S. Gisbert, L. Aarons and M. Rowland.
Centre for Applied Pharmacokinetic Research, School of Pharmacy and Pharmaceutical Sciences, University of Manchester, UK.
Whole body physiologically based pharmacokinetic (WBPBPK) models are complex as they incorporate a lot of information coming from different sources (literature, in vitro and in vivo experiments) but this allow the models to become predictive and to be used for extrapolation from animal to man. The complexity of the WPBPK model has meant that to date models have mainly been developed by a two-stage process (i) optimisation of the drug dependent parameters and (ii) simulations using literature data on parameter variability and uncertainty.
The aim of the present study was to estimate the parameters of a WBPBPK model with a one-stage process. As the model has a large number of parameters compared to the number of observations, the estimation is difficult. To overcome this problem three approaches were tested: (a) fixing some parameters; (b) using Bayesian priors[1] and (c) integrating mechanistically based equations to predict Kp in the model[2].
The in vivo studies were realised in the rat. Plasma and tissue concentration time profiles were obtained after i.v. bolus administration of a 30 mmol/kg dose of seven barbiturate homologues to standard 250 g male Sprague Dawley rats. The WBPBPK model is composed of 14 tissue and 2 blood compartments and integrates physiological variability. The mechanistically based equations to predict Kp take into account both compound and tissue specific parameters.
Models were developed within NONMEM.
The use of priors did not lead to improved parameter estimation, despite longer run time. The results from the different methods will be compared in the presentation.
References:
(1) Use of Prior Information to Stabilize a Population Data Analysis. Per O. Gisleskog, Mats O. Karlsson, and Stuart L. Beal. Journal of Pharmacokinetics and Pharmacodynamics, Vol. 29, No. 5/6, (Dec. 2002): 473-505.
(2) Quantitative Structure-Pharmacokinetics Relationships: II. A Mechanistically Based Model to Evaluate the Relationship Between Tissue Distribution Parameters and Compound Lipophilicity. I. Nestorov, L. Aarons, and Malcolm Rowland. Journal of Pharmacokinetics and Biopharmaceutics, Vol. 26, No. 5, (1998): 521-545.
Reference: PAGE 13 (2004) Abstr 465 [www.page-meeting.org/?abstract=465]
Poster: poster