The deterministic identifiability of nonlinear pharmacokinetic models.

This paper deals with the deterministic identifiability of nonlinear pharmacokinetic models, namely, whether the model parameters can be identified with perfect data. It is shown that the most familiar method for analyzing the deterministic identifiability of linear models, in which the Laplace transform of the observation is examined, does not work for nonlinear models. An alternative method, in which the observation is expanded as a Taylor series about t = 0, is described and is illustrated with some examples of nonlinear models familiar in the pharmacokinetics literature, in which an elimination rate is assumed capacity limited, with Michaelis-Menten kinetics.