Artificial pancreas performs well in clinical trial

Artificial Pancreas performs well in clinical trial
Schematic showing components of the closed-loop system. The insulin pump and Dexcom G4 Share AP CGM receiver with 505 algorithm were connected wirelessly via bluetooth to the Diabetes Assistant (DiAs) smartphone device. The Zone Model Predictive Control Artificial Pancreas algorithm ran on the DiAs. Credit: Doyle Group, Harvard SEAS

During more than 60,000 hours of combined use of a novel artificial pancreas system, participants in a 12-week, multi-site clinical trial showed significant improvements in two key measures of well-being in people living with type 1 diabetes.

During the trial, 30 patients with type 1 diabetes in California, Virginia and Minnesota went about their normal daily routines while the artificial pancreas system continuously monitored their glucose levels and automatically adapted insulin delivery settings.

The results, published today in the journal Diabetes Care, revealed positive effects on two important indicators: decreased hemoglobin A1c (HbA1c) and reduced time spent in hypoglycemia.

The outpatient trial was led by Frank Doyle and Eyal Dassau from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), and included collaborators at the William Sansum Diabetes Center in Santa Barbara, California; Mayo Clinic in Rochester, Minnesota; the University of Virginia's Center for Diabetes Technology; and the University of Padova.

People with type 1 diabetes must vigilantly monitor and, when necessary, administer doses of insulin either via needle injections or infusion pump. The artificial pancreas is designed to mimic a healthy person's glucose regulating function. The closed-loop system consists of an insulin pump and continuous glucose monitor placed under the user's skin. An advanced control algorithm embedded in a blue tooth-connected smart phone signals how much insulin the pump should deliver to the patient based on a range of variables including meals consumed, physical activity, sleep, stress, and metabolism.

The adaptive control algorithm system used in the trial is based on model-predictive control (MPC), a strategy originally developed by Doyle and colleagues in a seminal paper published in 1996 and, in a 2010 paper, extended to a zone-based version of the MPC algorithm. Rather than regulating glucose levels to a specific point in the same way that a home thermostat keeps the room temperature at a precise setting, zone-MPC defines an acceptable zone for an individual's and controls variables to stay within that range. In addition to the core zone MPC algorithm, the collaborative team introduced adaptive components that allowed the algorithm to "learn" from the repeated daily cycles, leading to improvements in basal control as well as meal compensation.

"This is by far the longest duration trial we have conducted, and it is a testament to the robustness of the algorithm that our key performance indices were maintained from our earlier, shorter ," said Doyle, John A. Paulson Dean and John A. & Elizabeth S. Armstrong Professor of Engineering & Applied Sciences at SEAS. "Moreover, we took a disciplined group that had very good overall HbA1c levels before the trial, and we brought the group level even lower."

The trial builds on a foundation of earlier studies by Doyle and Dassau, a SEAS Senior Research Fellow, including a clinical trial earlier this year that tested the application of the on children and adolescents with type 1 during extended use of infusion set and sensor.

More information: Eyal Dassau et al. 12-Week 24/7 Ambulatory Artificial Pancreas With Weekly Adaptation of Insulin Delivery Settings: Effect on Hemoglobin A 1c and Hypoglycemia, Diabetes Care (2017). DOI: 10.2337/dc17-1188

Journal information: Diabetes Care
Provided by Harvard University
Citation: Artificial pancreas performs well in clinical trial (2017, October 16) retrieved 28 March 2024 from https://medicalxpress.com/news/2017-10-artificial-pancreas-clinical-trial.html
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