Project description
Synthetic data for advanced personalised medicine
Traditional data-sharing platforms that focus on overcoming technical barriers create challenges for the healthcare industry and the research community in developing tools for personalised healthcare using explainable AI. The EU-funded SEARCH project aims to address European biomedical challenges and advance personalised medicine by enabling comprehensive data aggregation and analysis while protecting the integrity and privacy of original datasets through synthetic data proxies. It will tackle legal, ownership, and subject privacy concerns, specifically targeting distributed institutional repositories that are hesitant to share multimodal clinical data. The project will combine clinical synthetic data proxies with a federated learning framework to overcome security concerns, promote public-private data collaborations, create synthetic datasets for evaluating biomedical AI solutions, and drive innovation in digital healthcare.
Objective
The objectives of SEARCH are truly ground-breaking, seeking to enable extensive data aggregation and analysis while safeguarding the integrity and privacy of original datasets through synthetically derived proxies. This initiative is designed to address biomedical challenges in Europe and offer translational solutions that will ultimately contribute to the advancement of personalised medicine. Unlike traditional data-sharing platforms that mainly focus on technical obstacles, SEARCH adopts an innovative approach by addressing legal, ownership, and subject privacy concerns. It specifically targets distributed institutional repositories that are hesitant to share multimodal clinical data, overcoming security concerns through a combination of clinical synthetic data proxies and a Federated Learning framework. Until synthetic data proxies gain wider acceptance, this combined strategy aimed at alleviating security concerns, facilitates the scalability required for AI analysis and promotes creative public-private data collaborations.
SEARCH will offer advanced data federation capabilities, incorporating unique Synthetic Data Generation features to create various data types, including those not comprehensively addressed currently (e.g. wearable device data, image sequences, and genomic data). Through curated access to these novel digital tools, SEARCH will facilitate convenient access for the healthcare industry and research community to address bottlenecks and challenges in the development of novel tools for personalized prevention, diagnosis and treatment based on explainable AI. Moreover, SEARCH will provide agreed-upon gold standard synthetic datasets for evaluating the performance of biomedical AI solutions. SEARCH aims to consolidate European Innovation and Research endeavours by promoting public and private collaborations to unlock the potential for innovation in the digital healthcare sector.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
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Keywords
Programme(s)
- HORIZON.2.1 - Health Main Programme
- HORIZON.2.1.7 - Innovative Health Initiative
Funding Scheme
HORIZON-JU-RIA - HORIZON JU Research and Innovation ActionsCoordinator
D02 CX56 Dublin
Ireland
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Participants (24)
D03 Y6A2 DUBLIN
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8953 DIETIKON
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
76131 Karlsruhe
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
2595 AN The Hague
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
D15 HN66 DUBLIN
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8152 Glattpark
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1831 Diegem
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325 Haifa Haifa
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38221 Volos
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0167 Oslo
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48160 DERIO BIZKAIA
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1165 Kobenhavn
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7100 Vejle
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462 80 VANERSBORG
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08025 Barcelona
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151 23 Marousi
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50132 Limassol
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
47822 Santarcangelo Di Romagna
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11632 Athina
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
11741 Athina
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
40476 DUSSELDORF
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08005 Barcelona
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3000 LEUVEN
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
E1 8FA LONDON
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partners (5)
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
28046 Madrid
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
81477 Munchen
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
8005 Zurich
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
Participation ended
E1 8FA LONDON
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
8953 DIETIKON
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.