The ongoing study titled "The Nutrition for Precision Health," funded by the National Institutes of Health, is exploring personalized nutrition through artificial intelligence. This five-year project, with a budget of $200 million, aims to develop individualized dietary recommendations based on metabolic responses.
Illinois Institute of Technology collaborates with Northwestern University and the University of Chicago as part of this initiative. The consortium's objective is to monitor the diets of 9,000 participants, collecting biospecimens to analyze their metabolic reactions to typical and test meals. The data collected will be centralized and used by teams at West Point and City University of New York to create predictive algorithms.
Britt Burton-Freeman, director of Illinois Tech’s Center for Nutrition Research, stated, “With the amount of detailed data we will have on people under different conditions, we will be in a position to develop virtual people based on real people’s dietary responses to test diet-related hypotheses.” She further explained that AI simulations could provide insights into individualized dietary recommendations.
The research is divided into three modules. Illinois Tech handles data collection for modules one and two. Participants' diets are monitored over set periods: ten days for module one and two-week intervals for module two. During these times, participants follow a calorie-customized diet plan from Illinois Tech’s Metabolic Precision Nutrition Production Kitchen. After each period, they consume a standardized test meal at the Center for Nutrition Research.
Burton-Freeman noted the complexity involved in providing identical meals across participants: “Who’s making all that food for Illinois participants? Illinois Tech is,” she said. A dedicated kitchen prepares meals customized for weight maintenance across various locations including Illinois, California, Alabama, and Boston.
As more data becomes available, Burton-Freeman anticipates identifying clusters among participants based on their metabolic responses. These findings could inform AI-generated personalized nutrition plans tailored to individual health needs.
In its second year, about 25% of the data has been gathered. Researchers aim to reach their target participant number before entering a verification phase where AI predictions are tested.
“This is discovery science so we’ll see what we learn,” Burton-Freeman remarked about future prospects. The ultimate goal is using scientific evidence to explain varied dietary impacts on health and longevity.