Quantitative property-property relationship for screening-level prediction of intrinsic clearance of volatile organic chemicals in rats and its integration within PBPK models to predict inhalation pharmacokinetics in humans

The objectives of this study were (i) to develop a screening-level quantitative property-property relationship (qppr) for intrinsic clearance (c l int) obtained from in vivo animal studies and (ii) to incorporate it with human physiology in a pbpk model for predicting the inhalation pharmacokinetics of vocs. c l int,calculated as the ratio of the in vivo v max (mol/h/kg bw rat) to the k m (m),was obtained for 26 vocs from the literature. the qppr model resulting from stepwise linear regression analysis passed the validation step (r 2 = 0.8; leave-one-out cross-validation q 2 = 0.75) for c l int normalized to the phospholipid (pl) affinity of the vocs. the qppr facilitated the calculation of c l int (l pl/h/kg bw rat) from the input data on log p ow,log blood: water pc and ionization potential. the predictions of the qppr as lower and upper bounds of the 95 mean confidence intervals (lmci and umci,resp.) were then integrated within a human pbpk model. the ratio of the maximum (using lmci for c l int) to minimum (using umci for c l int) auc predicted by the qppr-pbpk model was 1.36 ± 0.4 and ranged from 1.06 (1,1-dichloroethylene) to 2.8 (isoprene). overall,the integrated qppr-pbpk modeling method developed in this study is a pragmatic way of characterizing the impact of the lack of knowledge of c l int in predicting human pharmacokinetics of vocs,as well as the impact of prediction uncertainty of c l int on human pharmacokinetics of vocs. copyright © 2012 thomas peyret and kannan krishnan.