Effect of acidity of drugs on the prediction of human oral absorption by biopartitioning micellar chromatography

Biopartitioning micellar chromatography (BMC) is a potentially high throughput and low cost alternative for in vitro prediction of drug absorption, which can mimic the drug partitioning process in biological systems. In this paper, a data set of 56 compounds representing acidic, basic, neutral and amphoteric drugs from various structure classes with human oral absorption (HOA) data available were employed to show the effect of acidity of drugs in oral absorption prediction. HOA was reciprocally correlated to the negative value of the capacity factor (kBMC) determined by BMC at pH 7.4 and 6.5. The relationships between kBMC and the corresponding HOA values of all compounds were rather poor, but the correlations were improved when the acidity of drugs was taken into consideration. Moreover, the proposed models allowed obtaining of good predictive values for both highly and poorly absorbed compounds. It is demonstrated that the constructed models derived from compounds with the same kind of charge property are of more practically meaningful and rigorous.