New AI-driven App Could Transform how People with Diabetes Improve Insulin Intake

New AI-driven App Could Transform how People with Diabetes Improve Insulin Intake

Diabetes management app, Quin, powered by algorithmic insights and machine learning, helps users decide when and how much insulin they should take daily. Why? Well, it turns out that for millions of diabetics—for whom insulin is a lifeline—the ability to consistently recommend medical targets is exceedingly difficult. They are consequently more likely to experience medical conditions such as fatigue, anxiety, and stress. Traditional insulin therapies rely on too much personal judgment—it is just too much for the average person. Can Quin change this?

According to digital health, entrepreneur Cyndi Williams recently covered in Forbes, “The science of diabetes is incomplete, and no one knows exactly how much insulin to take and when. People are left to fill the gaps through trial and error and diabetes technology to try to find a solution that works for them. This is a massive cognitive and psychological load.”

Enter Quin Technology

Quin takes away the pressure and, in the process, will transform the lives of millions of people worldwide suggests Ms. Williams and partner Isabella Degan. Williams explains, “The app aggregates data from people with diabetes and their devices, sensors, and phones to take the guesswork out of insulin dosage.” She continued, “We are structuring the data our users generate to create previously unseen insights into the root causes behind fluctuations in blood glucose and ultimately enable a more personalized approach to insulin-treated diabetes.”

Pre-Clinical Trial Research

Back in Spring 2019, it was reported that the app was still in beta version and that it was being built in collaboration with users as part of a research testing program—involving participants who are on MDI (multiple day injections) therapy using Dexcom’s continuous glucose monitoring (CGM) and have access to an Apple iPhone—they use the app on a daily-based for an 18 month trial period.

The research is funded in part by Innovate UK. It was reported that this research was some of the first to use machine learning algorithms to detect situations to allow for treatment advice in the future. The sponsors will test the app in clinical trials in the future.

A Human First Approach

The Quin team has taken a “human-first approach,” meaning the system learns from the user as they “go about life, making hundreds of diabetes decisions a day, and uses what it learns to create personalized insulin-dosing guidance.” The founders believe that the individual’s past-insulin dosing decisions, and not medical formulas, will drive the most reliable basis for an individual’s future insulin-dosing decisions. Hence Quin will aggregate and analyze data from diabetes devices, wearables, and phones to ensure insulin treatments are effective.


Quin will be launched in the UK and Europe in late 2020 and commence the FDA application process in America around the same time. The founders are presently pitching partnerships with major diabetes devices and insulin makers. A clinical trial is planned in early 2021.

Call to Action: Interested in learning more? Check out their website.


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