GenoMed4ALL

Genomics and Personalized Medicine for all though Artificial Intelligence in Haematological Diseases

Abstract

GENOMED4ALL will support the pooling of genomic, clinical data and other “-omics” health data (data EHR, PET, MRI and CT , Next Generation Sequencing, Microarray, Genome Wide Association, Copy Number Variations, DNA sequencing, RNA sequencing, including single cell, etc.) through a secure and privacy respectful data sharing platform based on the novel Federated Learning scheme, to advance research in personalised medicine in haematological diseases thanks to advanced novel AI models and standardized sharing of cross-border data. GENOMED4ALL will make use of the existing infrastructures and initiatives, including powerful High Performance Computing facilities, hospital registries, data processing tools, and pre-existing repositories, starting from 10 clinical partners repositories to be enlarged especially by the resources provided by ERN-EuroBloodNet where GENOMED4ALL clinical partners have a leading position, which contain 66 relevant clinical sites providing repositories and knowledge, for the successful exploitation of genomics, clinical and other related “- omics” data to facilitate personalised medicine in common, rare and ultrarare haematological diseases to demonstrate the versatility and utility of the solutions, and 20 external of this network. GENOMED4ALL will demonstrate the potential and benefits of trustable and explainable AI technologies, with a novel approach to AI models and algorithms using AI advanced deep learning, variational autoencoders, generative models, besides combining with advanced statistical and Machine learning processes approaches to exploit the powerful set of “- omics” data which will be at researchers’ disposal. This will allow for identifying new knowledge, to support clinical research and decision making by linking Europe's relevant genomic repositories in haematological diseases, while ensuring full compliance with data protection legislation and ethical principles, and increasing the AI trust for personalized medicine.

Project details

Unibo Team Leader: Gastone Castellani

Unibo involved Department/s:
Dipartimento di Medicina Specialistica, Diagnostica e Sperimentale
Dipartimento di Fisica e Astronomia "Augusto Righi"

Coordinator:
Universidad Politécnica De Madrid (Spain)

Other Participants:
ALMA MATER STUDIORUM - Università di Bologna (Italy)

Total Eu Contribution: EUR 9.999.063,75
Project Duration in months: 48
Start Date: 01/01/2021
End Date: 31/12/2024

Cordis webpage

UE flag This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101017549