Interspecies Prediction of Human Drug Clearance Based on Scaling Data from One or Two Animal Species

A data-driven approach was adopted to derive new one- and two-species-based methods for predicting human drug clearance (CL) using CL data from rat, dog, or monkey (n = 102). The new one-species methods were developed as CLhuman/kg = 0.152 · CLrat/kg, CLhuman/kg = 0.410 · CLdog/kg, and CLhuman/kg = 0.407 · CLmonkey/kg, referred to as the rat, dog, and monkey methods, respectively. The coefficient of the monkey method (0.407) was similar to that of the monkey liver blood flow (LBF) method (0.467), whereas the coefficients of the rat method (0.152) and dog method (0.410) were considerably different from those of the LBF methods (rat, 0.247; dog, 0.700). The new rat and dog methods appeared to perform better than the corresponding LBF methods, whereas the monkey method and the monkey LBF method showed improved predictability compared with the rat and dog one-species-based methods and the allometrically based “rule of exponents” (ROE). The new two-species methods were developed as CLhuman = arat-dog · W human0.628 (referred to as rat-dog method) and CLhuman = arat-monkey · W human0.650 (referred to as rat-monkey method), where arat-dog and arat-monkey are the coefficients obtained allometrically from the corresponding two species. The predictive performance of the two-species methods was comparable with that of the three-species-based ROE. Twenty-six Wyeth compounds having data from mouse, rat, dog, monkey, and human were used to test these methods. The results showed that the rat, dog, monkey, rat-dog, and rat-monkey methods provided improved predictions for the majority of the compounds compared with those for the ROE, suggesting that the use of three or more species in an allometrically based approach may not be necessary for the prediction of human exposure.