Fully Integrated Artificial Pancreas in Type 1 Diabetes

Author:

Breton Marc1,Farret Anne2,Bruttomesso Daniela3,Anderson Stacey1,Magni Lalo4,Patek Stephen1,Dalla Man Chiara5,Place Jerome2,Demartini Susan1,Del Favero Simone5,Toffanin Chiara4,Hughes-Karvetski Colleen1,Dassau Eyal67,Zisser Howard67,Doyle Francis J.6,De Nicolao Giuseppe4,Avogaro Angelo3,Cobelli Claudio5,Renard Eric2,Kovatchev Boris1,

Affiliation:

1. University of Virginia, Center for Diabetes Technology, Charlottesville, Virginia

2. University Hospital of Montpellier, Department of Endocrinology, Diabetes, and Nutrition, INSERM Clinical Investigation Center 1001, Institute of Functional Genomics, CNRS UMR5203, INSERM U661, University of Montpellier, Montpellier, France

3. Department of Internal Medicine, Unit of Metabolic Disease, University of Padova, Padova, Italy

4. Department of Computer Engineering and System Sciences, University of Pavia, Pavia, Italy

5. Department of Information Engineering, University of Padova, Padova, Italy

6. University of California Santa Barbara, Santa Barbara, California

7. Sansum Diabetes Research Institute, Santa Barbara, California

Abstract

Integrated closed-loop control (CLC), combining continuous glucose monitoring (CGM) with insulin pump (continuous subcutaneous insulin infusion [CSII]), known as artificial pancreas, can help optimize glycemic control in diabetes. We present a fundamental modular concept for CLC design, illustrated by clinical studies involving 11 adolescents and 27 adults at the Universities of Virginia, Padova, and Montpellier. We tested two modular CLC constructs: standard control to range (sCTR), designed to augment pump plus CGM by preventing extreme glucose excursions; and enhanced control to range (eCTR), designed to truly optimize control within near normoglycemia of 3.9–10 mmol/L. The CLC system was fully integrated using automated data transfer CGM→algorithm→CSII. All studies used randomized crossover design comparing CSII versus CLC during identical 22-h hospitalizations including meals, overnight rest, and 30-min exercise. sCTR increased significantly the time in near normoglycemia from 61 to 74%, simultaneously reducing hypoglycemia 2.7-fold. eCTR improved mean blood glucose from 7.73 to 6.68 mmol/L without increasing hypoglycemia, achieved 97% in near normoglycemia and 77% in tight glycemic control, and reduced variability overnight. In conclusion, sCTR and eCTR represent sequential steps toward automated CLC, preventing extremes (sCTR) and further optimizing control (eCTR). This approach inspires compelling new concepts: modular assembly, sequential deployment, testing, and clinical acceptance of custom-built CLC systems tailored to individual patient needs.

Publisher

American Diabetes Association

Subject

Endocrinology, Diabetes and Metabolism,Internal Medicine

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