Most attempts to improve processed food stop at swapping ingredients: less sugar, fewer calories, lower salt. The evidence suggests that doesn’t solve the real problem.

A more useful way to approach reformulation is to focus on the metabolic systems most affected by ultra-processed foods. Think about protecting the liver by capping added sugar and fructose and reducing seed oils, feeding the gut by adding real fiber and removing emulsifiers that disrupt the microbiome, and supporting the brain by rebalancing fats and including essential nutrients. This way of thinking, sometimes called the metabolic matrix, has already been applied at scale in the Middle East, where a major food company reformulated hundreds of products.

The other missing piece is verification. Labels and nutrient panels don’t tell you whether a food reduces metabolic stress. Continuous glucose monitors do. A simple A/B test comparing the old and reformulated product shows immediately whether you flattened the glucose spike. That gives you real outcome data within days rather than waiting for epidemiology years later.

This frames reformulation as an engineering problem: change the inputs, define the constraints, then measure the outputs with real human data. It shifts the conversation from “does the label look better” to “does this food reduce glycemic pressure in practice.”

I’m curious whether others have tried using CGMs or other biometrics in product design. Could this become a standard tool for validating food and nutrition claims?