The Novel In Vitro Method to Calculate Tissue-to-Plasma Partition Coefficient in Humans for Predicting Pharmacokinetic Profiles by Physiologically-Based Pharmacokinetic Model With High Predictability

Abstract

Proper prediction of human pharmacokinetic (PK) profiles can accelerate the compound selection in drug discovery. Recently, we reported a robust bottom-up physiologically-based pharmacokinetic (PBPK) approach (J Pharm Sci. 2019 Aug; 108(8):2718-2727), which uses the in vivo rat distribution volume at the steady state (V_ss) to determine human tissue-to-plasma partition coefficients (Kp_tissue). Here, we report on a bottom-up PBPK approach that can simulate the PK profile with both high-throughput and high-predictive accuracy only using in vitro data. In this study, as an alternative parameter of in vivo rat V_ss which was used for the correction of human Kp_tissue, V_{ss, in vitro} was obtained from protein binding data in rats, and the values of V_{ss, in vitro} for 31 reference compounds showed good correlation with the observed rat V_ss (R² = 0.859). Next, rat and human PK profiles of reference compounds were predicted by the bottom-up PBPK approach using Kp_tissue corrected by rat V_{ss, in vitro}. As a result, the absolute average fold errors for pharmacokinetic parameters were almost less than 2, showing that these PK profiles could be accurately predicted using in vitro data. This method enables the screening of promising compounds with good PK profiles in humans at an early stage of drug discovery.

Keywords: Absorption, distribution, metabolism, and excretion (ADME); Pharmacokinetics; Physiologically based pharmacokinetic modeling; Protein binding; Tissue distribution.