Integral-based identification of a physiological insulin and glucose model on euglycaemic clamp trials and IVGTT trials (Invited)

Abstract

Modelling can enhance the diagnosis and control of metabolic disorders. Clinical effectiveness demands physiological accuracy, patient specificity and identification with limited data. A two-compartment insulin kinetics model and associated insulin-glucose pharmacodynamics are presented. Similarities with a well validated C-peptide model are used to simplify parameter identification. Critical patient specific parameters are identified using a novel convex, integral-based method. The model and methods are validated using euglycaemic- hyperinsulinemic clamp data (N=146). The identified parameter values are within reported physiological ranges. The mean errors in the resulting glucose and insulin profiles are eG = 5.9% ± 6.6% SD and eI = 6.2% ± 6.4% SD, which are within measurement error.