For millions of people living with diabetes around the world, insulin is a daily lifeline. But it’s believed that a staggering 92% of them do not achieve recommended medical targets and are more likely to experience medical conditions such as fatigue, anxiety, stress and depression.
The challenge with traditional insulin therapies, according to digital health entrepreneur Cyndi Williams, is that they’re heavily reliant on individual judgement. She explains: “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.”
Looking to transform the lives of millions of people globally, Cyndi teamed up with Isabella Degen to launch diabetes management app Quin. Powered by algorithmic insights and machine learning, it helps users decide when and how much insulin they should take on a daily basis.
“The app aggregates data from people with diabetes and their devices, sensors and phones to take the guesswork out of insulin dosage,” explains Williams. “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 personalised approach to insulin-treated diabetes.”
When it comes to current diabetes treatments, she believes that progress is slow and that the condition is poorly understood. “At diagnosis, people are given general medical formulas to calculate how much insulin to take for what they eat,” explains Williams.
“These simple formulas don’t accurately reflect the complex and unique functions of their body, so people use trial and error to create a constantly changing treatment regime that suits the ways that they eat, move, work, sleep, and go about daily life.”
However, by taking a human-first approach, Williams says things can change significantly. “Quin observes each individual as they go about life, making hundreds of diabetes decisions a day, and uses what it learns to create a personalised insulin-dosing guidance. The underlying principle is that your past insulin-dosing decisions – not medical formulas – are the most reliable basis for your future insulin-dosing decisions.”
Unlike existing solutions, Quin analyzes data from diabetes devices, wearables and phones to ensure insulin treatments are effective; uses machine learning to better understand the complex influences on fluctuations in blood glucose; structures data to reveal insights into the physiological factors affecting glucose levels; and expands diabetes knowledge.
Although Quin is still in the early stages of development, it’s already impacting the lives of many people living with diabetes. In a study conducted by the firm, 76% of users said they feel more confident and find life with diabetes easier. Meanwhile, 35% have improved their HbA1c healthcare’s target measure.
Sandra, a user who was diagnosed 50 years ago, says: “There is no one rule for everybody, so Quin is a great supportive tool to help with that, because you’re seeing every day how your decisions affect your blood sugars and you’ve got that as a record. It’s really positive and will help everyone with diabetes, now and in the future.”
Over the coming year, the firm hopes to rollout the app on a global scale. Williams adds: “We have been co-creating the Quin app with more than 100 users over the past 2 years. We are excited to be launching an equity crowdfunding campaign this month, and we are opening the business to investors across Europe, starting with as little as £10.
“We will launch Quin in the UK and Europe in late 2020, and start the process with the US FDA around that time. We’re currently working to establish partnerships with the major diabetes device and insulin manufacturers and we plan to run a clinical trial in early 2021.”
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