NUTRIclock: a tool based on microbiome and artificial intelligence for implementing precision nutrition.

ended

The aging process is nowadays the major risk factor for chronic diseases. Understanding its mechanisms and developing interventions to modulate it constitute a major challenge in order to increase both our life and healthspan. The nutritional interventions have arisen as a potent instrument to influence aging mechanisms. However, the great variability of the effect of nutrition in different persons requires the development of proper tools to characterize the impact of a nutritional treatment. Here, we propose the development of NUTRIclock, an algorithm based on the latest advances in artificial intelligence and microbiome data directed to implement personalized nutrition by characterizing the effect of nutritional interventions on the aging process and health status of an individual. NUTRIclock will be the first algorithm designed to specifically address the interaction of nutrition with aging and the specific changes occurring in the microbiota. We have conceived this project as the opportunity to develop an instrument useful to implement precision nutrition strategies. It will be highly translational both in the design of public health plans through the application of efficient and personalized treatments, but also for the development in the food industry of new products and approaches to enhance the precision nutrition field. The implementation of this project will require the combination of the expertise in biocomputing of the hosting group and my background in molecular sciences and aging signaling. Importantly, I will strengthen my current bioinformatic knowledge, increasing my capacity to develop scientific projects making use of this powerful tool. In addition, I will sharpen my communication skills, instrumental for the dissemination of our work to the scientific community and the society. This project will enhance my professional career and help me to become an independent researcher in the nutrition, aging and bioinformatic field.