Transporter-mediated alterations in bile acid disposition may have significant toxicological implications. Current methods to predict interactions are limited by the interplay of multiple transporters, absence of protein in the experimental system, and inaccurate estimates of inhibitor concentrations. An integrated approach was developed to predict altered bile acid disposition due to inhibition of multiple transporters using the model bile acid taurocholate (TCA). TCA pharmacokinetic parameters were estimated by mechanistic modeling using sandwich-cultured human hepatocyte data with protein in the medium. Uptake, basolateral efflux, and biliary clearance estimates were 0.63, 0.034, and 0.074 mL/min/g liver, respectively. Cellular total TCA concentrations (C t,Cells ) were selected as the model output based on sensitivity analysis. Monte Carlo simulations of TCA C t,Cells in the presence of model inhibitors (telmisartan and bosentan) were performed using inhibition constants for TCA transporters and inhibitor concentrations, including cellular total inhibitor concentrations ([I] t,cell ) or unbound concentrations, and cytosolic total or unbound concentrations. For telmisartan, the model prediction was accurate with an average fold error (AFE) of 0.99-1.0 when unbound inhibitor concentration ([I] u ) was used; accuracy dropped when total inhibitor concentration ([I] t ) was used. For bosentan, AFE was 1.2-1.3 using either [I] u or [I] t . This difference was evaluated by sensitivity analysis of the cellular unbound fraction of inhibitor (f u,cell,inhibitor ), which revealed higher sensitivity of f u,cell,inhibitor for predicting TCA C t,Cells when inhibitors exhibited larger ([I] t,cell /IC 50 ) values. In conclusion, this study demonstrated the applicability of a framework to predict hepatocellular bile acid concentrations due to drug-mediated inhibition of transporters using mechanistic modeling and cytosolic or cellular unbound concentrations.