Summary
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.
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| Web resources: | https://cordis.europa.eu/project/id/899932 |
| Start date: | 01-04-2020 |
| End date: | 30-06-2022 |
| Total budget - Public funding: | - 150 000,00 Euro |
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Original description
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.Status
CLOSEDCall topic
ERC-2019-POCUpdate Date
27-04-2024
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