Miniaturized Neural Networks for Deploying Fully Closed Loop Insulin Delivery Systems: A Pilot Study Featuring Flexible Meal Announcement Options.

Journal: Journal of diabetes science and technology
Published Date: Aug 9, 2025

Abstract

BACKGROUND: Automated insulin delivery (AID) has revolutionized glucose management. Next-generation AID systems focus on reducing user input, particularly for mealtime dosing, aiming for fully closed loop (FCL) control. Our goal was to assess the safety and feasibility of the next iteration of FCL control, using a miniature neural network to enable implementation within existing hardware capabilities.

Authors

  • Elliott C Pryor
    Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA.
  • Marcela Moscoso-Vasquez
    Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA.
  • David Fulkerson
    Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA.
  • Viola Holmes
    Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA.
  • Sara Davis Prince
    Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA.
  • Chaitanya L K Koravi
    Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA.
  • Anas El Fathi
  • Sue A Brown
    Center for Diabetes Technology, University of Virginia School of Medicine, Charlottesville, Virginia, USA.
  • Mark D DeBoer
    University of Virginia, Charlottesville, VA, USA.
  • Marc D Breton
    Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA.

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