Algorithm-Based Personalized Nutrition Platform Improves Key Blood Biomarkers In Healthy Humans

Tuesday, October 2, 2018 Diet & Nutrition News
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The first peer-reviewed paper of its kind validates that a completely automated algorithmic platform can improve the wellness of its users through ultra-personalized nutrition interventions.

CAMBRIDGE, Mass., Oct. 2, 2018 /PRNewswire/ -- InsideTracker, a personalized nutrition and wellness company, today announced

the publication of a landmark paper in peer-reviewed journal Scientific Reports, titled "Longitudinal analysis of biomarker data from a personalized nutrition platform in healthy subjects." The paper features a study which demonstrates for the first time that automated, web-based personalized nutrition platforms like InsideTracker are effective in improving the wellness of users through the generation of personalized dietary interventions. Tracking a broad age-range of >1000 relatively healthy InsideTracker users over time, the study finds that nutrition recommendations provided by a smart algorithm are not only accurate, but work to optimize key markers of health that concern the majority of today's global population, such as blood sugar, cholesterol, and inflammation.

InsideTracker's patent pending algorithm generates ultra-customized diet recommendations by reading an individual user's bloodwork and comparing it to a comprehensive database of over 100,000 people – more data than any nutritionist or physician could effectively analyze on their own. The expert system matches the most relevant, science-based recommendations to each individual based on blood data and demographics, as well as on self-reported preferences and wellness goals. Implementing these personalized recommendations and tracking changes in bloodwork over time may allow users to improve critical markers of wellness in a more targeted way than with the help of a healthcare provider alone. An individual's level of blood sugar, for instance, is a key predictor of future health and longevity. Management of blood sugar is a challenge that affects a significant portion of the world. Importantly, the study finds that InsideTracker's automated algorithm is effective in reducing blood sugar levels by tailoring nutrition recommendations to each individual's needs.

This represents a significant milestone for both the personalized nutrition industry and precision health, as it is the first such rigorous study to receive peer-reviewed acceptance and validation by the scientific community.

"This paper validates our founding science team's vision that personalization can powerfully improve quality of life, and that our research helped create the technology to bring personalization to the masses," says InsideTracker founder and CSO, Gil Blander, PhD.

The paper aggregates data and technology amassed and analyzed over the past nine years as a collaboration between InsideTracker and its vastly experienced, multidisciplinary scientific team, including leaders in the fields of nutrition, aging, bioinformatics, and technology, from Harvard, MIT, and Tufts University. It represents a crowning achievement for the group. Esteemed Harvard geneticist David Sinclair, co-director of the Paul F. Glenn Center for the Biological Mechanisms of Aging, chairman of the InsideTracker scientific advisory board, and a co-author of the paper, adds: "This is an exciting milestone for InsideTracker – one that may be seen as a turning point in human health. I can imagine people looking back one day wondering how was it possible that people modified their diet blind to what was going on inside, and only went to their doctors once a year for a checkup or after they became sick."

Based in Cambridge, Massachusetts, InsideTracker provides sophisticated, science-based blood analytics through the measurement and analysis of over 40 blood serum biomarkers and DNA. Using a fully-automated smart algorithm, InsideTracker gives users an easy-to-read snapshot of their blood and generates appropriate, personalized nutrition and lifestyle interventions aimed at improving overall health and wellness. The platform is driven by the patent pending SegterraX algorithm, which serves as a powerful enabler for the expert system designed and continually refined by InsideTracker scientists, and represents the culmination of over 70 person-years of work.

A lack of human bias along with high computational power that can select the most biochemically relevant interventions for an individual user from thousands of possibilities, is what gives the InsideTracker algorithm its edge. As an automated web-based system it is unique in its mass scalability, and thus, potential for global adoption by any individual interested in improving their health, in a world where scientific information is abundant but individual direction is often lacking.

"This study is important because it shows that the InsideTracker algorithm can guide people toward managing their own health by making appropriate dietary and lifestyle modifications," explains InsideTracker scientific advisory board member Leonard Guarente, Ph.D., Novartis Professor of Biology at the Massachusetts Institute of Technology.

The paper can be found by visiting: www.nature.com/articles/s41598-018-33008-7

About InsideTrackerInsideTracker is an innovative health analytics company whose mission is to empower people to improve their health and performance through science, quantification, and personalization. Founded by leading scientists from MIT, Tufts, and Harvard, the InsideTracker platform analyzes key biomarkers related to health and performance, and provides actionable guidance tailored to each individual user. Our technology delivers a simple, accessible, personalized, and scientific action plan each person can follow to optimize their health and achieve their goals.

Media Contacts:InsideTracker: Ross Yellin  – ryellin@insidetracker.com 617-588-3215

Cision View original content:http://www.prnewswire.com/news-releases/algorithm-based-personalized-nutrition-platform-improves-key-blood-biomarkers-in-healthy-humans-300722478.html

SOURCE InsideTracker



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