H2020
Europeo
Expected Outcome:This topic aims at supporting activities that are enabling or contributing to one or several expected impacts of destination 5 “Unlocking the full potential of new tools, technologies and digital solutions for a healthy society”. To that end, proposals under this topic should aim for delivering results that are directed towards and contributing to most of the following expected outcomes:
Researchers, innovators and healthcare professionals benefit from better linkage of health data from various sources, including genomics, based on harmonised approaches related to data structure, format and quality, applicable across certain disease areas and across national borders.Researchers, innovators, healthcare professionals and health policymakers have access to advanced digital tools for the integration, management and analysis of various health data re-used in a secure, cost-effective and clinically meaningful way enabling the improvement of health outcomes.By linking and using effectively more data and new methods and tools, including artificial intelligence, researchers, innovators and healthcare professionals are able to advance our understanding of the ri...
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Expected Outcome:This topic aims at supporting activities that are enabling or contributing to one or several expected impacts of destination 5 “Unlocking the full potential of new tools, technologies and digital solutions for a healthy society”. To that end, proposals under this topic should aim for delivering results that are directed towards and contributing to most of the following expected outcomes:
Researchers, innovators and healthcare professionals benefit from better linkage of health data from various sources, including genomics, based on harmonised approaches related to data structure, format and quality, applicable across certain disease areas and across national borders.Researchers, innovators, healthcare professionals and health policymakers have access to advanced digital tools for the integration, management and analysis of various health data re-used in a secure, cost-effective and clinically meaningful way enabling the improvement of health outcomes.By linking and using effectively more data and new methods and tools, including artificial intelligence, researchers, innovators and healthcare professionals are able to advance our understanding of the risk factors, causes, development and optimal treatment in disease areas where genomics integrated with other health data, spanning from clinical to e.g. lifestyle, offer potential for novel and more comprehensive information.Healthcare professionals and health policymakers benefit from data-driven solutions and reinforced evidence base for decisions addressing health and care challenges.Citizens can be offered data-driven patient-focused health interventions, resulting in improved disease prevention, diagnosis, treatment and monitoring towards better patient outcomes and well-being.Citizens’ trust in the sharing and re-use of health data for research and healthcare increases due to the application of advanced technologies and data governance preserving data privacy and security. Scope:Health data bear vast information potential in many disease areas, to significantly improve the outcomes and efficiency of healthcare delivery, unlock new research and innovation avenues, and inform public health policy across Europe. There is a huge need of integration, use and deployment of health data from multiple sources for effectively addressing the challenges of medical research underpinning diagnostics, therapy guidance and implementation decisions on new therapies. Such integration requires linking data of different types, disease areas and provenance which are scattered in repositories and databases across Europe.
This topic aims to support proposals focusing on the integration of health data from multiple sources (e.g. electronic health records, genomics, medical imaging, laboratory and diagnostic results, pathogen data, public health registries and other clinical research data) by linking real-world and clinical research data. The data integration should be exemplified in several use-cases, i.e. well-justified groups of diseases (excluding cancer), within and/or across medical domains, and pave the way towards improved health outcomes. At least one of those use cases should build on the use of whole genome sequence data.
The consortium should ensure wide coverage of EU and associated countries, contributing significantly to health data standardisation, while catering for the diversity of health data sources.
To enhance synergies and avoid overlaps of activities, the proposals are expected to align with and complement the relevant European initiatives, in particular the European Health Data Space (EHDS), the 1+Million Genomes initiative (1+MG) and the European Open Science Cloud.
The applicants have to demonstrate that the necessary data sources are, or will be, effectively, timely and legally available for the proposed research activities.
The proposals should address all of the following activities:
Identification of the barriers to health data integration and access as needed for the selected use cases, and of specific existing tools, technological solutions and coordination and standardisation agreements addressing those barriers. Issues to be covered include semantic ontologies, data standards and formats, data quality, data storage, management and access modalities, as well as enhanced findability of relevant datasets through improved metadata standards and data catalogues.New approaches to assemble large, easily findable and lawfully accessible high-quality datasets integrating multiple types of health data leading to improved clinical outcomes (e.g. new care solutions, personalised disease management, advanced diagnostic tools), taking into account data FAIRification[1] and inter-operability needs.New techniques, support tools, mechanisms and modalities to enable GDPR compliant access to sensitive personal data, including genomics, allowing for their re-use across borders and integration of different types of data relevant to human health. Legal and ethical frameworks should duly consider the heterogeneity in national and sectorial rules and procedures for data access and re-use.Data management approaches for cross-border distributed data storage and processing, enabling remote collaboration, electronic consent management, data provenance tracking, and scalability of data management resources, ensuring data privacy and security, and resulting in robust support to advanced, innovative clinical workflows. Joint data governance is expected to be piloted among several clinical centres across Europe.Development of a data analytics platform applying distributed learning and artificial intelligence approaches to query and aggregate efficiently, effectively and securely data from multiple sources for multiple use cases (groups of diseases), to monitor patients' health status, analyse causal inference, support diagnosis and health policymakers, and establish recommendations for patients and other stakeholders. The proposals should adhere to the FAIR data[1] principles and build on existing and justified tools and harmonisation efforts, such as widely used standards for encoding the different types of health data and inter-operability for cross-sector collaborations. Also the data collection, management and/or modelling should build on ongoing EU and international efforts to avoid possible duplication of efforts and fragmentation. In particular, projects are expected to take into account the legislation, if available, on the EHDS, so as to align project activities with pertinent EHDS infrastructure efforts that provide for the secondary use of health data as regards e.g. cross-border access to data, cross-border infrastructures, data quality and utility labelling. The achievements of the relevant past and ongoing EU-funded projects and initiatives, and good practices developed by the European research infrastructures, should be duly considered and used. Close involvement of patients and end-users is crucial to ensure that the project outcomes are relevant, widely accepted and feasible in real-world settings.
The tools developed by the projects are expected to be widely accessible and amenable to necessary updates after the project’s end for further use by interested parties. Datasets generated during the project should be accessible to researchers and innovators. For example, genomic data and linked patient level data are expected to be made accessible for secondary use through the 1+MG data infrastructure.
This topic requires an effective contribution of social sciences and humanities (SSH) disciplines and the involvement of SSH experts, in order to produce meaningful and significant effects enhancing the societal impact of the related research activities.
All projects funded under this topic are strongly encouraged to participate in networking and joint activities. These networking and joint activities could, for example, involve the participation in joint workshops, the exchange of knowledge, the development and adoption of best practices, or joint communication activities. This could also involve networking and joint activities with projects funded under other clusters and pillars of Horizon Europe, or other EU programmes. Therefore, proposals are expected to include a budget for the attendance to regular joint meetings and may consider covering the costs of any other potential joint activities without the prerequisite to detail concrete joint activities at this stage. The details of these joint activities will be defined during the grant agreement preparation phase. In this regard, the Commission may take on the role of facilitator for networking and exchanges, including with relevant stakeholders.
Applicants envisaging to include clinical studies should provide details of their clinical studies in the dedicated annex using the template provided in the submission system. See definition of clinical studies in the introduction to this work programme part.
[1] See definition of FAIR data in the introduction to this work programme part.
[2] See definition of FAIR data in the introduction to this work programme part.
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La ayuda es de ámbito europeo, puede aplicar a esta linea cualquier empresa que forme parte de la Comunidad Europea.
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Presupuesto medio
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Grande
17%
0€
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