Physiologically based
pharmacokinetic (PBPK) models are increasingly
used in drug development to simulate changes in both systemic and
tissue exposures that arise as a result of changes in enzyme and/or
transporter activity. Verification of these model-based simulations
of tissue exposure is challenging in the case of transporter-mediated
drug–drug interactions (tDDI), in particular as these may lead
to differential effects on substrate exposure in plasma and tissues/organs
of interest. Gadoxetate, a promising magnetic resonance imaging (MRI)
contrast agent, is a substrate of organic-anion-transporting polypeptide
1B1 (OATP1B1) and multidrug resistance-associated protein 2 (MRP2).
In this study, we developed a gadoxetate PBPK model and explored the
use of liver-imaging data to achieve and refine in vitro–in
vivo extrapolation (IVIVE) of gadoxetate hepatic transporter kinetic
data. In addition, PBPK modeling was used to investigate gadoxetate
hepatic tDDI with rifampicin i.v. 10 mg/kg. In vivo dynamic contrast-enhanced
(DCE) MRI data of gadoxetate in rat blood, spleen, and liver were
used in this analysis. Gadoxetate in vitro uptake kinetic data were
generated in plated rat hepatocytes. Mean (%CV) in vitro hepatocyte
uptake unbound Michaelis–Menten constant (
K
m,u
) of gadoxetate was 106 μM (17%) (
n
= 4 rats), and active saturable uptake accounted for 94% of total
uptake into hepatocytes. PBPK–IVIVE of these data (bottom-up
approach) captured reasonably systemic exposure, but underestimated
the in vivo gadoxetate DCE–MRI profiles and elimination from
the liver. Therefore, in vivo rat DCE–MRI liver data were subsequently
used to refine gadoxetate transporter kinetic parameters in the PBPK
model (top-down approach). Active uptake into the hepatocytes refined
by the liver-imaging data was one order of magnitude higher than the
one predicted by the IVIVE approach. Finally, the PBPK model was fitted
to the gadoxetate DCE–MRI data (blood, spleen, and liver) obtained
with and without coadministered rifampicin. Rifampicin was estimated
to inhibit active uptake transport of gadoxetate into the liver by
96%. The current analysis highlighted the importance of gadoxetate
liver data for PBPK model refinement, which was not feasible when
using the blood data alone, as is common in PBPK modeling applications.
The results of our study demonstrate the utility of organ-imaging
data in evaluating and refining PBPK transporter IVIVE to support
the subsequent model use for quantitative evaluation of hepatic tDDI.