This project is an interdisciplinary and inter-institutional effort of physicians, mathematicians, and engineers from the University of Virginia (UVA) and Stanford University, dedicated to development and testing of a new network-control artificial pancreas (AP) concept: optimization of glycemia in type 1 diabetes by alignment of engineering control functions with physiologic and behavioral processes in a modular design. The vehicle for implementation of this concept into the clinical practice will be the Diabetes Assistant (DiAs) - the first [worldwide] smart-phone AP system used in outpatient closed-loop control (CLC) trials. DiAs combines local patient services (e.g. hypoglycemia prevention, advice, CLC), and global services (e.g. real-time remote monitoring, telemedicine). The system development will utilize 15 years of extensive theoretical work, CLC studies, behavioral interventions, and cutting-edge engineering designs. Nevertheless, our basic philosophy is straightforward: in order to be successful, CLC needs to include a robust safety system reducing the risk for hypoglycemia and control algorithms learning from each individual's daily behavioral and basal/bolus patterns. (1) Technology development will include: (i) Structural Software design, based on our prototype Medical Android operating system (deposited in FDA Master File 2109), and adding a system hypervisor to enable seamless co-execution of critical CLC functions together with other non-critical processes (e.g. normal smart phone operation);(ii) Alignment of Advisory and CLC Algorithms with key physiological processes by incorporating modules specific to prevention of hypoglycemia, behavioral optimization of basal/bolus profiles to reflect each patient's daily patterns;and real-time fine-tuning of insulin delivery to safely intensify treatment. (2) Clinical Trials will include: (i) Study 1 demonstrating reversal of hypoglycemia unawareness with CLC, which will result from 1-month use of our hypoglycemia-preventing Unified Safety System (USS Virginia);(ii) Study 2 deploying an Advisory System comprised of local and global advisory modules, which will optimize each person's daily basal/bolus profiles by matching them to individual behavioral patterns. (iii) Study 3 bringing together Safety, Advisory, and CLC modules into a comprehensive network-control system. Specifically: the USS will safeguard against hypoglycemia - the primary barrier to optimal diabetes control - thereby allowing intensified treatment by Fully-Integrated CLC, which will adjust insulin delivery to fine-tune each person's behaviorally-optimized profile. The DiAs technology will be primarily developed by the UVA team. All clinical studies will be carried out in parallel at UVA (focusing on adult patients) and Stanford (focusing on pediatric population). Ultimately, this project will finalize and test extensively a modular portable AP system, making it ready for clinical deployment.
The success of the artificial pancreas (AP) is contingent upon the interaction between a network of physiologic and behavioral processes specific to each patient, and an individually-tailored AP system. Thus, to ensure the transition of the AP to everyday ambulatory use, network-control elements need to be implemented in a portable outpatient AP platform. This project aims to finalize the development and the clinical acceptance of the Diabetes Assistant (DiAs) - a smart-phone based AP platform combining local patient services (e.g. hypoglycemia prevention, closed-loop control) and global services (e.g. real-time remote monitoring). DiAs will be tested in clinical studies at the University of Virginia and Stanford University, which will demonstrate: Sustained prevention of hypoglycemia and restoration of hypoglycemia awareness (Study 1);Optimization of daily basal/bolus insulin delivery profiles through advisory feedback (Study 2), and Real-time fine-tuning of insulin dosing and timing relative to optimal basal/bolus profiles (Study 3). Ultimately, this project will resultin the availability of a modular portable AP system that will be ready for clinical deployment.
| Breton, Marc D; Patek, Stephen D; Lv, Dayu et al. (2018) Continuous Glucose Monitoring and Insulin Informed Advisory System with Automated Titration and Dosing of Insulin Reduces Glucose Variability in Type 1 Diabetes Mellitus. Diabetes Technol Ther 20:531-540 |
| Brown, Sue A; Breton, Marc D; Anderson, Stacey M et al. (2017) Overnight Closed-Loop Control Improves Glycemic Control in a Multicenter Study of Adults With Type 1 Diabetes. J Clin Endocrinol Metab 102:3674-3682 |
| Brown, Sue A; Kovatchev, Boris P; Breton, Marc D et al. (2015) Multinight ""bedside"" closed-loop control for patients with type 1 diabetes. Diabetes Technol Ther 17:203-9 |
| Cobelli, Claudio; Renard, Eric; Kovatchev, Boris (2014) The artificial pancreas: a digital-age treatment for diabetes. Lancet Diabetes Endocrinol 2:679-81 |
