Circadian variability of insulin sensitivity: Physiological input for in silico artificial pancreas

Roberto Visentin, Chiara Dalla Man, Yogish C. Kudva, Ananda Basu, Claudio Cobelli

Research output: Contribution to journalArticlepeer-review

55 Scopus citations


Closed-loop control clinical research trials have been considerably accelerated by in silico trials using the Food and Drug Administration-accepted type 1 diabetes mellitus (T1DM) simulator. We have recently demonstrated that postprandial insulin sensitivity (SI) in T1DM subjects was lower at breakfast (B) than lunch (L) and dinner (D), but not significantly, because of the small population size. The goal of this study was therefore to incorporate this novel information into the University of Virginia/Padova T1DM simulator and to reproduce in silico the observed circadian variability. Twenty T1DM subjects received an identical mixed meal at B, L, and D. SI was calculated for each meal using the oral glucose minimal model. Seven SI daily patterns were identified, and their probabilities were estimated. Each in silico subject was linked to a time-varying SI profile, while random deviations of up to 40% were allowed. Simulations were compared with experimental data. The integrated area above the basal glucose curve values were 2.60±0.91 (B), 1.38±0.91 (L), and 1.44±1.07 (D) 104 min·mg/dL in silico versus 2.87±1.65 (B), 1.98±1.56 (L), and 2.16±2.00 (D) 104 min·mg/dL in vivo. Incremental peak glucose values were 109±33 (B), 80±29 (L), and 81±30 (D) mg/dL in silico versus 136±39 (B), 126±37 (L), and 125±48 (D) mg/dL in vivo. The incorporation of a time-varying SI into the simulator makes this technology suitable for running multiple-meal scenarios, thus enabling a more robust design of artificial pancreas algorithms.

Original languageEnglish (US)
Pages (from-to)1-7
Number of pages7
JournalDiabetes Technology and Therapeutics
Issue number1
StatePublished - Jan 1 2015

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Endocrinology
  • Medical Laboratory Technology


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