Queen Margaret’s Research Institute
Uncovering key drivers of optimal and sub-optimal blood glucose levels in type 1 diabetes.
OpenAPS was developed by a dedicated community of individuals (named #wearenotwaiting) who sought to provide a more flexible and customisable approach to diabetes management. The data is generated by patients using insulin pumps and continuous glucose monitors (CGMs), which communicate with each other via an algorithm. Patients still need to administer insulin with meals and make adjustments with exercise; the data collected includes glucose concentrations (recorded every 5 minutes), insulin dose, activity and food/carbohydrate intake.
George’s project aims to extract and analyse these complex datasets and apply statistical and machine learning techniques to understand factors that lead to both excellent and suboptimal blood glucose control.