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

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.