title: Development of a clinical type 1 diabetes metabolic system model and in silico simulation tool.
abstract: OBJECTIVE
  The goal of this study was to develop a system model of type 1 diabetes for the purpose of in silico simulation for the prediction of long-term glycemic control outcomes.
  
  
  METHODS
  The system model was created and identified on a physiological cohort of virtual type 1 diabetes patients (n = 40). Integral-based identification was used to develop (n = 40) insulin sensitivity profiles.
  
  
  RESULTS
  The n = 40 insulin sensitivity profiles provide a driving input for virtual patient trials using the models developed. The identified models have a median (90% range) absolute percentage error of 1.33% (0.08-7.20%). The median (90% range) absolute error was 0.12 mmol/liter (0.01-0.56 mmol/liter). The model and integral-based identification of SI captured all patient dynamics with low error, which would lead to more physiological behavior simulation.
  
  
  CONCLUSIONS
  A simulation tool incorporating n = 40 virtual patient data sets to predict long-term glycemic control outcomes from clinical interventions was developed based on a physiological type 1 diabetes metabolic system model. The overall goal is to utilize this model and insulin sensitivity profiles to develop and optimize self-monitoring blood glucose and multiple daily injection therapy.
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand.
authors.forename: Xing-Wei
authors.initials: XW
authors.lastname: Wong
authors.forename: J Geoffrey
authors.initials: JG
authors.lastname: Chase
authors.forename: Christopher E
authors.initials: CE
authors.lastname: Hann
authors.forename: Thomas F
authors.initials: TF
authors.lastname: Lotz
authors.forename: Jessica
authors.initials: J
authors.lastname: Lin
authors.forename: Aaron J
authors.initials: AJ
authors.lastname: Le
authors.forename: Geoffrey M
authors.initials: GM
authors.lastname: Shaw