Project description
Supplements to strengthen cooperation in ICT R&D in an enlarged European Union
Data-rich, individualised medicine poses unprecedented challenges for IT, in hardware, storage and communication. We propose a data-driven, individualised medicine of the future, based on molecular/physiological/anatomical data from individual patients. We shall make general models of human pathways, tissues, diseases and ultimately of the human as a whole. Individualised versions of the models, produced for each patient, will then be used to identify personalised prevention/therapy schedules and side effects of drugs.
To develop this IT driven, data rich, individualised medicine of the future, this first-phase flagship project will prepare for the amalgamation of 5 major areas: medicine, from sample and diagnosis provision to clinical practice and patient consent, analytical techniques, covering functional genomics and imaging technology analyses on a routine basis, IT developments required to address the computational challenges, and integration, developing interfaces, modelling and machine learning tools required to integrate the data generated through the different analysis streams, and to inform relevant health providers. A coordination work package will address the administrative, educational, funding and translational components of the work.
This is the first time the huge IT implications of worldwide individualized patient care will be addressed and combined with up-to-date genomics and requirements from the medical field. The project outcomes will enable the calculation of health, disease, therapy and its effects for individual patients. These may revolutionize our health care with enormous (i) benefits for health (prevention, diagnosis and therapy), (ii) reduction in health care cost by individualising combinations of a limited number of drugs, and (iii) new commercial opportunities in the IT, analytic and health care sectors.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences genetics
- natural sciences computer and information sciences artificial intelligence machine learning
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
FP7-ICT-2011-FET-F
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Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
80539 MUNCHEN
Germany
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Participants (24)
1210 Wien
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8010 GRAZ
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1000 BRUXELLES
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1211 Geneve
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12489 Berlin
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10117 Berlin
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69117 Heidelberg
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08028 Barcelona
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75015 PARIS 15
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69006 Lyon
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50121 FIRENZE
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4365 ESCH-SUR-ALZETTE
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Participation ended
1081 HV Amsterdam
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6200 MD Maastricht
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1081 HV Amsterdam
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1010 Auckland
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100 44 Stockholm
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751 05 Uppsala
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SW7 2AZ London
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M13 9PL Manchester
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CB10 1SA SAFFRON WALDEN
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WC1E 6BT LONDON
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CB21 6DF Great Abington
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LE1 7RH Leicester
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