Empirical scaling factor for predicting human pharmacokinetic profiles of disproportionate metabolites using the Css-MRTpo method and chimeric mice with humanised livers

Predicting plasma concentration-time profiles of disproportionate metabolites in humans is crucial for evaluating metabolites according to the Safety Testing guidelines. We evaluated Css-MRTpo, an empirical method, using chimeric mice with humanised livers capable of generating human-disproportionate metabolites. Azilsartan and AZ-M2 were administered to humanised chimeric mice, and pharmacokinetic parameters were obtained. Pharmacokinetic data for DS-1971a and DS-M1 in humanised chimeric mice were obtained from the literature. The human plasma concentration-time profiles of these compounds were simulated using the Css-MRTpo method. Azilsartan, DS-1971a, and PF-04937319 produced human disproportionate metabolites, AZ-M2, DS-M1, and PF-M1, respectively. The predicted human pharmacokinetic profiles of PF-04937319 and PF-M1 were obtained from a previous study, and their outcomes were re-evaluated. Our findings revealed that the plasma concentrations of the three metabolites were unexpectedly underpredicted, whereas the three unchanged drugs were reasonably predicted. Further, the introduction of the empirical scaling factor of 3, obtained from six model compounds, improved the predictability of metabolites, suggesting the potential usefulness of the Css-MRTpo method in combination with humanised chimeric mice for predicting the pharmacokinetic profiles of disproportionate metabolites at the early stage of new drug development.

Automated summary

In this study, we evaluated the empirical method Css-MRTpo using chimeric mice with humanised livers to predict the plasma concentration-time profiles of disproportionate metabolites in humans. The results showed that the method could accurately predict the pharmacokinetic profiles of unchanged drugs, but had poor predictability for disproportionate metabolites. The introduction of an empirical scaling factor improved the prediction of metabolites, suggesting the potential usefulness of the Css-MRTpo method combined with humanised chimeric mice for predicting the pharmacokinetic profiles of disproportionate metabolites at the early stage of new drug development.