The project TAILOR addresses new technological challenges for automated glucose control in type 1 diabetes aiming at the improvement of glycemic control while matching the patients’ expected interaction with the system, yielding to patient-tailored solutions that maximize perceived usefulness and ease of use to foster the adoption of the technology. As ultimate goal, technological progress to widen the access of technological solutions to all patients that might benefit from them is pursued.
To achieve this goal, either in the artificial pancreas or new technological solutions for insulin pen users integrating a continuous glucose monitor (MDI+CGM), devices should be flexible enough to accommodate to different users, widening its target population. This implies that freedom should be given to the patient regarding management of meals and exercise (with/without announcement, carbs/glucagon) and use of extra wearables (always/sometimes/never) while improving glycemic control with respect to current therapy. To this end, learning tools for a better management of variability and system personalization will be key.
To achieve this goal, the following challenges will be addressed by the project consortium, in which the researchers of the group Tecnodiabetes of the Instituto-ai2-UPV are involved, together with the Hospital Sant Joan de Déu de Barcelona, the Hospital Clínic de Barcelona, the Steno Diabetes Center Conpenhaguen, the Technical University of Denmark, as well as the University of Virginia and the University of Padova.
First, improvement of glycemic control will require new simulation tools better characterizing variability in diverse cohorts. Of special interest will be the study of physiological differences between men and women with respect to the glycemic effect of exercise.
Second, new personalization tools based on advanced learning methods will be derived, expectedly improving glycemic control due to a better management of variability. Third, alleviation of patients burden in meal control will be addressed through the development of automatic meal detection systems without detriment of glycemic control, yielding to artificial pancreas systems with optional meal announcement. Fourth, alleviation of patients burden in hypoglycemia mitigation, especially under unannounced exercise, will be addressed by automatic infusion of glucagon in a dual-hormone artificial pancreas as compared to recommendation of rescue carbohydrates. Fifth, alleviation of decision making burden and improvement of glycemic control in MDI+CGM users will be addressed, translating to this context results from the artificial pancreas. Four clinical studies will be conducted for the evaluation of these technologies.
As final outcome of the project, a new system, jAP-TAILOR, will be developed, featuring a flexible interaction to accommodate to different user profiles, both for artificial pancreas and MDI+CGM, as well as providing satisfactory glucose control.