InsideTracker Raises $15M for Healthspan Optimization

InsideTracker

Ultra-processed foods are killing us. Searching for solutions, startups are pitching personalized nutrition.

What’s happening: Using blood biometrics to optimize healthspan, InsideTracker raised $15M in a Series B round led by PeakBridge.

With personalized nutrition at the center, the AI-driven platform seeks to add years to its users’ lives by recommending the food and nutrients their bodies specifically need.

According to InsideTracker founder and chief science officer Dr. Gil Blander, the secret to aging well is right in front of us:

“Today, there are over 8,000 foods available, yet the average American only consumes around 20 different foods per week. To me, this means that we have a tremendous number of building blocks but are only using a few.”

The app analyzes blood and DNA tests, wearables, and demographic information alongside its nutrition, longevity, and chronic disease database to create one-of-one meal plans.

Food as Medicine

There’s a growing body of evidence that prescribing healthy food can prevent and treat chronic conditions like diabetes, heart disease, and some cancers.

Combining big data and home diagnostics, startups are getting closer to answering the age-old question of “what should I eat?”

  • January AI synthesizes CGM, wearable, food, and microbiome data, delivering personalized insights for better health.
  • Lumen, a breathalyzer device that allows you to “hack your metabolism,” partnered with meal kit service Metabolic Meals to personalize orders.
  • COR, which raised $12M this March, uses an at-home blood spectrometer to make recommendations for food, fitness, and general wellness.

Looking ahead: Precision nutrition platforms serve health optimizers who would do—and pay—anything to look and feel better. But the majority of Americans, knowing diet and exercise will help them live longer, still make unhealthy lifestyle choices. Until we democratize healthy food, our collective healthspans will continue to suffer.

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