Closed-loop Artificial Pancreas: Algorithm Engineering and Clinical Evaluation ABSTRACT This proposal seeks to build on a promising line of research that has already resulted in a working prototype of a closed-loop artificial pancreas (AP) that combines continuous glucose sensing with automated insulin delivery via a control algorithm. The AP consists of three components: a continuous glucose sensor, a continuous subcutaneous insulin infusion pump, and artificial pancreas software (APS). The APS is in the final stages of review by the Food and Drug Administration for use in fully automated closed-loop control clinical trials (Master File MAF-1625 ).
The specific aims are: 1) Development of the Artificial Pancreas to optimize insulin delivery and minimize meal-related excursions in glucose, 2) Expansion of the Artificial Pancreas to include alterations and individual differences in insulin sensitivity, and 3) Further development of the algorithms using multi-parametric model predictive control (mpMPC) in order to reduce online computation, develop effective online monitoring strategies to ensure that the AP is operating properly, and accommodate multiple input systems. In the quest to achieve our overall goal of a completely automated closed-loop device for insulin delivery, we will utilize a staged approach in which the clinical studies also have a concurrent engineering design approach in order to refine our AP. In silico testing and human in-clinic testing will be used to validate each step of model development. The ultimate goal of this line of research is a functional AP that will provide around-the-clock glucose regulation through controlled insulin delivery in response to detected patterns of changes in glucose levels in order to achieve optimal glucose regulation in subjects with type 1 diabetes. Special consideration will be given to the amount of potentially available insulin from prior infusions (insulin-on-board) in setting constraints for subsequent insulin delivery. The proposal describes multi-parametric model predictive control approaches to glycemic regulation and extensive in silico and clinical validation of the AP under overnight, meal, and exercise conditions. This application grows out of a long-standing collaboration between systems engineers at the University of California, Santa Barbara (UCSB) and research physicians specializing in diabetes research at the prestigious Sansum Diabetes Research Institute (Sansum) located less than ten miles away. This team has distinguished itself as a major contributor to the artificial pancreas literature and as an international leader in diabetes technology.

Public Health Relevance

This project aims to develop a functional artificial pancreas that will provide around-the-clock glucose regulation through controlled insulin delivery in response to detected patterns of changes in glucose levels in order to achieve optimal glucose regulation in subjects with type 1 diabetes. Special consideration will be given to the amount of potentially available insulin from prior infusions (insulin-on-board) in setting constraints for subsequent insulin delivery. The proposal describes multi-parametric model predictive control approaches to glycemic regulation and extensive in silico and clinical validation of the AP under overnight, meal, and exercise conditions.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
5R01DK085628-04
Application #
8326148
Study Section
Special Emphasis Panel (ZDK1-GRB-2 (O2))
Program Officer
Arreaza-Rubin, Guillermo
Project Start
2009-09-30
Project End
2014-08-31
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
4
Fiscal Year
2012
Total Cost
$711,905
Indirect Cost
$124,005
Name
University of California Santa Barbara
Department
None
Type
Organized Research Units
DUNS #
094878394
City
Santa Barbara
State
CA
Country
United States
Zip Code
93106
Harvey, Rebecca A; Dassau, Eyal; Bevier, Wendy C et al. (2014) Clinical evaluation of an automated artificial pancreas using zone-model predictive control and health monitoring system. Diabetes Technol Ther 16:348-57
Lee, Justin J; Dassau, Eyal; Zisser, Howard et al. (2014) Design and in silico evaluation of an intraperitoneal-subcutaneous (IP-SC) artificial pancreas. Comput Chem Eng 70:180-188
Doyle 3rd, Francis J; Huyett, Lauren M; Lee, Joon Bok et al. (2014) Closed-loop artificial pancreas systems: engineering the algorithms. Diabetes Care 37:1191-7
Toffanin, Chiara; Zisser, Howard; Doyle 3rd, Francis J et al. (2013) Dynamic insulin on board: incorporation of circadian insulin sensitivity variation. J Diabetes Sci Technol 7:928-40
Dassau, Eyal; Zisser, Howard; Harvey, Rebecca A et al. (2013) Clinical evaluation of a personalized artificial pancreas. Diabetes Care 36:801-9
Patek, S D; Magni, L; Dassau, E et al. (2012) Modular closed-loop control of diabetes. IEEE Trans Biomed Eng 59:2986-99
Zisser, Howard (2011) Clinical hurdles and possible solutions in the implementation of closed-loop control in type 1 diabetes mellitus. J Diabetes Sci Technol 5:1283-6
Percival, M W; Wang, Y; Grosman, B et al. (2011) Development of a multi-parametric model predictive control algorithm for insulin delivery in type 1 diabetes mellitus using clinical parameters. J Process Control 21:391-404
Grosman, Benyamin; Dassau, Eyal; Zisser, Howard C et al. (2010) Zone model predictive control: a strategy to minimize hyper- and hypoglycemic events. J Diabetes Sci Technol 4:961-75
Percival, Matthew W; Bevier, Wendy C; Wang, Youqing et al. (2010) Modeling the effects of subcutaneous insulin administration and carbohydrate consumption on blood glucose. J Diabetes Sci Technol 4:1214-28