Bile salt export pump (BSEP) inhibition has emerged as an important mechanism that may contribute to the initiation of human drug‐induced liver injury (DILI). Proactive evaluation and understanding of BSEP inhibition is recommended in drug discovery and development to aid internal decision making on DILI risk. BSEP inhibition can be quantified using in vitro assays. When interpreting assay data, it is important to consider in vivo drug exposure. Currently, this can be undertaken most effectively by consideration of total plasma steady state drug concentrations (Css,plasma). However, because total drug concentrations are not predictive of pharmacological effect, the relationship between total exposure and BSEP inhibition is not causal. Various follow‐up studies can aid interpretation of in vitro BSEP inhibition data and may be undertaken on a case‐by‐case basis. BSEP inhibition is one of several mechanisms by which drugs may cause DILI, therefore, it should be considered alongside other mechanisms when evaluating possible DILI risk.

This study considers a 1D fluid dynamics arterial network model with 14 vessels developed to assimilate ex vivo 0D temporal data for pressure-area dynamics in individual vessel segments from 11 male Merino sheep. A 0D model was used to estimate vessel wall parameters in a two-parameter elastic model and a four-parameter Kelvin viscoelastic model. This was done using nonlinear optimization minimizing the least squares error between model predictions and measured cross-sectional areas. Subsequently, estimated values for elastic stiffness and unstressed area were related to construct a nonlinear relationship. This relation was used in the network model. A 1D single vessel model of the aorta was then developed and used to estimate the inflow profile and parameters for total resistance and compliance for the downstream network and to demonstrate effects of incorporating viscoelasticity in the arterial wall. Lastly, the extent to which vessel wall parameters estimated from ex vivo data can be used to realistically simulate pressure and area in a vessel network was evaluated. Elastic wall parameters in the network simulations were found to yield pressure-area relationships across all vessel locations and sheep that were in ranges comparable to those in the ex vivo data.

Elevations in serum bilirubin during drug treatment may indicate global liver dysfunction and a high risk of liver failure. However, drugs also can increase serum bilirubin in the absence of hepatic injury by inhibiting specific enzymes/transporters. We constructed a mechanistic model of bilirubin disposition based on known functional polymorphisms in bilirubin metabolism/transport. Using physiologically based pharmacokinetic (PBPK) model‐predicted drug exposure and enzyme/transporter inhibition constants determined in vitro, our model correctly predicted indinavir‐mediated hyperbilirubinemia in humans and rats. Nelfinavir was predicted not to cause hyperbilirubinemia, consistent with clinical observations. We next examined a new drug candidate that caused both elevations in serum bilirubin and biochemical evidence of liver injury in rats. Simulations suggest that bilirubin elevation primarily resulted from inhibition of transporters rather than global liver dysfunction. We conclude that mechanistic modeling of bilirubin can help elucidate underlying mechanisms of drug‐induced hyperbilirubinemia, and thereby distinguish benign from clinically important elevations in serum bilirubin.