title: The university of Virginia/Padova type 1 diabetes simulator matches the glucose traces of a clinical trial.
abstract: BACKGROUND
  In 2008, the Food and Drug Administration (FDA) accepted our type 1 diabetes mellitus (T1DM) simulator (S2008), equipped with 100 in silico adults, 100 adolescents, and 100 children, as a substitute for preclinical trials for certain insulin treatments, including closed-loop algorithms. Hypoglycemia was well described in the simulator, but recent closed-loop trials showed a much larger frequency of hypoglycemia events in patients compared with the in silico ones. In order to better describe the distribution of glucose concentration observed in clinical trials, the simulator has recently been updated, and modifications have been accepted by the FDA (S2013). The aim of this study is to assess the validity of the S2013 simulator against clinical data and compare its performance with that of the S2008.
  
  
  METHODS
  The database consists of 24 T1DM subjects who received dinner (70.7±3.3 g of carbohydrate) and breakfast (52.9±0.1 g of carbohydrate) in two occasions (open- and closed-loop), for a total of 96 postmeal glucose profiles. Measured plasma glucose profiles were compared with those simulated in 100 in silico adults, and the continuous glucose error grid analysis (CG-EGA) was used to assess the validity of the simulated traces. Moreover, the most common outcome metrics have been compared.
  
  
  RESULTS
  The frequency of hypoglycemia episodes predicted by the S2013 well reproduces that observed during clinical trials as proven by the CG-EGA. In addition, the outcome metrics provided by the S2013 are similar to those observed in clinical trials in a set of T1DM subjects.
  
  
  CONCLUSIONS
  We demonstrated that the virtual subjects of the S2013 are representative of the T1DM population observed in a clinical trial. We conclude that the S2013 is a valid tool usable to test the robustness of closed-loop control algorithms for artificial pancreas.
authors.affiliation: 1 Department of Information Engineering, University of Padova , Padova, Italy .
authors.forename: Roberto
authors.initials: R
authors.lastname: Visentin
authors.forename: Chiara
authors.initials: C
authors.lastname: Dalla Man
authors.forename: Boris
authors.initials: B
authors.lastname: Kovatchev
authors.forename: Claudio
authors.initials: C
authors.lastname: Cobelli
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D001786:Blood Glucose / Q000378:metabolism*; D015190:Blood Glucose Self-Monitoring; D002986:Clinical Trials as Topic; D003198:Computer Simulation; D003922:Diabetes Mellitus, Type 1 / Q000097:blood* / Q000188:drug therapy; D005260:Female; D006801:Humans; D007003:Hypoglycemia / Q000097:blood / Q000139:chemically induced*; D007004:Hypoglycemic Agents / Q000008:administration & dosage / Q000009:adverse effects*; D007328:Insulin / Q000008:administration & dosage / Q000009:adverse effects*; D007332:Insulin Infusion Systems; D008297:Male; D015203:Reproducibility of Results; D014481:United States
chemical_list: D001786:Blood Glucose; D007004:Hypoglycemic Agents; D007328:Insulin