive proof of concept.

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HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

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(opens in new window) HORIZON-HLTH-2023-TOOL-05

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Coordinator

UNIVERSITAIR MEDISCH CENTRUM UTRECHT
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 2 300 000,00
Address
HEIDELBERGLAAN 100
3584 CX Utrecht
Netherlands

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Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 2 300 000,00

Participants (14)

Partners (6)

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