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. 2014 Jan;8(1):26-34.
doi: 10.1177/1932296813514502. Epub 2014 Jan 1.

The UVA/PADOVA Type 1 Diabetes Simulator: New Features

Chiara Dalla Man  1 , Francesco Micheletto  1 , Dayu Lv  2 , Marc Breton  2 , Boris Kovatchev  2 , Claudio Cobelli  3
Affiliations

The UVA/PADOVA Type 1 Diabetes Simulator: New Features

Chiara Dalla Man et al. J Diabetes Sci Technol. 2014 Jan.

Abstract

Recent studies have provided new insights into nonlinearities of insulin action in the hypoglycemic range and into glucagon kinetics as it relates to response to hypoglycemia. Based on these data, we developed a new version of the UVA/PADOVA Type 1 Diabetes Simulator, which was submitted to FDA in 2013 (S2013). The model of glucose kinetics in hypoglycemia has been improved, implementing the notion that insulin-dependent utilization increases nonlinearly when glucose decreases below a certain threshold. In addition, glucagon kinetics and secretion and action models have been incorporated into the simulator: glucagon kinetics is a single compartment; glucagon secretion is controlled by plasma insulin, plasma glucose below a certain threshold, and glucose rate of change; and plasma glucagon stimulates with some delay endogenous glucose production. A refined statistical strategy for virtual patient generation has been adopted as well. Finally, new rules for determining insulin to carbs ratio (CR) and correction factor (CF) of the virtual patients have been implemented to better comply with clinical definitions. S2013 shows a better performance in describing hypoglycemic events. In addition, the new virtual subjects span well the real type 1 diabetes mellitus population as demonstrated by good agreement between real and simulated distribution of patient-specific parameters, such as CR and CF. S2013 provides a more reliable framework for in silico trials, for testing glucose sensors and insulin augmented pump prediction methods, and for closed-loop single/dual hormone controller design, testing, and validation.

Keywords: computer simulation; diabetes control; modeling.

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Conflict of interest statement

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Scheme of the model included in the FDA-accepted T1DM simulator. White blocks are the unit processes of S2008 (gastro-intestinal tract, glucose kinetics and insulin kinetics); gray blocks are those that have been updated in the S2013 to account for counterregulation (liver, muscle, and adipose tissue); black blocks are new (alpha cell, glucagon kinetics, and delivery).
Figure 2.
Figure 2.
Average model prediction against glucose data in 32 T1DM subjects (unpublished). The gray area represents the counterregulation needed to return in normal glycemia (vertical bars are standard deviations).
Figure 3.
Figure 3.
The user interface window of S2013.
Figure 4.
Figure 4.
Simulated distribution of insulin to carbs ratio (CR, left) and correction factor (CF, right panels), in adult (upper), adolescent (middle), and children (lower panels) populations.
Figure 5.
Figure 5.
Simulated plasma glucose (upper), insulin (middle), and glucagon (lower panels) in the 100 in silico adults (left), adolescents (middle), and children (right panels).
See this image and copyright information in PMC

References

    1. Cobelli C, Dalla Man C, Sparacino G, Magni L, De Nicolao G, Kovatchev BP. Diabetes: models, signals, and control. IEEE Rev Biomed Eng. 2009;2:54-96. - PMC - PubMed
    1. Cobelli C, Renard E, Kovatchev B. Artificial pancreas: past, present, future. Diabetes. 2011;60:2672-2682. - PMC - PubMed
    1. Hovorka R, Chassin LJ, Wilinska ME, et al. Closing the loop: the adicol experience. Diab Technol Therap. 2004;3:307-318. - PubMed
    1. Kovatchev BP, Breton M, Dalla Man C, Cobelli C. In silico preclinical trials: a proof of concept in closed-loop control of type 1 diabetes. J Diabetes Sci Technol. 2009;3(1):44-55. - PMC - PubMed
    1. Visentin R, Dalla Man C, Kovatchev BP, Cobelli C. Incorporating nonlinear response to hypoglycemia into the type 1 diabetes simulator. Paper presented at: 11th Diabetes Technology Meeting; October 27-29, 2011; San Francisco, CA.