Tel-Aviv’s Nutrino uses AI to recommend diet plans based on signals like stress and activity levels. Medical device giant Medtronic acquired Nutrino at the end of 2018, with the stated aim of using its technology to help patients with diabetes. Buoyed by the broader wellness trend, the personalized nutrition market is expected to continue to grow in the coming years as more and more people expect the same amount of personalization that they get from other industries like fashion and entertainment. From 3D-printed pills to DNA-driven dietary recommendations and nutrient-tracking mouth wearables, the idea is to achieve better health through wellness offerings which are tailored to each user’s individual circumstances.
With that said, we need to remember that the current generation of personalized nutrition platforms can’t replace advice from qualified professionals. Many wellness wearables still aren’t ready to go to market, while up-and-coming fields like nutrient genomics are being subjected to ever-increasing skepticism and scrutiny. We’ll need to make significant advancements if we want to establish public trust and to maintain it over the longer term. We’ve already seen a number of high-profile failures in this space for well-funded companies like Arrivale, Ubiome and Driver, all of which had high price tags and niche customer segments. Each of their business models relied on consumers spending a large amount of money to buy a product with uncertain benefits.
The National Institutes of Health have been carrying out new research that centers on precision nutrition and which should be instrumental to the growth of the field. One study, announced at the start of 2022, is nested in the organization’s All of Us research program, which aims to enroll a million people in healthcare research to promote precision medicine and to speed up the pace of medical discoveries. The goal is to gather data that we can use to create healthy and effective diet plans that are grounded in human diversity and which are tailored to each individual patient.
Research into precision nutrition will allow us to build on the advances we’ve already made in biomedical science, much of which comes from the fields of AI, genetics and microbiomes. All of this research will contribute additional data on people’s dietary habits, and we’ll be able to use a combination of AI processing and data mining to create and validate algorithms that can be used in clinics.
We’re seeing ever-increasing demand for better wellness and more personalized nutrition, and we can hope that this will eventually encourage mainstream consumers to improve their health. It all depends whether technology and its real-life applications can fulfill their full potential. The next step is to do prospective studies to see if personalized nutrition really does help with better weight loss, improved blood lipids, and other areas.
