Empirical models for fitting of oral concentration time curves with and without an intravenous reference.
Appropriate model selection is important in fitting oral concentration-time data due to the complex character of the absorption process. When IV reference data are available, the problem is the selection of an empirical input function (absorption model). In the present examples a weighted sum of inverse Gaussian density functions (IG) was found most useful. It is shown that alternative models (gamma and Weibull density) are only valid if the input function is log-concave. Furthermore, it is demonstrated for the first time that the sum of IGs model can be also applied to fit oral data directly (without IV data). In the present examples, a weighted sum of two or three IGs was sufficient. From the parameters of this function, the model-independent measures AUC and mean residence time can be calculated. It turned out that a good fit of the data in the terminal phase is essential to avoid parameter biased estimates. The time course of fractional elimination rate and the concept of log-concavity have proved as useful tools in model selection.
Department of Pharmacology, Martin Luther University Halle-Wittenberg, 06097, Halle (Saale), Germany. michael.weiss@medizin.uni-halle.de.
Michael
M
Weiss
D061605:Administration, Intravenous; D000284:Administration, Oral; D000465:Algorithms; D006801:Humans; D008954:Models, Biological; D016011:Normal Distribution; D004364:Pharmaceutical Preparations / Q000008:administration & dosage*
D004364:Pharmaceutical Preparations
Data fitting; Drug absorption; Inverse Gaussian function; Model selection; Oral administration