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JDRF is launching an initiative to identify appropriate additional signals for next generation Artificial Pancreas systems. AP systems are a combined Continuous Glucose Monitor (CGM), algorithm and insulin delivery system which automates insulin delivery for the therapeutic treatment of Type 1 diabetes. Current AP systems employ continuous glucose monitoring as the reference input, but this proposal seeks to identify which additional signals could add value by reducing user burden and increasing automation of AP systems.
In 2006, JDRF launched its Artificial Pancreas Project to accelerate the development of commercially available closed-loop systems.
Since then, significant progress has been made in developing and testing algorithmic approaches to automate insulin delivery, and clinical studies have progressed to the outpatient pilot setting. The NIH are currently funding large efficacy studies in this area and at least one manufacturer has announced their intent to launch a first generation AP system in 2017.
One of the issues with first generation AP systems is that the kinetics of insulin delivered subcutaneously does not match the speed of endogenous insulin activity. Therefore, users are still required to interact with these AP systems to announce food intake to facilitate optimal control. In the same way, exercise must be managed by the user, since it could lead to hypoglycemic events or even temporarily increase glucose levels, as is the case with certain types of exercise. Finally, stress also has significant impact on blood sugar levels, which must also be managed by the user.
Hence, JDRF would like next generation AP systems to be more automated, so identifying additional signals which allow automatic compensation of these issues by the AP system, such as physiological biomarkers and/or habitual and geospatial approaches, is the purpose of this call.