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

Abstract

The objectives of this study were (i) to develop a screening-level Quantitative property-property relationship (QPPR) for intrinsic clearance (CLint) obtained fromin vivoanimal studies and (ii) to incorporate it with human physiology in a PBPK model for predicting the inhalation pharmacokinetics of VOCs.CLint, calculated as the ratio of thein vivoVmax(μmol/h/kg bw rat) to theKm(μM), was obtained for 26 VOCs from the literature. The QPPR model resulting from stepwise linear regression analysis passed the validation step (R2=0.8; leave-one-out cross-validationQ2=0.75) forCLintnormalized to the phospholipid (PL) affinity of the VOCs. The QPPR facilitated the calculation ofCLint(L PL/h/kg bw rat) from the input data on logPow, 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 forCLint) to minimum (using UMCI forCLint) AUC predicted by the QPPR-PBPK model was1.36±0.4and 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 ofCLintin predicting human pharmacokinetics of VOCs, as well as the impact of prediction uncertainty ofCLinton human pharmacokinetics of VOCs.