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DataROC, the AI generated and powered digital twin to accelerate Health Science

Objective

DataROC, the Open Science generative database to accelerate Biomedical Sciences, aims to design, develop, and validate an AI-powered digital twin model addressing key challenges in Health Research. It is a digital copy of the human body trained to identify missing scientific concepts, autocomplete them, and provide answers through a platform accessible to all researchers.

By integrating Health, Biology, Artificial Intelligence, and Epidemiology, it targets three complementary use cases covering discovery of new therapeutic mechanisms for complex diseases, early detection of pathologies, and comprehensive prevalence and prediction of pathologies, all based on the mechanistical understanding of scientific concepts, and not only on statistics anymore.

As a consortium of 12 partners, from 5 European countries, experts in artifical intelligence, scientific and clinical research, we have come together to cross-validate our findings, strengthen the model, provide data reproducibility, and finally develop this one-of-a-kind, powerful, and innovative database for the future of Research.

The platform associated to the digital twin will enable predictive, interpretable, and actionable data to assist researchers, clinicians, and public health authorities in making informed decisions, to generate, and to verify precious data necessary for research breakthroughs, clinical purpose and drug discovery.

This project funded by this HORIZON-INFRA-2025-01- Tech 04 – Virtual Twin for Sciences will benefit most researchers on a structural, OpenScience, and world-wide level, and also help research on neurodegenerative diseases, types of cancer, mental health, and more, with not only early detection, biomarkers, parameters for clinical research, but also mechanistical understanding leading to potential therapeutic options…

This interdisciplinary approach will foster innovation, accelerate treatment discovery, and strengthen European leadership in AI for Health Research.

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: The European Science Vocabulary.

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Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-INFRA-2025-01

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Coordinator

IROC
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.

€ 3 161 277,47
Address
12 rue du général Delestraint
75016 Paris
France

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Ile-de-France Ile-de-France Paris
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
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.

No data

Participants (10)

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