Over the past decade, there’s been a rise in the adoption of technology through phones and wearables. We’re now able to collect our data to help track steps; tune in when we need a reminder to breathe or get better sleep. Bearing this in mind, at Quin we realised we could use the data we so unintentionally collect to help answer a question people with diabetes ask themselves everyday, several times a day: how much insulin should I take and when.
More diabetes data than ever
We’ve got access to more diabetes-related data now more than ever before; no one is able to dissect this data in such a way to answer this very question that has lingered around since the 1921 when Banting and Best was credited with discovering insulin. That’s not even the earliest timestamp we have. It is said that the ancient Egyptians first mentioned a condition that appeared to have been type 1 diabetes over 3000 years ago but don’t quote us on that.
Quin does not only build on the ecosystem we’re in. We also disrupt it. We do so by thinking of the person we want to create this for: you can’t take them out of the picture because each person is different. How do we disrupt? We pick up on the infrastructure that’s in place. We then take into account the person in their natural environment and learn from their daily life experience instead of artificial clinical settings. These would not take into account various factors and practicality of actions that simply come with living a real life.
Believe it or not, this very context of real-life scenario and practical actions is not taken into account in many modern-day science projects but that’s how we humanise diabetes technology at Quin.
Why is now the best time to try solving diabetes with technology and data? Tech, data, the ecosystem, diabetes community are all now so advanced that it feels right to harness them and finally help people decide how much and when to take insulin.