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  • Review Article
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Closed-loop insulin delivery: from bench to clinical practice

Abstract

Automated closed-loop insulin delivery, also referred to as the 'artificial pancreas', has been an important but elusive goal of diabetes treatment for many decades. Research milestones include the conception of continuous glucose monitoring in the early 1960s, followed by the production of the first commercial hospital-based artificial pancreas in the late 1970s that combined intravenous glucose sensing and insulin delivery. In the past 10 years, research into the artificial pancreas has gained substantial momentum and focused on the subcutaneous route for glucose measurement and insulin delivery, which reflects technological advances in interstitial glucose monitoring and the increasing use of the continuous subcutaneous insulin infusion. This Review discusses the design of an artificial pancreas, its components and clinical results, as well as the advantages and disadvantages of different types of automated closed-loop systems and potential future advances. The introduction of the artificial pancreas into clinical practice will probably occur gradually, starting with simpler approaches, such as overnight control of blood glucose concentration and temporary pump shut-off, that are adapted to more complex situations, such as glycemic control during meals and exercise.

Key Points

  • Closed-loop systems deliver insulin according to real-time glucose levels

  • Closed-loop systems combine three components: a continuous glucose sensor, an insulin pump and a control algorithm

  • The subcutaneous route for glucose sensing and insulin delivery is most promising for widespread clinical use

  • Compared with conventional pump therapy, closed-loop insulin delivery under supervised conditions reduced the frequency of hypoglycemia and increased the time within the target glucose range

  • Introduction into clinical practice may be gradual, beginning with simpler approaches, such as overnight control and temporary pump shut-off, that progress to more complex situations, such as control during meals and exercise

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Figure 1: An illustrative depiction of a closed-loop insulin delivery system.

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References

  1. Steil, G. M., Panteleon, A. E. & Rebrin, K. Closed-loop insulin delivery-the path to physiological glucose control. Adv. Drug Deliv. Rev. 56, 125–144 (2004).

    Article  CAS  PubMed  Google Scholar 

  2. Renard, E., Costalat, G., Chevassus, H. & Bringer, J. Artificial beta-cell: clinical experience toward an implantable closed-loop insulin delivery system. Diabetes Metab. 32, 497–502 (2006).

    Article  CAS  PubMed  Google Scholar 

  3. Nishida, K., Shimoda, S., Ichinose, K., Araki, E. & Shichiri, M. What is artificial endocrine pancreas? Mechanism and history. World J. Gastroenterol. 15, 4105–4110 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Shichiri, M. Artificial endocrine pancreas: development and clinical applications (Kamome Press, Kumamoto, 2000).

    Google Scholar 

  5. Kumareswaran, K., Evans, M. L. & Hovorka, R. Artificial pancreas: an emerging approach to treat type 1 diabetes. Expert Rev. Med. Devices 6, 401–410 (2009).

    Article  CAS  PubMed  Google Scholar 

  6. Hovorka, R. The future of continuous glucose monitoring: closed loop. Curr. Diabetes Rev. 4, 269–279 (2008).

    Article  CAS  PubMed  Google Scholar 

  7. Hovorka, R. Continuous glucose monitoring and closed-loop systems. Diabet. Med. 23, 1–12 (2006).

    Article  CAS  PubMed  Google Scholar 

  8. Steil, G. M. & Rebrin, K. Closed-loop insulin delivery—what lies between where we are and where we are going? Expert Opin. Drug Deliv. 2, 353–362 (2005).

    Article  CAS  PubMed  Google Scholar 

  9. Smiley, D. & Umpierrez, G. E. Management of hyperglycemia in hospitalized patients. Ann. NY Acad. Sci. 1212, 1–11 (2010).

    Article  CAS  PubMed  Google Scholar 

  10. Eslami, S., Abu-Hanna, A., de Jonge, E. & de Keizer, N. F. Tight glycemic control and computerized decision-support systems: a systematic review. Intensive Care Med. 35, 1505–1517 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Hirsch, I. B. Clinical review: Realistic expectations and practical use of continuous glucose monitoring for the endocrinologist. J. Clin. Endocrinol. Metab. 94, 2232–2238 (2009).

    Article  CAS  PubMed  Google Scholar 

  12. De Block, C., Vertommen, J., Manuel-y-Keenoy, B. & Van Gaal, L. Minimally-invasive and non-invasive continuous glucose monitoring systems: indications, advantages, limitations and clinical aspects. Curr. Diabetes Rev. 4, 159–168 (2008).

    Article  CAS  PubMed  Google Scholar 

  13. Klonoff, D. C. Continuous glucose monitoring: roadmap for 21st century diabetes therapy. Diabetes Care 28, 1231–1239 (2005).

    Article  PubMed  Google Scholar 

  14. Tamborlane, W. V. et al. Continuous glucose monitoring and intensive treatment of type 1 diabetes. N. Engl. J. Med. 359, 1464–1476 (2008).

    Article  PubMed  Google Scholar 

  15. Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group. The effect of continuous glucose monitoring in well-controlled type 1 diabetes. Diabetes Care 32, 1378–1383 (2009).

  16. Pickup, J. & Keen, H. Continuous subcutaneous insulin infusion at 25 years: evidence base for the expanding use of insulin pump therapy in type 1 diabetes. Diabetes Care 25, 593–598 (2002).

    Article  PubMed  Google Scholar 

  17. Selam, J. L. CSII in Europe: where are we, where are we going? An analysis of articles published in Infusystems International. Diabetes Res. Clin. Pract. 74 (Suppl. 2), S123–S126 (2006).

    Article  Google Scholar 

  18. Bequette, B. W. A critical assessment of algorithms and challenges in the development of a closed-loop artificial pancreas. Diabetes Technol. Ther. 7, 28–47 (2005).

    Article  CAS  PubMed  Google Scholar 

  19. Magni, L. et al. Model predictive control of type 1 diabetes: an in silico trial. J. Diabetes Sci. Technol. 1, 804–812 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Parker, R. S., Doyle, F. J. 3rd & Peppas, N. A. A model-based algorithm for blood glucose control in type I diabetic patients. IEEE Trans. Biomed. Eng. 46, 148–157 (1999).

    Article  CAS  PubMed  Google Scholar 

  21. Hovorka, R. et al. Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes. Physiol. Meas. 25, 905–920 (2004).

    Article  PubMed  Google Scholar 

  22. Albisser, A. M. et al. An artificial endocrine pancreas. Diabetes 23, 389–396 (1974).

    Article  CAS  PubMed  Google Scholar 

  23. Clemens, A. H. Feedback control dynamics for glucose controlled insulin infusion system. Med. Prog. Technol. 6, 91–98 (1979).

    CAS  PubMed  Google Scholar 

  24. Marchetti, G., Barolo, M., Jovanovic, L., Zisser, H. & Seborg, D. E. An improved PID switching control strategy for type 1 diabetes. IEEE Trans. Biomed. Eng. 55, 857–865 (2008).

    Article  PubMed  Google Scholar 

  25. Castle, J. R. et al. Novel use of glucagon in a closed-loop system for prevention of hypoglycemia in type 1 diabetes. Diabetes Care 33, 1282–1287 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Atlas, E., Nimri, R., Miller, S., Grunberg, E. A. & Phillip, M. MD-logic artificial pancreas system: a pilot study in adults with type 1 diabetes. Diabetes Care 33, 1072–1076 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  27. El-Khatib, F. H., Jiang, J. & Damiano, E. R. Adaptive closed-loop control provides blood-glucose regulation using dual subcutaneous insulin and glucagon infusion in diabetic Swine. J. Diabetes Sci. Technol. 1, 181–192 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Rodríguez-Herrero, A. et al. A simulation study of an inverse controller for closed- and semiclosed-loop control in type 1 diabetes. Diabetes Technol. Ther. 12, 95–104 (2010).

    Article  PubMed  Google Scholar 

  29. Lee, H., Buckingham, B. A., Wilson, D. M. & Bequette, B. W. A closed-loop artificial pancreas using model predictive control and a sliding meal size estimator. J. Diabetes Sci. Technol. 3, 1082–1090 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Percival, M. W., Zisser, H., Jovanovic, L. & Doyle, F. J. 3rd. Closed-loop control and advisory mode evaluation of an artificial pancreatic Beta cell: use of proportional-integral-derivative equivalent model-based controllers. J. Diabetes Sci. Technol. 2, 636–644 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Dua, P., Doyle, F. J. 3rd & Pistikopoulos, E. N. Model-based blood glucose control for type 1 diabetes via parametric programming. IEEE Trans. Biomed. Eng. 53, 1478–1491 (2006).

    Article  PubMed  Google Scholar 

  32. Trajanoski, Z. & Wach, P. Neural predictive controller for insulin delivery using the subcutaneous route. IEEE Trans. Biomed. Eng. 45, 1122–1134 (1998).

    Article  CAS  PubMed  Google Scholar 

  33. de Leiva, A. et al. Telemedical artificial pancreas: PARIS (Pancreas Artificial Telemedico Inteligente) research project. Diabetes Care 32 (Suppl. 2), S211–S216 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Dassau, E., Jovanovic, L., Doyle, F. J. 3rd & Zisser, H. C. Enhanced 911/global position system wizard: a telemedicine application for the prevention of severe hypoglycemia—monitor, alert, and locate. J. Diabetes Sci. Technol. 3, 1501–1506 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Kovatchev, B. et al. Control to range for diabetes: functionality and modular architecture. J. Diabetes Sci. Technol. 3, 1058–1065 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Ellingsen, C. et al. Safety constraints in an artificial pancreatic beta cell: an implementation of model predictive control with insulin on board. J. Diabetes Sci. Technol. 3, 536–544 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Hovorka, R. et al. Manual closed-loop insulin delivery in children and adolescents with type 1 diabetes: a phase 2 randomised crossover trial. Lancet 375, 743–751 (2010).

    Article  CAS  PubMed  Google Scholar 

  38. Elleri, D. et al. Suspended insulin infusion during overnight closed-loop glucose control in children and adolescents with type 1 diabetes. Diabet. Med. 27, 480–484 (2010).

    Article  CAS  PubMed  Google Scholar 

  39. Wang, Y., Dassau, E. & Doyle, F. J. 3rd. Closed-loop control of artificial pancreatic Beta -cell in type 1 diabetes mellitus using model predictive iterative learning control. IEEE Trans. Biomed. Eng. 57, 211–219 (2010).

    Article  PubMed  Google Scholar 

  40. Camacho, E. F. & Bordons, C. Model Predictive Control (Springer-Verlag, London, 1999).

    Book  Google Scholar 

  41. Cobelli, C. et al. Diabetes: Models, signals, and control. IEEE Rev. Biomed. Eng. 2, 54–96 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Kovatchev, B., Anderson, S., Heinemann, L. & Clarke, W. Comparison of the numerical and clinical accuracy of four continuous glucose monitors. Diabetes Care 31, 1160–1164 (2008).

    Article  CAS  PubMed  Google Scholar 

  43. Garg, S. K. et al. Comparison of accuracy and safety of the SEVEN and the Navigator continuous glucose monitoring systems. Diabetes Technol. Ther. 11, 65–72 (2009).

    Article  CAS  PubMed  Google Scholar 

  44. Kamath, A., Mahalingam, A. & Brauker, J. Analysis of time lags and other sources of error of the DexCom SEVEN continuous glucose monitor. Diabetes Technol. Ther. 11, 689–695 (2009).

    Article  CAS  PubMed  Google Scholar 

  45. Weinstein, R. L. et al. Accuracy of the 5-day FreeStyle Navigator Continuous Glucose Monitoring System: comparison with frequent laboratory reference measurements. Diabetes Care 30, 1125–1130 (2007).

    Article  CAS  PubMed  Google Scholar 

  46. Garg, S. K., Voelmle, M. & Gottlieb, P. A. Time lag characterization of two continuous glucose monitoring systems. Diabetes Res. Clin. Pract. 87, 348–353 (2010).

    Article  CAS  PubMed  Google Scholar 

  47. Wei, C. et al. Measurement delay associated with the Guardian RT continuous glucose monitoring system. Diabet. Med. 27, 117–122 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Keenan, D. B., Mastrototaro, J. J., Voskanyan, G. & Steil, G. M. Delays in minimally invasive continuous glucose monitoring devices: a review of current technology. J. Diabetes Sci. Technol. 3, 1207–1214 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  49. McGarraugh, G. & Bergenstal, R. Detection of hypoglycemia with continuous interstitial and traditional blood glucose monitoring using the FreeStyle Navigator Continuous Glucose Monitoring System. Diabetes Technol. Ther. 11, 145–150 (2009).

    Article  CAS  PubMed  Google Scholar 

  50. Wilinska, M. E. et al. Overnight closed-loop insulin delivery with model predictive control: assessment of hypoglycemia and hyperglycemia risk using simulation studies. J. Diabetes Sci. Technol. 3, 1109–1120 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  51. El-Khatib, F. H., Russell, S. J., Nathan, D. M., Sutherlin, R. G. & Damiano, E. R. A bihormonal closed-loop artificial pancreas for type 1 diabetes. Sci. Transl. Med. 2, 27ra27 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Heinemann, L. Variability of insulin absorption and insulin action. Diabetes Technol. Ther. 4, 673–682 (2002).

    Article  PubMed  Google Scholar 

  53. Carroll, M. F. & Schade, D. S. The dawn phenomenon revisited: implications for diabetes therapy. Endocr. Pract. 11, 55–64 (2005).

    Article  PubMed  Google Scholar 

  54. Riazi, A., Pickup, J. & Bradley, C. Daily stress and glycaemic control in type 1 diabetes: individual differences in magnitude, direction, and timing of stress-reactivity. Diabetes Res. Clin. Pract. 66, 237–244 (2004).

    Article  CAS  PubMed  Google Scholar 

  55. Turner, B. C., Jenkins, E., Kerr, D., Sherwin, R. S. & Cavan, D. A. The effect of evening alcohol consumption on next-morning glucose control in type 1 diabetes. Diabetes Care 24, 1888–1893 (2001).

    Article  CAS  PubMed  Google Scholar 

  56. Szypowska, A. et al. Age-dependent basal insulin patterns in children with type 1 diabetes treated with continuous subcutaneous insulin infusion. Acta Paediatr. 98, 523–526 (2009).

    Article  PubMed  Google Scholar 

  57. Davidson, P. C., Hebblewhite, H. R., Steed, R. D. & Bode, B. W. Analysis of guidelines for basal-bolus insulin dosing: basal insulin, correction factor, and carbohydrate-to-insulin ratio. Endocr. Pract. 14, 1095–1101 (2008).

    Article  PubMed  Google Scholar 

  58. Steil, G. M., Rebrin, K., Darwin, C., Hariri, F. & Saad, M. F. Feasibility of automating insulin delivery for the treatment of type 1 diabetes. Diabetes 55, 3344–3350 (2006).

    Article  CAS  PubMed  Google Scholar 

  59. Dassau, E., Bequette, B. W., Buckingham, B. A. & Doyle, F. J. 3rd. Detection of a meal using continuous glucose monitoring: implications for an artificial beta-cell. Diabetes Care 31, 295–300 (2008).

    Article  CAS  PubMed  Google Scholar 

  60. Kovatchev, B. et al. Multinational study of subcutaneous model-predictive closed-loop control in type 1 diabetes mellitus: summary of the results. J. Diabetes Sci. Technol. 4, 1374–1381 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Weinzimer, S. A. et al. Fully automated closed-loop insulin delivery versus semiautomated hybrid control in pediatric patients with type 1 diabetes using an artificial pancreas. Diabetes Care 31, 934–939 (2008).

    Article  PubMed  Google Scholar 

  62. Palerm, C. C. et al. Closed-loop insulin delivery utilizing insulin feedback: preliminary clinical results. J. Diabetes Sci. Technol. 3, a124 (2009).

    Google Scholar 

  63. [No authors listed] Epidemiology of severe hypoglycemia in the diabetes control and complications trial. The DCCT Research Group. Am. J. Med. 90, 450–459 (1991).

  64. Tsalikian, E. et al. Prevention of hypoglycemia during exercise in children with type 1 diabetes by suspending basal insulin. Diabetes Care 29, 2200–2204 (2006).

    Article  CAS  PubMed  Google Scholar 

  65. McMahon, S. K. et al. Glucose requirements to maintain euglycemia after moderate-intensity afternoon exercise in adolescents with type 1 diabetes are increased in a biphasic manner. J. Clin. Endocrinol. Metab. 92, 963–968 (2007).

    Article  CAS  PubMed  Google Scholar 

  66. Tsalikian, E. et al. Impact of exercise on overnight glycemic control in children with type 1 diabetes mellitus. J. Pediatr. 147, 528–534 (2005).

    Article  CAS  PubMed  Google Scholar 

  67. Bussau, V. A., Ferreira, L. D., Jones, T. W. & Fournier, P. A. A 10-s sprint performed prior to moderate-intensity exercise prevents early post-exercise fall in glycaemia in individuals with type 1 diabetes. Diabetologia 50, 1815–1818 (2007).

    Article  CAS  PubMed  Google Scholar 

  68. Sigal, R. J. et al. Hyperinsulinemia prevents prolonged hyperglycemia after intense exercise in insulin-dependent diabetic subjects. J. Clin. Endocrinol. Metab. 79, 1049–1057 (1994).

    CAS  PubMed  Google Scholar 

  69. Breton, M. D. Physical activity—the major unaccounted impediment to closed loop control. J. Diabetes Sci. Technol. 2, 169–174 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  70. Renard, E., Place, J., Cantwell, M., Chevassus, H. & Palerm, C. C. Closed-loop insulin delivery using a subcutaneous glucose sensor and intraperitoneal insulin delivery: feasibility study testing a new model for the artificial pancreas. Diabetes Care 33, 121–127 (2010).

    Article  CAS  PubMed  Google Scholar 

  71. Kovatchev, B. P. et al. Assessment of risk for severe hypoglycemia among adults with IDDM: validation of the low blood glucose index. Diabetes Care 21, 1870–1875 (1998).

    Article  CAS  PubMed  Google Scholar 

  72. Hill, N. R. et al. A method for assessing quality of control from glucose profiles. Diabet. Med. 24, 753–758 (2007).

    Article  CAS  PubMed  Google Scholar 

  73. Rodbard, D. Interpretation of continuous glucose monitoring data: glycemic variability and quality of glycemic control. Diabetes Technol. Ther. 11 (Suppl. 1), S55–S67 (2009).

    Article  CAS  PubMed  Google Scholar 

  74. Cryer, P. E. Hypoglycemia: still the limiting factor in the glycemic management of diabetes. Endocr. Pract. 14, 750–756 (2008).

    Article  PubMed  Google Scholar 

  75. Weller, C., Linder, M., Macaulay, A., Ferrari, A. & Kessler, G. Continuous in vivo determination of blood glucose in human subjects. Ann. NY Acad. Sci. 87, 658–668 (1960).

    Article  CAS  PubMed  Google Scholar 

  76. Clemens, A. H., Chang, P. H. & Myers, R. W. The development of Biostator, a Glucose Controlled Insulin Infusion System (GCIIS). Horm. Metab. Res. Suppl. 7, 23–33 (1977).

    CAS  PubMed  Google Scholar 

  77. Pfeiffer, E. F., Thum, C. & Clemens, A. H. The artificial beta cell—a continuous control of blood sugar by external regulation of insulin infusion (glucose controlled insulin infusion system). Horm. Metab. Res. 6, 339–342 (1974).

    Article  CAS  PubMed  Google Scholar 

  78. Renard, E., Costalat, G., Chevassus, H. & Bringer, J. Closed loop insulin delivery using implanted insulin pumps and sensors in type 1 diabetic patients. Diabetes Res. Clin. Pract. 74 (Suppl. 2), S173–S177 (2006).

    Article  CAS  Google Scholar 

  79. Dassau, E. et al. Modular artificial beta-cell system: a prototype for clinical research. J. Diabetes Sci. Technol. 2, 863–872 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Voskanyan, G. et al. Closed-loop insulin delivery utilising insulin feedback: Overnight control. J. Diabetes Sci. Technol. 4, a177 (2010).

    Google Scholar 

  81. Sherr, J. L. et al. Frequency of exercise-related hypoglycemia using a closed-loop artificial pancreas: Preliminary results. J. Diabetes Sci. Technol. 4, a157 (2010).

    Google Scholar 

  82. Hovorka, R. et al. Overnight closed-loop insulin delivery in adults with type 1 diabetes: crossover randomised controlled studies. BMJ (in press).

  83. Murphy, H. R. et al. Closed-loop insulin delivery during pregnancy complicated by type 1 diabetes. Diabetes Care 34, 406–411 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Elleri, D. et al. Automated overnight closed-loop glucose control in young children with type 1 diabetes. Diabetes Technol. Ther. doi:10.1089/dia.2010.0176.

  85. Buckingham, B. et al. Duration of nocturnal hypoglycemia before seizures. Diabetes Care 31, 2110–2112 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  86. Buckingham, B. et al. Prevention of nocturnal hypoglycemia using predictive alarm algorithms and insulin pump suspension. Diabetes Care 33, 1013–1017 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  87. Cengiz, E. et al. Is an automatic pump suspension feature safe for children with type 1 diabetes? An exploratory analysis with a closed-loop system. Diabetes Technol. Ther. 11, 207–210 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Davis, E. A., Keating, B., Byrne, G. C., Russell, M. & Jones, T. W. Hypoglycemia: incidence and clinical predictors in a large population-based sample of children and adolescents with IDDM. Diabetes Care 20, 22–25 (1997).

    Article  CAS  PubMed  Google Scholar 

  89. Sovik, O. & Thordarson, H. Dead-in-bed syndrome in young diabetic patients. Diabetes Care 22 (Suppl. 2), B40–B42 (1999).

    PubMed  Google Scholar 

  90. Elleri, D. et al. Parental attitudes towards overnight closed-loop glucose control in children with type 1 diabetes. Diabetes Technol. Ther. 12, 35–39 (2010).

    Article  PubMed  Google Scholar 

  91. Panteleon, A. E., Loutseiko, M., Steil, G. M. & Rebrin, K. Evaluation of the effect of gain on the meal response of an automated closed-loop insulin delivery system. Diabetes 55, 1995–2000 (2006).

    Article  CAS  PubMed  Google Scholar 

  92. El-Khatib, F. H., Jiang, J. & Damiano, E. R. A feasibility study of bihormonal closed-loop blood glucose control using dual subcutaneous infusion of insulin and glucagon in ambulatory diabetic swine. J. Diabetes Sci. Technol. 3, 789–803 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  93. Patek, S. D. et al. In silico preclinical trials: methodology and engineering guide to closed-loop control in type 1 diabetes mellitus. J. Diabetes Sci. Technol. 3, 269–282 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  94. Chassin, L. J., Wilinska, M. E. & Hovorka, R. Evaluation of glucose controllers in virtual environment: methodology and sample application. Artif. Intell. Med. 32, 171–181 (2004).

    Article  PubMed  Google Scholar 

  95. Wilinska, M. E. & Hovorka, R. Simulation models for in silico testing of closed-loop glucose controllers in type 1 diabetes. Drug Discov. Today Dis. Models 5, 289–298 (2008).

    Article  Google Scholar 

  96. Wilinska, M. E. et al. Simulation environment to evaluate closed-loop insulin delivery systems in type 1 diabetes. J. Diabetes Sci. Technol. 4, 132–144 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  97. Hovorka, R. et al. Closing the loop: the adicol experience. Diabetes Technol. Ther. 6, 307–318 (2004).

    Article  CAS  PubMed  Google Scholar 

  98. Chan, A., Breton, M. D. & Kovatchev, B. P. Effects of pulsatile subcutaneous injections of insulin lispro on plasma insulin concentration levels. J. Diabetes Sci. Technol. 2, 844–852 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  99. Man, C. D., Breton, M. D. & Cobelli, C. Physical activity into the meal glucose-insulin model of type 1 diabetes: in silico studies. J. Diabetes Sci. Technol. 3, 56–67 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  100. Kovatchev, B. P., 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. 3, 44–55 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  101. Basu, R. et al. Effects of age and sex on postprandial glucose metabolism: differences in glucose turnover, insulin secretion, insulin action, and hepatic insulin extraction. Diabetes 55, 2001–2014 (2006).

    Article  CAS  PubMed  Google Scholar 

  102. Hovorka, R. et al. Partitioning glucose distribution/transport, disposal, and endogenous production during IVGTT. Am. J. Physiol. 282, E992–E1007 (2002).

    CAS  Google Scholar 

  103. Hovorka, R., Chassin, L. J., Ellmerer, M., Plank, J. & Wilinska, M. E. A simulation model of glucose regulation in the critically ill. Physiol. Meas. 29, 959–978 (2008).

    Article  PubMed  Google Scholar 

  104. Kanderian, S. S., Weinzimer, S., Voskanyan, G. & Steil, G. M. Identification of intraday metabolic profiles during closed-loop glucose control in individuals with type 1 diabetes. J. Diabetes Sci. Technol. 3, 1047–1057 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  105. Elleri, D. et al. Absorption of an evening meal with complex carbohydrates in type 1 diabetes. Diabetes 50 (Suppl. 1), a422 (2010).

    Google Scholar 

  106. Capani, F. et al. Insulin requirement of simple and complex carbohydrate foods in type 1 (insulin-dependent) CSII-treated diabetic subjects, obtained by biostator. Correlation with glycaemic index. Acta Diabetol. Lat. 28, 47–53 (1991).

    Article  CAS  PubMed  Google Scholar 

  107. Klonoff, D. C. The need for a glycemia modeling comparison workshop to facilitate development of an artificial pancreas. J. Diabetes Sci. Technol. 4, 1–3 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  108. Kowalski, A. J. Can we really close the loop and how soon? Accelerating the availability of an artificial pancreas: a roadmap to better diabetes outcomes. Diabetes Technol. Ther. 11 (Suppl. 1), S113–S119 (2009).

    Article  CAS  PubMed  Google Scholar 

  109. Pinkos, A. et al. FDA's proactive role in the development of an artificial pancreas for the treatment of diabetes mellitus. Drug Discov. Today Technol. 4, 25–28 (2007).

    Article  PubMed  Google Scholar 

  110. Vaughn, D. E. et al. Accelerated pharmacokinetics and glucodynamics of prandial insulins injected with recombinant human hyaluronidase. Diabetes Technol. Ther. 11, 345–352 (2009).

    Article  CAS  PubMed  Google Scholar 

  111. Steiner, S. et al. A novel insulin formulation with a more rapid onset of action. Diabetologia 51, 1602–1606 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Raz, I. et al. Effect of a local heating device on insulin and glucose pharmacokinetic profiles in an open-label, randomized, two-period, one-way crossover study in patients with type 1 diabetes using continuous subcutaneous insulin infusion. Clin. Ther. 31, 980–987 (2009).

    Article  CAS  PubMed  Google Scholar 

  113. Pettis, R. J. et al. Intradermal injection of regular or lispro insulin with microneedles provides faster insulin uptake and postprandial glycemic benefit. J. Diabetes Sci. Technol. 4, a127 (2010).

    Google Scholar 

  114. Liebl, A. et al. A reduction in severe hypoglycaemia in type 1 diabetes in a randomized crossover study of continuous intraperitoneal compared with subcutaneous insulin infusion. Diabetes Obes. Metab. 11, 1001–1008 (2009).

    Article  CAS  PubMed  Google Scholar 

  115. Weyer, C. et al. Pramlintide reduces postprandial glucose excursions when added to regular insulin or insulin lispro in subjects with type 1 diabetes: a dose-timing study. Diabetes Care 26, 3074–3079 (2003).

    Article  CAS  PubMed  Google Scholar 

  116. Lindpointner, S. et al. Use of the site of subcutaneous insulin administration for the measurement of glucose in patients with type 1 diabetes. Diabetes Care 33, 595–601 (2010).

    Article  CAS  PubMed  Google Scholar 

  117. Bergenstal, R. M. et al. Effectiveness of sensor-augmented insulin-pump therapy in type 1 diabetes. N. Engl. J. Med. 363, 311–320 (2010).

    Article  CAS  PubMed  Google Scholar 

  118. Ritholz, M. D. et al. Psychosocial factors associated with use of continuous glucose monitoring. Diabet. Med. 27, 1060–1065 (2010).

    Article  CAS  PubMed  Google Scholar 

  119. Ritholz, M. D. et al. Perceptions of psychosocial factors and the insulin pump. Diabetes Care 30, 549–554 (2007).

    Article  PubMed  Google Scholar 

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Acknowledgements

R. Hovorka is supported by grants from the Juvenile Diabetes Research Foundation (#22-2006-1113, #22-2007-1801, #22-2009-801), Diabetes UK (BDA07/0003549, BDA07/0003551), European Commission Framework Program 7 (247138), the NIH (DK085621) and the NIHR Cambridge Biomedical Research Centre.

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The author declares associations with the following companies/organizations: Abbott Diabetes Care (grant/research support), Animas (grant/research support, consultant, speaker), Lifescan (speaker), Medtronic (speaker), University of Cambridge (patent holder).

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Hovorka, R. Closed-loop insulin delivery: from bench to clinical practice. Nat Rev Endocrinol 7, 385–395 (2011). https://doi.org/10.1038/nrendo.2011.32

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