Quantitative structure pharmacokinetic relationship modelling

This article presents the current methods in quantitative structure pharmacokinetic relationship ŽQSPkR. modelling along with examples using chemicals of toxicological significance. The common method involves: Ži. collecting pharmacokinetic data or determining pharmacokinetic parameters Že.g. elimination half-life, volume of distribution. by fitting to experimental data; and Žii. associating them with the structural features of chemicals using a Free Wilson model. Such QSPkRs have been developed for a few series of chemicals but their usefulness is limited to the exposure scenario and conditions under which the experimental data were originally collected. The alternative approach involves the development of quantitative structure property relationship ŽQSPR. models for parameters, blood:air partition coefficient, tissue:blood partition coefficient, maximal velocity for metabolism and Michaelis affinity constant, of physiologically-based pharmacokinetic ŽPBPK. models which are useful for conducting species, route, dose and scenario extrapolations of the tissue dose of chemicals. Mechanistic QSPRs are available for predicting tissue:blood and blood:air partition coefficients from molecular structure information of chemicals, whereas such approaches are not currently available for hepatic metabolism parameters. However, at the present time, the pharmacokinetics of inhaled volatile organic chemicals can be simulated adequately by considering the physiological limits of the hepatic extraction ratio Ž0 1. and molecular structure-based estimates of partition coefficients in the PBPK model. This current state-of-the-art of structure-based modelling of pharmacokinetics will advance with the development of QSPRs for other chemical-specific parameters of PBPK models. Integrated QSPR PBPK modelling should facilitate the identification of chemicals of a family that possess desired properties of bioaccumulation and blood concentration profile in both test animals and humans.