Fully Integrated Artificial Pancreas in Type 1 Diabetes
Modular Closed-Loop Glucose Control Maintains Near Normoglycemia
- Marc Breton1⇓,
- Anne Farret2,
- Daniela Bruttomesso3,
- Stacey Anderson1,
- Lalo Magni4,
- Stephen Patek1,
- Chiara Dalla Man5,
- Jerome Place2,
- Susan Demartini1,
- Simone Del Favero5,
- Chiara Toffanin4,
- Colleen Hughes-Karvetski1,
- Eyal Dassau6,7,
- Howard Zisser6,7,
- Francis J. Doyle III6,
- Giuseppe De Nicolao4,
- Angelo Avogaro3,
- Claudio Cobelli5,
- Eric Renard2,
- Boris Kovatchev1 and
- on behalf of The International Artificial Pancreas (iAP) Study Group
- 1University of Virginia, Center for Diabetes Technology, Charlottesville, Virginia
- 2University 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
- 3Department of Internal Medicine, Unit of Metabolic Disease, University of Padova, Padova, Italy
- 4Department of Computer Engineering and System Sciences, University of Pavia, Pavia, Italy
- 5Department of Information Engineering, University of Padova, Padova, Italy
- 6University of California Santa Barbara, Santa Barbara, California
- 7Sansum Diabetes Research Institute, Santa Barbara, California
- Corresponding author: Marc Breton, .
M.B., A.F., and D.B. contributed equally to this study.
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.
This article contains Supplementary Data online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db11-1445/-/DC1.
See accompanying commentary, p. 2221.
- Received October 17, 2011.
- Accepted March 15, 2012.
- © 2012 by the American Diabetes Association.
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