Clinical Evaluation of an Automated Artificial Pancreas Using Zone-Model Predictive Control and Health Monitoring System

Abstract

Background: This study was performed to evaluate the safety and efficacy of a fully automated artificial pancreas using zone-model predictive control (zone-MPC) with the health monitoring system (HMS) during unannounced meals and overnight and exercise periods. Subjects and Methods: A fully automated closed-loop artificial pancreas was evaluated in 12 subjects (eight women, four men) with type 1 diabetes (mean -SD age, 49.4 -10.4 years; diabetes duration, 32.7 -16.0 years; glycosylated hemoglobin, 7.3 -1.2%). The zone-MPC controller used an a priori model that was initialized using the subject's total daily insulin. The controller was designed to keep glucose levels between 80 and 140 mg/dL. A hypoglycemia prediction algorithm, a module of the HMS, was used in conjunction with the zone controller to alert the user to consume carbohydrates if the glucose level was predicted to fall below 70 mg/dL in the next 15 min. Results: The average time spent in the 70-180 mg/dL range, measured by the YSI glucose and lactate analyzer (Yellow Springs Instruments, Yellow Springs, OH), was 80% for the entire session, 92% overnight from 12 a.m. to 7 a.m., and 69% and 61% for the 5-h period after dinner and breakfast, respectively. The time spent < 60 mg/ dL for the entire session by YSI was 0%, with no safety events. The HMS sent appropriate warnings to prevent hypoglycemia via short and multimedia message services, at an average of 3.8 treatments per subject. Conclusions: The combination of the zone-MPC controller and the HMS hypoglycemia prevention algorithm was able to safely regulate glucose in a tight range with no adverse events despite the challenges of unannounced meals and moderate exercise.

Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas

“…The AP system architecture has been clinically evaluated for three potential configurations, based on the hardware platform where the controller was implemented, specifically: computer/laptop [7,[16][17][18], tablet [8,19,20] and smartphone [21]. In this study, we examine two possible AP hardware configurations; we refer to them as Configuration A and Configuration B.…”

Design and in silico evaluation of an intraperitoneal–subcutaneous (IP–SC) artificial pancreas

“…By contrast, SC continuous glucose monitoring (CGM) and CSII devices are smaller, less invasive, and already widely used in ambulatory diabetes care. Thus, CGM and CSII have been used in the development of an AP, and several clinical and in silico evaluations of the AP have been reported (Amrein et al, 2010; Atlas, Nimri, Miller, Grunberg, & Phillip, 2010; Breton et al, 2012; Cobelli et al, 2012; Dassau et al, 2010, 2013; Dua & Pistikopoulos, 2005; Harvey et al, 2014; Hovorka et al, 2011; Kovatchev et al, 2010; Murphy et al, 2011; Parker, Doyle, & Peppas, 1999; Patek et al, 2012; Steil, Rebrin, Darwin, Hariri, & Saad, 2006; Weinzimer et al, 2008; Zisser et al, 2012). However, substantial time delays associated with SC insulin delivery (i.e., the slow absorption peak at 50–60 min and long residence time of 6–8 h, Fig.…”

Artificial Pancreas (AP) Clinical Trial Participants' Acceptance of Future AP Technology

“…[2][3][4][5][6][7][8] Our first closed-loop study at SDRI was done in April 2007; several studies followed this initial closed-loop design with different controller designs but with the common theme of a fully automated closed-loop system. 9,10 Additional AP studies are being conducted in many other settings, including across the United States, the United Kingdom, The Netherlands, Israel, France, and Italy. [11][12][13][14][15] Knowing the importance of human behavior in diabetes management, investigators are now looking at future acceptance of AP technology as well as behavioral and psychological considerations.…”