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

Project description

DEENESFRITPL

AI guides omics-driven research for haematological diseases

Accumulating evidence points towards personalised medicine to treat and manage common, rare and ultra-rare haematological diseases. To address this need and support research further, the EU-funded GenoMed4ALL project will develop a data-sharing platform that utilises novel advanced AI models. The project's partners will share infrastructure, powerful computing facilities, hospital registries and data processing tools towards this effort. Advanced statistics and machine learning approaches will contribute to the exploitation of omics and clinical data in patient-oriented research and decision-making. Collectively, these tools will lead to improved therapies and better clinical outcomes.

Objective

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.

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Topic(s)

Call for proposal

H2020-SC1-FA-DTS-2018-2020

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Sub call

H2020-SC1-FA-DTS-2020-1

Funding Scheme

RIA - Research and Innovation action

Coordinator

UNIVERSIDAD POLITECNICA DE MADRID
Net EU contribution
€ 869 375,00
Address
Calle ramiro de maeztu 7 edificio rectorado
28040 Madrid
Spain

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Region
Comunidad de Madrid Comunidad de Madrid Madrid
Activity type
Higher or Secondary Education Establishments
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Other funding
€ 0,00

Participants (28)

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Last update: 4 December 2023

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Permalink: https://cordis.europa.eu/project/id/101017549

European Union, 2023