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Datrix Group wins a 10 million euro grant for a European AI-driven Project dedicated to Healthcare, coordinating an international medical-scientific consortium


Milan, 16 November 2023 – Datrix (ticker: DATA), a leading Group in the development of Artificial Intelligence applications to accelerate the data-driven growth of businesses, announces the award of a significant European grant (Horizon Europe) in the field of AI for Healthcare. 

The research project is named “BETTER” (Better Real-World Health-Data Distributed Analytics Research Platform, Grant agreement 101136262) and aims to create an easily accessible platform for European hospital doctors. They will be able to use it to view patient data – comparable and filterable by pathology or genetic parameters – and train predictive models, adhering to the most stringent global privacy regulations related to health information. This is achieved through a “Federated Learning” and “Distributed AI” approach.

As a matter of fact, Datrix’s advanced Federated Learning models enable the sharing of insights without exchanging sensitive data, preserving user privacy rights as well as the accuracy of results. This not only reinforces the protection of user-related data but also promotes a healthier, integrated relationship between humans and machines, aligned with the vision of a symbiotic AI working in harmony with human and social dynamics.

As project coordinator, Datrix once again distinguishes itself as a leading player capable of attracting funding from the European Commission to Italy and demonstrating commitment to innovation in international medical research based on Artificial Intelligence and Data Science. 

Specifically, 49 proposals were submitted in this call by various European consortia, of which only 4 were funded by the European Commission following the evaluation process. 

The BETTER project, coordinated by Datrix, secured the top position, receiving the highest evaluation: 15 points out of 15.

The total funds allocated at the European level amount to 10 million euros, with approximately half earmarked for genetic sequencing, crucial in the analysis of rare pediatric diseases, autism spectrum disorders in children and adolescents, and congenital visual problems, with a focus on retinal diseases.

“This is a significant milestone for Datrix, confirming the Group’s ability to be at the forefront of innovation, attract substantial financial resources from the European Commission, and prove its leadership in innovation projects as coordinators of a prestigious consortium. The consortium includes universities, research centers, and international clinical institutes,” comments Fabrizio Milano d’Aragona, Co-Founder & CEO of Datrix. “In addition to accessing innovative technological assets and gaining expertise on cutting-edge topics, the BETTER project will allow us to deepen our ongoing research on Federated Learning, a new approach in the AI world, adding value to society. Federated data management surpasses the limits dictated by privacy regulations, enabling the pooling of patient information and utilizing genetic components to prevent, diagnose, and treat many serious conditions.”

The project was officially approved in August 2023 and will commence on December 1, 2023. 

The R&D activities will continue for three and a half years, involving various Italian institutions and clinics, such as the Buzzi Pediatric Hospital in Milan, Politecnico di Milano, numerous technological partners from across Europe, and university and hospital centers providing their data. Partners include Klinikum Der Universitaet Zu Koeln (DE), Maastricht University (NL), Universitat Politècnica de València (ES), Aston University (UK), Universitetet i Tromsø (NO), RheaSoft ApSm (DK), Noosware Bv (NL), Fundació de Recerca Sant Joan de Déu (ES), Hospital Sant Joan de Déu, Fundació Docència i Recerca Mutua de Terrassa (ES), Hospital Universitario y Politécnico La Fe(ES), Institute of Molecular Genetics and Genetic Engineering (RS), and Hadassah Medical Center (IL).

The five main research objectives are:

1. Overcoming cross-border barriers for the integration, access, “FAIRification,” management, and sharing of scientific and health data.

2. Enriching health databases with open data and data from other hospital centers.

3. Implementing a distributed analysis framework (Federated Learning) for the processing and analysis of medical data applicable throughout Europe.

4. Developing tools to support doctors that leverage the capabilities of Artificial Intelligence and extensive cross-border databases.

5. Awareness of ethical, legal, and social aspects (ELSA) in the life cycle of AI (Trustworthy AI).

The teams will rely on diverse and cutting-edge technologies, introducing new approaches such as:

Distributed AI and Federated Learning: Unlike traditional approaches where data is centralized to train machine learning models, Federated Learning involves training various models on different available databases, then aggregating the models into a single central model. This allows training algorithms without the need to move or centralize the data, making it suitable for working with data collected from various hospital centers located in different nations.

FAIRification, the crucial activity of standardizing and homogenizing databases to make them readable and usable with the same interface.

Personal Health Train (PHT) model, a paradigm of distributed analysis for medical data, already experimented on a local scale.

“There is increasing talk of ‘Precision Medicine,’ a data-driven medicine that can use clinical data to improve diagnosis and treatment. However, this requires overcoming multiple challenges related to technological barriers, data management, and privacy. The ‘BETTER’ project enables Precision Medicine and aligns with the European Health Data Space initiative: a European-level genetic database, a common database accessible to all hospitals through interoperable data,” explains Matteo Bregonzio, CTO of Datrix and head of the R&D department. “The framework we aim to create seeks to define a robust decentralized infrastructure that will allow researchers and medical professionals to fully exploit the potential of community health data and tailor-made AI tools, with the ultimate goal of improving citizens’ health.”