Project description
Innovative diagnostic and prognostic platform for coronavirus pandemics
The EU-funded DRAGON project is supporting the effort of a multinational consortium of academic research institutes, biotech and pharma partners, affiliated patient-centred organisations and professional societies to develop a multifaceted diagnostic and prognostic platform to prevent and fight future coronavirus pandemics. Data from the current pandemic will be used to validate and optimise diagnostic and prognostic solutions. Using advanced AI techniques, molecular profiling will be shaped into a precision medicine approach for the accelerated development of new therapies. The proposed study will be one of the first to develop innovative machine learning techniques and introduce clinical procedure improvements that will potentially have a breakthrough impact on future coronavirus outbreaks.
Objective
In this project, a multinational consortium of high-tech SMEs, academic research institutes, biotech and pharma partners, affiliated patient-centred organisations and professional societies will achieve a multi-faceted diagnostic and prognostic platform and a precision medicine approach. This consortium will together realize a patient empowerment centred decision support system that will enable multiple stakeholders to participate in improved and more rapid diagnosis and prognosis, as well as the potential of precision medicine for accelerated development of new therapies. Citizens and patients will be empowered to contribute to the efficient planning and usage of resources. The project will begin by rapidly delivering a nomogram. Data from the pandemic will be used to validate and further optimise a scalable multifactorial diagnosis/prognosis solution. Existing and new data and sample collection efforts will be used to perform molecular profiling, which - using advanced AI techniques will be shaped into a precision medicine approach. These initial outputs will undergo further enhancement and assessment to evaluate the value they add to the development of a decision support system. The entire effort will be supported by the deployment of a federated machine learning system that will allow for the GDPR compliant use of multinational data resources. The various iterations of the decision support system and the federated machine learning system will be made available to other coronavirus initiatives with the intent to develop a stakeholder community that forms the basis for a highly efficient innovation ecosystem. Our proposed study will be one of the first to develop innovative machine learning, and clinical procedure improvement that will potentially make a huge socio-economic impact for the coronavirus outbreak.
Fields of science
- medical and health scienceshealth sciencespublic healthepidemiologypandemics
- medical and health scienceshealth sciencesinfectious diseasesRNA virusescoronaviruses
- medical and health scienceshealth sciencespersonalized medicine
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Keywords
Programme(s)
Topic(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
6200 MD Maastricht
Netherlands
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Participants (18)
6525EC Nijmegen
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
3631 Maasmechelen
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
SW7 2AZ LONDON
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1060 Bruxelles / Brussel
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
50121 Florence
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4000 LIEGE
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
4000 LIEGE
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
SO45 3PN Southampton
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1003 Lausanne
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S10 2PX Sheffield
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Participation ended
LS2 7UE Leeds
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CB2 1TN Cambridge
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CB4 0GA Cambridge
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
L69 7ZX Liverpool
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SO17 1BJ Southampton
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4000 Liege
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43121 PARMA
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1040 Bruxelles / Brussel
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