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Preventomics is research & development project funded by the European Commission's Horizon 2020 Research and Innovation programme. The project builds a new paradigm in preventive personalised nutrition based on the potential of omics and behavioural flexibility.

Empowering consumers to prevent diet-related diseases through omic sciences

Preventomics will create a new integration of genetic, nutritional 
and psychological factors thanks to the application of state-of-the-art metabolomics technologies and computational modelling to assess the real incidence of disease-inducing factors on the organism.

The main outcome from Preventomics is a novel mFood Platform, a unique-in-its-kind service, interoperable with current existing Apps for monitoring health status and with personalised nutrition software, thus opening the door to the personalisation of any type of health treatment where combinations of genetic, biological, nutritional and psychological factors are important.

Preventomics will be validated in three 
different case scenarios, performing relevant interventional studies with healthy and obese volunteers, to demonstrate its potential for personalisation of nutrition at the three levels of the food value chain (processing and distribution, marketing and consuming closest to the end- users).

Project goals

Modular predictive DSS

Different disease-inducing metabolic signatures to provide personalised nutrition from simple blood and urine samples.

Functional ingredients

Adapted to personalised nutrition needs.

Do's for behaviour change

Personalised, digital and remote prompts to increase behavioural flexibility


Dynamic software platform

To elaborate and deliver personalised nutritional advices in constant evolution with the user and expand behavioural flexibility.

Personalised shopping experience and food manufacturing

Big Data and Artificial Intelligence technologies for diet customisation and a new service of personalised food manufacturing and delivery leveraging for the food industry.

Results and Conclusions

There were significant main effects of time (P < 0.01), but no group main effects, or time-by-group interactions, for the change in fat mass (personalized: −2.1 [95% CI -2.9, −1.4] kg; control: −2.0 [95% CI -2.7, −1.3] kg) and body weight (personalized: −3.1 [95% CI -4.1, −2.1] kg; control: −3.3 [95% CI −4.2, −2.4] kg). The difference between groups in fat mass change was −0.1 kg (95% CI −1.2, 0.9 kg, P = 0.77). Both diets resulted in significant improvements in insulin resistance and lipid profile, but there were no significant differences between groups.

Personalized dietary plans did not result in greater benefits over a generic, but generally healthy diet, in this 10-week clinical trial. Further studies are required to establish the soundness of different precision nutrition approaches, and translate this science into clinically relevant dietary advice to reduce the burden of obesity and its comorbidities.

The project has received €6,969,901 funding from the European Commission's Horizon 2020 Research and Innovation programme under agreement No. 818318.

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