THE GLUCOSE MINIMAL MODEL: POPULATION VS INDIVIDUAL PARAMETER ESTIMATION

Glucose minimal model parameters are commonly estimated by applying weighted nonlinear least squares separately to each subject's data. Because of the model's nonlinearity the parameter precision of the single-compartment minimal model is not always satisfactory, especially in presence of a reduced sampling schedule. In the current work, the use of population analysis through nonlinear mixed effects models is evaluated and its performance tested against the parameter estimates obtained by the standard individual approach through weighted nonlinear least squares.