Closed-Loop Control Modalities in Type 1 Diabetes: Efficacy and System Acceptance In 2009 we initiated one of the first NIH studies dedicated to engineering and clinical testing of closed-loop control (CLC) of type 1 diabetes. Since then, we have achieved key milestones and derived conclusions which enabled further research in this rapidly growing field. Notably, we proposed the idea that the artificial pancreas is not a single all-in-one device but a network encompassing the patient in a digital treatment ecosystem that can offer and alter different treatment modalities in real time depending on the patient's clinical state. This new notion was reflected in: (1) Our modular engineering design of CLC algorithms, which now allows various treatment modalities to be initiated and swapped without interruption; (2) The Diabetes Assistant (DiAs) - the first portable CLC hub using a smart phone to run control algorithms and specifically designed to be operated by the patient, which is now used in a number of outpatient studies in the U.S. and in Europe, and (3) The Unified Safety System (USS Virginia) - the first CLC algorithm engineered to adapt its mode of operation during the course of every night, first mitigating after-dinner hyperglycemia and then sliding the patient to a target morning glucose of 120mg/dl, thereby resetting his/her metabolic state for a new day. Using these technologies, we now propose to compare in a randomized cross-over trial the long-term efficacy of three treatment modalities - sensor-augmented pump (SAP) vs. USS+SAP during the day(d) vs. USS+CLC(d). We plan to randomize 84 patients with type 1 diabetes into two different treatment sequences: SAP?USS+SAP(d)?USS+CLC(d)?USS+SAP(d) and USS+SAP(d)?USS+CLC(d)?USS+SAP(d)?SAP. Each treatment modality will continue for 2 months - sufficient time to address the following specific aims: SA1: Overnight CLC achieved by USS+SAP(d) will be superior to SAP alone in terms of: (1) Improved HbA1c without increasing the risk for hypoglycemia; (2) Reduced incidence and risk for hypoglycemia overnight, and (3) Reduced fear of hypoglycemia and improved diabetes quality of life scores. SA2: CLC during the day achieved by USS+CLC(d) will preserve the benefits of USS+SAP(d) and will be superior to USS+SAP(d) in terms of: (1) Increased time within target range of 70-180mg/dl during the day; (2) Reduced risk for hypoglycemia during and after exercise, and (3) Reduced postprandial glucose variability. SA3: CLC system acceptance evaluated by focus-group interviews and technology acceptance scores will be: (1) Superior, for USS+SAP(d) compared to SAP alone, i.e. adding USS overnight will increase patients' acceptance of CLC, and (2) Marginally inferior, for USS+CLC(d) compared to USS+SAP(d); i.e. some patients would prefer SAP alone during the day due to perceived increased system complexity. Overall, we expect to establish that a distinct overnight CLC modality (USS Virginia) combined with SAP therapy during the day is a viable precursor to future adaptable therapeutic schemes, achieving glycemic control that is superior to SAP alone and optimal balance between system complexity and perceived benefits.
Closed-Loop Control Modalities in Type 1 Diabetes: Efficacy and System Acceptance The future of the artificial pancreas (AP) as optimal treatment for type 1 diabetes is within reach. To fulfil their promise to all, AP systems need to prove their efficacy i rigorous clinical trials with outcomes targeting key parameters of glucose control-hemoglobin A1c and risk for hypoglycemia. We therefore propose to deploy the novel technologies we have developed in the past several years, in a long-term study aiming to establish that optimal balance between AP system complexity and benefits to the patient is achieved by a system that automatically takes over a person's blood glucose control in the evening and then stabilizes and 'resets' blood glucose levels to normal by the morning. Such an approach follows the natural wake-sleep circadian cycle, takes advantage of overnight steady-state glucose levels, and is proven with our current technology.
| 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 |
| Campos-Náñez, Enrique; Kovatchev, Boris P (2016) Impact of Meal Constituents on Artificial Pancreas Algorithms. Diabetes Technol Ther 18:607-609 |
| Kovatchev, Boris P; Patek, Stephen D; Ortiz, Edward Andrew et al. (2015) Assessing sensor accuracy for non-adjunct use of continuous glucose monitoring. Diabetes Technol Ther 17:177-86 |
| Kovatchev, Boris P (2015) Hypoglycemia Reduction and Accuracy of Continuous Glucose Monitoring. Diabetes Technol Ther 17:530-3 |
| 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 |
| Gonder-Frederick, Linda (2014) Lifestyle modifications in the management of type 1 diabetes: still relevant after all these years? Diabetes Technol Ther 16:695-8 |
| Kovatchev, Boris P; Renard, Eric; Cobelli, Claudio et al. (2014) Safety of outpatient closed-loop control: first randomized crossover trials of a wearable artificial pancreas. Diabetes Care 37:1789-96 |
| Cobelli, Claudio; Renard, Eric; Kovatchev, Boris (2014) The artificial pancreas: a digital-age treatment for diabetes. Lancet Diabetes Endocrinol 2:679-81 |
| Kovatchev, Boris P; Wakeman, Christian A; Breton, Marc D et al. (2014) Computing the surveillance error grid analysis: procedure and examples. J Diabetes Sci Technol 8:673-84 |
| Renard, Eric; Cobelli, Claudio; Kovatchev, Boris P (2013) Closed loop developments to improve glucose control at home. Diabetes Res Clin Pract 102:79-85 |
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