Patients at a diabetes camp who were treated with an artificial-pancreas system had less nocturnal hypoglycemia and tighter glucose control than when they were treated with a sensor-augmented insulin pump. (Funded by Sanofi and others; ClinicalTrials.gov number, NCT01238406.).

OBJECTIVECurrent state-of-the-art artificial pancreas systems are either based on traditional linear control theory or rely on mathematical models of glucose-insulin dynamics. Blood glucose control using these methods is limited due to the complexity of the biological system. The aim of this study was to describe the principles and clinical performance of the novel MD-Logic Artificial Pancreas (MDLAP) System.RESEARCH DESIGN AND METHODSThe MDLAP applies fuzzy logic theory to imitate lines of reasoning of diabetes caregivers. It uses a combination of control-to-range and control-to-target strategies to automatically regulate individual glucose levels. Feasibility clinical studies were conducted in seven adults with type 1 diabetes (aged 19–30 years, mean diabetes duration 10 ± 4 years, mean A1C 6.6 ± 0.7%). All underwent 14 full, closed-loop control sessions of 8 h (fasting and meal challenge conditions) and 24 h.RESULTSThe mean peak postprandial (overall sessions) glucose level was 224 ± 22 mg/dl. Postprandial glucose levels returned to <180 mg/dl within 2.6 ± 0.6 h and remained stable in the normal range for at least 1 h. During 24-h closed-loop control, 73% of the sensor values ranged between 70 and 180 mg/dl, 27% were >180 mg/dl, and none were <70 mg/dl. There were no events of symptomatic hypoglycemia during any of the trials.CONCLUSIONSThe MDLAP system is a promising tool for individualized glucose control in patients with type 1 diabetes. It is designed to minimize high glucose peaks while preventing hypoglycemia. Further studies are planned in the broad population under daily-life conditions.

OBJECTIVEWe evaluated the effect of the MD-Logic system on overnight glycemic control at patients' homes. RESEARCH DESIGN AND METHODSTwenty-four patients (aged 12-43 years; average A 1c 7.5 6 0.8%, 58.1 6 8.4 mmol/mol) were randomly assigned to participate in two overnight crossover periods, each including 6 weeks of consecutive nights: one under closed loop and the second under sensor-augmented pump (SAP) therapy at patients' homes in real-life conditions. The primary end point was time spent with sensor glucose levels below 70 mg/dL (3.9 mmol/L) overnight. RESULTSClosed-loop nights significantly reduced time spent in hypoglycemia (P = 0.02) and increased the percentage of time spent in the target range of 70-140 mg/dL (P = 0.003) compared with nights when the SAP therapy was used. The time spent in substantial hyperglycemia above 240 mg/dL was reduced by a median of 52.2% (interquartile range [IQR] 4.8, 72.9%; P = 0.001) under closed-loop control compared with SAP therapy. Overnight total insulin doses were lower in the closedloop nights compared with the SAP nights (P = 0.04). The average daytime glucose levels after closed-loop operation were reduced by a median of 10.0 mg/dL (IQR 22.7, 19.2; P = 0.017) while lower total insulin doses were used (P = 0.038). No severe adverse events occurred during closed-loop control; there was a single event of severe hypoglycemia during a control night. CONCLUSIONSThe long-term home use of automated overnight insulin delivery by the MD-Logic system was found to be a feasible, safe, and an effective tool to reduce nocturnal hypoglycemia and improve overnight glycemic control in subjects with type 1 diabetes.The use of a closed-loop system is gaining recognition as a tool for real-time feedback control of insulin delivery for type 1 diabetes (1). A closed-loop insulin delivery system for type 1 diabetes has been tested in hospital settings for overnight (2-4) and also for day and night glycemic control (5,6). Moreover, it has been used for different populations of patients with diabetes: newly diagnosed patients (7), pregnant women (8), those with type 2 diabetes (9), and critically ill patients (10). The

OBJECTIVEAn artificial pancreas (AP) that automatically regulates blood glucose would greatly improve the lives of individuals with diabetes. Such a device would prevent hypo- and hyperglycemia along with associated long- and short-term complications as well as ease some of the day-to-day burden of frequent blood glucose measurements and insulin administration.RESEARCH DESIGN AND METHODSWe conducted a pilot clinical trial evaluating an individualized, fully automated AP using commercial devices. Two trials (n = 22, nsubjects = 17) were conducted using a multiparametric formulation of model predictive control and an insulin-on-board algorithm such that the control algorithm, or “brain,” can be embedded on a chip as part of a future mobile device. The protocol evaluated the control algorithm for three main challenges: 1) normalizing glycemia from various initial glucose levels, 2) maintaining euglycemia, and 3) overcoming an unannounced meal of 30 ± 5 g carbohydrates.RESULTSInitial glucose values ranged from 84–251 mg/dL. Blood glucose was kept in the near-normal range (80–180 mg/dL) for an average of 70% of the trial time. The low and high blood glucose indices were 0.34 and 5.1, respectively.CONCLUSIONSThese encouraging short-term results reveal the ability of a control algorithm tailored to an individual’s glucose characteristics to successfully regulate glycemia, even when faced with unannounced meals or initial hyperglycemia. To our knowledge, this represents the first truly fully automated multiparametric model predictive control algorithm with insulin-on-board that does not rely on user intervention to regulate blood glucose in individuals with type 1 diabetes.

Original ArticleNight glucose control with MD-Logic artificial pancreas in home setting: a single blind, randomized crossover trial -interim analysis