We've updated our Privacy Policy to make it clearer how we use your personal data. We use cookies to provide you with a better experience. You can read our Cookie Policy here.

Advertisement
An image displaying a Newsletter on tablet, laptop & mobile

To continue reading this article, sign up for FREE to

Technology Networks logo


Membership is FREE and provides you with instant access to email newsletters, digital publications, our full content catalogue & more...

Rat Screening Study Predicts Inhalation PK in Humans

Read time: Less than a minute

Abstract
The objectives of this study were (i) to develop a screening-level Quantitative property-property relationship (QPPR) for intrinsic clearance (CL(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. CL(int), calculated as the ratio of the in vivo V(max) (μmol/h/kg bw rat) to the K(m) (μM), 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 CL(int) normalized to the phospholipid (PL) affinity of the VOCs. The QPPR facilitated the calculation of CL(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 CL(int)) to minimum (using UMCI for CL(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 CL(int) in predicting human pharmacokinetics of VOCs, as well as the impact of prediction uncertainty of CL(int) on human pharmacokinetics of VOCs.

This article is published online in the Journal of Toxicology and is free to access.

Google News Preferred Source Add Technology Networks as a preferred Google source to see more of our trusted coverage.