Eat this, not that, exercise now; new personalized software predicts and helps prevents blood sugar spikes – TechCrunch

Not everyone has type 2 diabetes, the disease that causes chronically high blood sugar levels, but many do. Around 9% of Americans are affected, and another 30% are at risk of developing.

Enter the software by January. AI, a four-year-old subscription-based startup that began offering customers personalized diet and activity suggestions in November based on a combination of food data the company tacitly collected over three years. and each person’s unique profile as determined over the first four days of that person’s use of the software.

Why the need for personalization? Believe it or not, people can react very differently to every single food, from rice to salad dressing.

The technology may sound trite, but it’s eye-opening and potentially life-saving, promises co-founder and CEO Nosheen Hashemi and her co-founder Michael Snyder, a Stanford genetics professor who has focused on diabetes and pre-diabetes for years.

Investors also like the idea. Felicis Ventures just launched a Series A investment of $ 21 million into the company with Marc Benioff, founder of HAND Capital and Salesforce. (Past investors include Jerry Yang’s Ame Cloud Ventures, SignalFire, YouTube co-founder Steve Chen, and Sunshine co-founder Marissa Mayer.) Felydis founder Aydin Senkut: “While other companies are making progress in understanding biometric sensor data have made – from heart rate and glucose monitors for example – January AI has made advances in analysis and Predictions the effects of food consumption itself [which is] Keys to Combating Chronic Diseases. “

To find out more, we spoke to Hashemi and Snyder this afternoon. Below is a portion of our chat edited for length and clarity.

TC: What did you build?

NH: We built a multi-comic platform that uses data from multiple sources and predicts people’s glycemic response so they can think about their decisions before making them. We use data from heart rate and continuous glucose monitors as well as a clinical study with 1,000 people and an atlas of 16 million foods, for which we have derived nutritional values ​​using machine learning and created a nutritional label [that didn’t exist previously].

[The idea is to] predict for [customers] What will your glycemic response to foods in our database be after just four days of training? You don’t actually have to eat the food to know whether or not to eat it; Our product tells you how to react to it.

TC: So there used to be glucose monitoring, but this is predictive. Why is that important?

NH: We want to bring joy back to eating and eliminate guilt. For example, we can predict how long after consuming food in our database you will have to walk to keep your blood sugar at the right level. Knowing what “is” is not enough. We want to tell you what to do about it. When you think of fried chicken and a shake, we can tell you, you need to walk 46 minutes later to stay healthy [blood sugar] Range. Would you like to take over the availability for it? No? Maybe then [eat the chicken and shake] At a saturday.

TC: This is subscription software that works with other wearables and costs $ 488 for three months.

NH: That’s the retail price, but we have an introductory offer of $ 288.

TC: Are you even concerned about people using the product, getting a feel for what they could do differently, and then ending their subscription?

NH: No. Pregnancy changes [one’s profile]Age changes. People don’t always travel and eat the same things. . .

MS: I’ve worn [continuous glucose monitoring] Wearables for seven years and I’m still learning things. Suddenly you realize that every time you eat white rice, for example, you poke through the roof. That goes for a lot of people. But we’re also soon offering a one-year subscription because we know people slip up sometimes [only to be reminded] later that these boosters are very valuable.

TC: How does it work in practice? Suppose I’m in a restaurant and want to have pizza, but I don’t know which one to order.

NH: You can compare curve by curve to see which is healthier. You can see how much you have to walk [depending on the toppings].

TC: Do I have to speak all of these rubbers into my smartphone?

NH: January scans barcodes, it also understands photos. It also has manual input and it takes voice [commands].

TC: Are you doing anything else with this huge food database that you have aggregated and that you enrich with your own data?

NH: We are definitely not going to sell any personal information.

TC: Not even aggregated data? Because it sounds like a useful database. . .

MS: We’re not 23andMe; That really is not the goal.

TC: You mentioned that rice can raise a person’s blood sugar, which is surprising. What might surprise some people what your software can show them?

NH: The way people react to blood sugar is so different, not just between Connie and Mike, but also between Connie and Connie. If you eat nine days in a row, your glycemic response may be different on each of those nine days depending on how much you slept or how much you thought the day before, or how much fiber was in your body and whether you went before bed have eaten.

Pre-meal activity and post-meal activity are important. Fiber is important. It is the most overlooked intervention in the American diet. Our traditional diets included 150 grams of fiber per day; The average American diet today is 15 grams of fiber. Many health problems can be traced back to a lack of fiber.

TC: It seems like coaching in conjunction with your app would be helpful. Is there a coaching component?

NH: We don’t offer a coaching component today, but we are currently in discussions with various coaching solutions in order to be the AI ​​partner for them.

TC: Who else do you work with? Health company? Employers who can offer this as an advantage?

NH: We sell directly to consumers, but we have had a pharmaceutical customer for two years. Pharmaceutical companies are very interested in working with us because we can use lifestyle as a biomarker. We essentially give it [anonymized] Insight into a person’s lifestyle for a period of two weeks, or however long they may want to do the program, so that they can gain insight into whether the therapeutic is working because of the person’s lifestyle or despite the person’s lifestyle. Pharmaceutical companies are very interested in working with us as they may get answers faster in a test phase and even reduce the number of topics required.

So we are happy about Pharma. We are also very interested in working with employers, with coaching solutions and ultimately with payers [like insurance companies].

Leave a Comment