Passive oral drug absorption can be predicted more reliably by experimental than computational models--fact or myth.

This study assessed the prediction power of experimental and computational models that are widely used to predict human passive intestinal absorption. The models evaluated included two cell lines, three artificial membrane models, in vivo rat experiments, and seven previously described computational quantitative structure property relationship models based on human absorption values. The data sets used in the assessment of the models were carefully chosen from the literature, and different models were compared using the same compounds to ensure objective results. Three of the computational models were found to be significantly more reliable in predicting human passive intestinal absorption than the artificial membrane models that have been developed for the prediction of passive intestinal absorption. Two of these computational models were found to be as reliable as the Caco-2 and the 2/4/A1 cell lines and, furthermore, one of the models was able to predict the absorption of a set of 65 drugs nearly as well as absorption studies in rats. The unexpectedly good prediction power of the simple computational models with high throughput makes them ideal tools in the early screening of drug candidates, whereas laborious cell culture models and animal studies can be useful in the later phases when detailed information about the transport mechanisms is needed.