Mealtime correction insulin advisor for CGM-informed insulin pen therapy

With improvements in the accuracy and reliability of continuous glucose monitoring (CGM), the stage is set for new algorithmic approaches to the treatment of Type 1 diabetes. While recent efforts to build a closed-loop artificial pancreas device are encouraging, the artificial pancreas will not apply to patients who prefer to inject insulin manually or who simply will not submit to fully automatic closed-loop control. Therefore, it is of interest to see whether non-pump users can benefit from algorithmic insulin advisory systems. In this paper we present a mealtime correction bolus advisor for patients on “multiple daily injection” (MDI) therapy, taking advantage of the ability to estimate the patient´s metabolic state in real time using both CGM and manual reports of insulin delivery. The state estimation process for this is informed by knowledge of the patient´s daily injection of long-acting insulin through the novel concept of a virtual basal rate profile. Preliminary in silico trials indicate that the advisor can result in significantly improved control (reduction of up to 1% saturation of hemoglobin A1C) for patients currently struggling with sustained hyperglycemia.