Hacking Blood Sugar

My wife and I are working with a health coach at Arivale to help us with diet and lifestyle choices. (Note: Arivale has since gone out of business). This data-driven coaching draws on analysis of my DNA, gut biome and saliva, blood sugar, and a number of other factors.

Lee Hood is the founder of Arivale and a pioneer in biology instrumentation, including inventing the first automated DNA sequencer. The year before I gave my talk at TEDx Rainier, Lee was on that same stage giving us his vision for the future of personalized medicine:

I mention Lee’s vision because it is at the core of why we are working with Arivale. Our coach uses all that data we’re collecting on our biology to tweak her recommendations for diet and exercise. In the not-too-distant future, we will all have some version of this kind of personalized health advice. But more on that in a moment.

In my call with my coach today, I went over my glucose levels which I only test every six months as part of a blood draw that looks at a bunch of other stuff:

She was explaining how blood sugars work and how to interpret my numbers, so it was a nice coincidence to get a notification a few hours later that a friend of mine from business school, Richard Sprague, had just published a piece in NEO.LIFE on monitoring his blood sugar using a device from Abbott, called FreeStyle Libre. As Richard describes it, it’s a “button-sized sensor patch you stick painlessly on your arm that measures blood glucose once a minute.” Once a minute. Compare that to what I’m tracking now, which is once every six months.

Richard has always been an interesting guy and now he’s using this and other devices to measure glucose loads after drinking wine and eating ramen and oatmeal; he’s essentially hacking his blood sugar levels and adjusting his diet in a data-driven way. Or as he puts it:

And that may be the greatest benefit of these new self-tracking technologies. By giving me immediate, actionable insight into how food affects me, I’m able to adjust in time to have an impact. Wearing the FreeStyle Libre, even for a few weeks, let me taste a future where we can all learn how our bodies are unique and how to optimize their performance.


These kinds of devices will make it increasingly affordable to spread Arivale-like data-driven advisory capabilities to more and more health coaches. Over time, as more health sensors get built into our phones, watches, and other personal devices, the flood of data will be so ubiquitous that we will inevitably throw machine learning at the challenge of translating it into actionable health advice. It might not be as good as the advice I will get by collaborating with an actual coach using those same models, but it will be much less expensive and therefore more easily accessible to more people.

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