Prediction of Apparent Oral Clearance of Small-Molecule Inhibitors in Pediatric Patients

The purpose of this study was to build regression models for the prediction of apparent oral clearance (CL/F) for small-molecule inhibitors in the pediatric population using data obtained from adults. Two approaches were taken; a simple allometric regression model which considers no interdrug or interindividual variability and an allometric regression model with mixed-effects modeling where some variability parameters are included in the model. Average CL/F values were obtained for 15 drugs at various dosages from 31 literatures (a total of 139 data sets) conducted in adults and for 15 drugs from 26 literatures (62 data sets) conducted in children. Data were randomly separated into the “modeling” or “validation” data set, and the 2 allometric regression models were applied to the modeling data set. The predictive ability of the models was examined by comparing the observed and model-predicted CL/F in children using the validation data set. The percentage root mean square error was 17.2% and 26.3% in the simple allometric regression model and the allometric regression model with mixed-effects modeling, respectively. The predictive ability of the 2 models seems acceptable, suggesting that they could be useful for predicting the CL/F of new small-molecule inhibitors and for determining adequate doses in clinical pharmacotherapy for children.