A performance limitation for blood glucose regulation in type 1 diabetes accounting for insulin delivery delays

The usual recommendation made by clinicians to type 1 diabetics is that they should inject insulin when consuming a meal or, preferably, slightly earlier. However, in practice, insulin injection maybe delayed. In this paper we develop a fundamental limit on performance when insulin is delivered at some time other than the preferred time. The paper develops an optimal injection policy which minimizes the maximum blood glucose response whilst ensuring that the minimum response does not fall below a pre-specified level. The result provides a “gold standard” against which other insulin injection policies can be compared. Implementation issues are also briefly described.

[1]  Graham C. Goodwin,et al.  Scenario-based, closed-loop model predictive control with application to emergency vehicle scheduling , 2013, Int. J. Control.

[2]  Luigi del Re,et al.  Estimating Interval Process Models for Type 1 Diabetes for Robust Control Design , 2011 .

[3]  T. Alamo,et al.  Stochastic Programming Applied to Model Predictive Control , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[4]  M. A. Krasnoselʹskii,et al.  Positive Linear Systems, the Method of Positive Operators , 1989 .

[5]  Eyal Dassau,et al.  Modeling the Effects of Subcutaneous Insulin Administration and Carbohydrate Consumption on Blood Glucose , 2010, Journal of diabetes science and technology.

[6]  A. Berman,et al.  Nonnegative matrices in dynamic systems , 1979 .

[7]  G. Goodwin,et al.  Stochastic output feedback model predictive control , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[8]  F. Doyle,et al.  Quest for the Artificial Pancreas: Combining Technology with Treatment , 2010, IEEE Engineering in Medicine and Biology Magazine.

[9]  Graham C. Goodwin,et al.  Fundamental Limitations in Filtering and Control , 1997 .

[10]  Graham C. Goodwin,et al.  Feedforward model predictive control , 2011, Annu. Rev. Control..

[11]  L. Quinn,et al.  Estimation of future glucose concentrations with subject-specific recursive linear models. , 2009, Diabetes technology & therapeutics.

[12]  S. Aronoff,et al.  Glucose Metabolism and Regulation: Beyond Insulin and Glucagon , 2004 .

[13]  Andrew J. Felt Stochastic linear model predictive control using nested decomposition , 2003, Proceedings of the 2003 American Control Conference, 2003..

[14]  Graham C. Goodwin,et al.  A fundamental control limitation for linear positive systems with application to Type 1 diabetes treatment , 2015, Autom..

[15]  W. Tamborlane,et al.  The Artificial Pancreas: Are We There Yet? , 2014, Diabetes Care.

[16]  Scott A. Kaestner,et al.  Microneedle-Based Intradermal Delivery Enables Rapid Lymphatic Uptake and Distribution of Protein Drugs , 2010, Pharmaceutical Research.

[17]  Rolf Johansson,et al.  Post-prandial plasma glucose prediction in type I diabetes based on Impulse Response Models , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[18]  Jitka Dupacová,et al.  Scenarios for Multistage Stochastic Programs , 2000, Ann. Oper. Res..

[19]  K. Kumareswaran Closed-loop insulin delivery in adults with type 1 diabetes , 2012 .