Open AccessPhysiologically‐Based Pharmacokinetic Modeling Approach to Predict Rifampin‐Mediated Intestinal P‐Glycoprotein Induction
Author(s) -
Yamazaki Shinji,
Costales Chester,
Lazzaro Sarah,
Eatemadpour Soraya,
Kimoto Emi,
Varma Manthena V.
Publication year - 2019
Publication title -
cpt: pharmacometrics and systems pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.53
H-Index - 37
ISSN - 2163-8306
DOI - 10.1002/psp4.12458
Subject(s) - physiologically based pharmacokinetic modelling , p glycoprotein , pharmacokinetics , pharmacology , in vivo , efflux , chemistry , digoxin , drug , quinidine , biology , medicine , antibiotics , multiple drug resistance , biochemistry , heart failure , microbiology and biotechnology
Physiologically‐based pharmacokinetic ( PBPK ) modeling is a powerful tool to quantitatively describe drug disposition profiles in vivo , thereby providing an alternative to predict drug–drug interactions ( DDI s) that have not been tested clinically. This study aimed to predict effects of rifampin‐mediated intestinal P‐glycoprotein (Pgp) induction on pharmacokinetics of Pgp substrates via PBPK modeling. First, we selected four Pgp substrates (digoxin, talinolol, quinidine, and dabigatran etexilate) to derive in vitro to in vivo scaling factors for intestinal Pgp kinetics. Assuming unbound Michaelis‐Menten constant ( K m ) to be intrinsic, we focused on the scaling factors for maximal efflux rate (J max ) to adequately recover clinically observed results. Next, we predicted rifampin‐mediated fold increases in intestinal Pgp abundances to reasonably recover clinically observed DDI results. The modeling results suggested that threefold to fourfold increases in intestinal Pgp abundances could sufficiently reproduce the DDI results of these Pgp substrates with rifampin. Hence, the obtained fold increases can potentially be applicable to DDI prediction with other Pgp substrates.