Project description
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.
Fields of science
- natural sciencescomputer and information sciencescomputer securitydata protection
- humanitiesphilosophy, ethics and religionethicsethical principles
- medical and health scienceshealth sciencespersonalized medicine
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcomputer hardwaresupercomputers
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
28040 Madrid
Spain
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Participants (29)
64293 Darmstadt
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28232 Madrid
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
Participation ended
29590 MALAGA
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
Participation ended
50197 Zaragoza
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00138 Roma
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
28005 MADRID
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
9860 OOSTERZELE
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20100 Rozzano (Mi)
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08035 Barcelona
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75012 Paris
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81377 Munchen
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
3584 CX Utrecht
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47007 Valladolid
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2371 AGIOS DOMETIOS
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35122 Padova
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04109 Leipzig
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10561 Athina
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40126 Bologna
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
40138 Bologna
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1165 Kobenhavn
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08003 Barcelona
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10124 Torino
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70013 Irakleio
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Participation ended
75382 Paris
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40033 Casalecchio Di Reno Bo
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28232 Madrid
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
29590 MALAGA
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77454 Marne-La-Vallee
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08028 Barcelona
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