title: In silico optimization of basal insulin infusion rate during exercise: implication for artificial pancreas.
abstract: BACKGROUND
  Several clinical trials have been performed to assess safety and efficacy of closed-loop control. Some included physical activity (PA), with the goal of challenging the control algorithms with a rapid change in insulin sensitivity while reducing the risk of hypoglycemia. However, the question remains as to the necessity to inform the control algorithm on the imminent PA. The aim here is to assess in silico (i) if it is necessary to announce upcoming PA and (ii) if this is the case, what is the safest strategy of basal insulin reduction in the context of the closed-loop control.
  
  
  METHODS
  We modified the University of Virginia/Padova type 1 diabetes simulator to incorporate the effect of PA based on a study in healthy subjects that demonstrated an almost doubling of insulin sensitivity during PA versus rest. Two in silico experiments, including a PA session, have been simulated on the virtual adult population: one in the absence of and one with different degrees of reductions and durations of basal insulin infusion rates.
  
  
  RESULTS
  Most in silico subjects experienced hypoglycemia in the absence of basal insulin adjustment. We show that, in the absence of patient-specific information, a safe and effective strategy is to reduce basal insulin by 50% starting 90 min before exercise and by 30% during exercise.
  
  
  CONCLUSIONS
  Our results suggest that control algorithms could benefit by knowing an upcoming PA. Ideally, the control algorithm should be informed about the patient-specific basal insulin reduction pattern. An alternative strategy that has been proposed here has been deemed safe and effective in in silico experiments.
authors.affiliation: Department of Information Engineering, University of Padova, Via Gradenigo 6/B, I-35131 Padova, Italy.
authors.forename: Michele
authors.initials: M
authors.lastname: Schiavon
authors.forename: Chiara
authors.initials: C
authors.lastname: Dalla Man
authors.forename: Yogish C
authors.initials: YC
authors.lastname: Kudva
authors.forename: Ananda
authors.initials: A
authors.lastname: Basu
authors.forename: Claudio
authors.initials: C
authors.lastname: Cobelli
mesh_terms: D000465:Algorithms; D001786:Blood Glucose / Q000378:metabolism*; D003198:Computer Simulation; D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000188:drug therapy*; D004305:Dose-Response Relationship, Drug; D015444:Exercise / Q000502:physiology*; D006801:Humans; D007003:Hypoglycemia / Q000503:physiopathology / Q000517:prevention & control; D007328:Insulin / Q000008:administration & dosage* / Q000627:therapeutic use*; D007558:Italy; D008954:Models, Biological; D019397:Pancreas, Artificial; D013997:Time Factors; D014481:United States
chemical_list: D001786:Blood Glucose; D007328:Insulin