Andrew Wade

C2I 2020 Medical & Healthcare winner: data driven insulin dosing

In-Depth

The winner of The Engineer's C2I2020 Medical and Healthcare category is an app  - jointly developed by Quin Technology and the University of Bristol - that is helping thousands of people manage diabetes more effectively. Andrew Wade reports

Category: Medical & Healthcare

Winner: Machine Learning for Enhanced Diabetes Care

Partners: Quin Technology Ltd with University of Bristol

A typical person with type 1 diabetes will have around 65,000 insulin injections throughout their lifetime. But despite the fact that technology is improving treatment all the time, decisions about the timing and quantity of these injections is still little more than guesswork in many cases. Quin, a new app underpinned by the winning project in our Medical & Healthcare category, is striving to change that.

The app allows users to input both insulin dosage and food consumption, as well as providing reminders for when regular insulin injections are due. Additional sensor data from smartphones such as activity, sleep and menstrual cycle can also be linked, alongside readings from CGMs (Continuous Glucose Monitors). Over time, the platform’s algorithms learn from individual inputs and outcomes and help users adjust their insulin dosage based on what has worked for them in the past.

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