Project description
Tailored diets using a computational approach
Nutrition plays a fundamental role in disease prevention and outcome during and after therapy since food contains ingredients that can function more or less as drugs. However, the large number of potential ingredient combinations makes it virtually impossible to optimise food profiles through standard experimental approaches. To this end, the EU-funded Hyperfoods project proposes to adopt a machine learning approach for the computational discovery and design of personalised nutrition. The Hyperfoods technology could pave the way for tailored diets to promote population well-being, help tackle diseases such as cancer and sustain the healthcare system.
Objective
With rapidly ageing populations, the world is experiencing an unsustainable healthcare and economic burden from chronic diseases such as cancer, cardiovascular, metabolic and neurodegenerative disorders. Diet and nutritional factors play an essential role in the prevention of these diseases and significantly influence disease outcome in patients during and after therapy. Everyday food ingredients contain multiple drug-like molecules that can potentially prevent or beat diseases. For example, it is estimated that up to half of oncological diseases can be prevented by dietary choices. The wide adoption of tailored health-promoting diets potentially has a revolutionary impact on the population wellbeing and long-term sustainability of the healthcare systems. However, due to an exponentially large number of combinations of the ingredients, their sourcing, processing, preparation, and preservation methods, it is virtually impossible to use traditional experimental approaches to optimise the health-promoting molecular profiles of foods. Hyperfoods will use novel graph-based ML methods to provide the technological capabilities for the computational discovery and design of personalised nutrition. We will explore the commercial opportunities of our technology for currently unmet business needs in global health, in particular cancer treatments.
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.
- medical and health sciences health sciences nutrition
- medical and health sciences clinical medicine oncology
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
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.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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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.
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.
ERC-POC - Proof of Concept Grant
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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.
(opens in new window) ERC-2019-PoC
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
SW7 2AZ London
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.