title: Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes.
abstract: A nonlinear model predictive controller has been developed to maintain normoglycemia in subjects with type 1 diabetes during fasting conditions such as during overnight fast. The controller employs a compartment model, which represents the glucoregulatory system and includes submodels representing absorption of subcutaneously administered short-acting insulin Lispro and gut absorption. The controller uses Bayesian parameter estimation to determine time-varying model parameters. Moving target trajectory facilitates slow, controlled normalization of elevated glucose levels and faster normalization of low glucose values. The predictive capabilities of the model have been evaluated using data from 15 clinical experiments in subjects with type 1 diabetes. The experiments employed intravenous glucose sampling (every 15 min) and subcutaneous infusion of insulin Lispro by insulin pump (modified also every 15 min). The model gave glucose predictions with a mean square error proportionally related to the prediction horizon with the value of 0.2 mmol L(-1) per 15 min. The assessment of clinical utility of model-based glucose predictions using Clarke error grid analysis gave 95% of values in zone A and the remaining 5% of values in zone B for glucose predictions up to 60 min (n = 1674). In conclusion, adaptive nonlinear model predictive control is promising for the control of glucose concentration during fasting conditions in subjects with type 1 diabetes.
authors.affiliation: Diabetes Modelling Group, Department of Paediatrics, University of Cambridge, Box 116, Addenbrooke's Hospital, Hills Road, Cambridge CB2 2QQ, UK. r.hovorka@uk.avecho.com
authors.forename: Roman
authors.initials: R
authors.lastname: Hovorka
authors.forename: Valentina
authors.initials: V
authors.lastname: Canonico
authors.forename: Ludovic J
authors.initials: LJ
authors.lastname: Chassin
authors.forename: Ulrich
authors.initials: U
authors.lastname: Haueter
authors.forename: Massimo
authors.initials: M
authors.lastname: Massi-Benedetti
authors.forename: Marco
authors.initials: M
authors.lastname: Orsini Federici
authors.forename: Thomas R
authors.initials: TR
authors.lastname: Pieber
authors.forename: Helga C
authors.initials: HC
authors.lastname: Schaller
authors.forename: Lukas
authors.initials: L
authors.lastname: Schaupp
authors.forename: Thomas
authors.initials: T
authors.lastname: Vering
authors.forename: Malgorzata E
authors.initials: ME
authors.lastname: Wilinska
mesh_terms: D001786:Blood Glucose / Q000502:physiology*; D003922:Diabetes Mellitus, Type 1 / Q000503:physiopathology*; D005544:Forecasting; D006801:Humans; D007004:Hypoglycemic Agents / Q000493:pharmacokinetics / Q000494:pharmacology / Q000627:therapeutic use*; D007328:Insulin / Q000031:analogs & derivatives* / Q000493:pharmacokinetics / Q000494:pharmacology / Q000627:therapeutic use*; D061268:Insulin Lispro; D008962:Models, Theoretical
chemical_list: D001786:Blood Glucose; D007004:Hypoglycemic Agents; D007328:Insulin; D061268:Insulin Lispro