A 'middle-out approach' for the prediction of human drug disposition from preclinical data using simplified physiologically based pharmacokinetic (PBPK) models.

Simplified physiologically based pharmacokinetic (PBPK) models, using estimated tissue-to-unbound plasma partition coefficients (Kpu), were previously investigated by fitting them to in vivo pharmacokinetic (PK) data. After optimisation with preclinical data, the performance of these models for extrapolation of distribution kinetics to human were evaluated to determine the best approach for prediction of human drug disposition and volume of distribution (Vss) using PBPK modelling. Three lipophilic bases were tested (diazepam, midazolam and basmisanil) for which intravenous PK data were available in rat, monkey and human. The models with Kpu scalars using K-means clustering were generally the best for fitting data in the preclinical species and gave plausible Kpu values. Extrapolations of plasma concentrations for diazepam and midazolam using these models and parameters obtained were consistent with observed clinical data. For diazepam and midazolam, the human predictions of Vss after optimisation in rats and monkeys were better compared to the Vss estimated from the traditional PBPK modelling approach (varying from 1.1 to 3.1 vs 3.7-fold error). For basmisanil, the sparse preclinical data available could have affected the model performance for fitting and the subsequent extrapolation to human. Overall, this work provides a rational strategy to predict human drug distribution using preclinical PK data within the PBPK modelling strategy.