Predictive power of indices derived from models of biological dynamic systems

We are given a reliable parametric model of a system whose structure and parameter values can be obtained by an identification experiment. Often, one or more indices can be determined as a function of model parameters, i.e. an index is a function that maps the parameter space into the real line. The aim of these indices is to incorporate as much information as possible on a certain phenomenon of interest described by the model. The paper proposes an approach to compare competitive indices in terms of predictive power of system output. The new concept is applied to the minimal model of glucose kinetics, by comparing the performance of two different insulin sensitivity indices whose objective is to describe insulin ability to control glucose.