The Use of ROC Analysis for the Qualitative Prediction of Human Oral Bioavailability from Animal Data

Purpose To develop and evaluate a tool for the qualitative pre-diction of human oral bioavailability (Fhuman) from animal oral bioavailability (Fanimal) data employing ROC analysis and to identify the optimal thresholds for such predictions. Methods A dataset of 184 compounds with known Fhuman and Fanimal in at least one species (mouse, rat, dog and non-human primates (NHP)) was employed. A binary classification model for Fhuman was built by setting a threshold for high/low Fhuman at 50%. The thresholds for high/low Fanimal were varied from 0 to 100 to generate the ROC curves. Optimal thresholds were derived from ‘cost analysis ’ and the outcomes with respect to false negative and false positive predictions were analyzed against the BDDCS class distributions. Results We successfully built ROC curves for the combined dataset and per individual species. Optimal Fanimal thresholds wer