Sandwich-Cultured Hepatocytes as a Tool to Study Drug Disposition and Drug-Induced Liver Injury

Drug Transporter Expression and Activity in Human Hepatoma HuH-7 Cells

Human hepatoma cells may represent a valuable alternative to the use of human hepatocytes for studying hepatic drug transporters, which is now a regulatory issue during drug development. In the present work, we have characterized hepatic drug transporter expression, activity and regulation in human hepatoma HuH-7 cells, in order to determine the potential relevance of these cells for drug transport assays. HuH-7 cells displayed notable multidrug resistance-associated protein (MRP) activity, presumed to reflect expression of various hepatic MRPs, including MRP2. By contrast, they failed to display functional activities of the uptake transporters sodium taurocholate co-transporting polypeptide (NTCP), organic anion-transporting polypeptides (OATPs) and organic cation transporter 1 (OCT1), and of the canalicular transporters P-glycoprotein and breast cancer resistance protein (BCRP). Concomitantly, mRNA expressions of various sinusoidal and canalicular hepatic drug transporters were not detected (NTCP, OATP1B1, organic anion transporter 2 (OAT2), OCT1 and bile salt export pump) or were found to be lower (OATP1B3, OATP2B1, multidrug and toxin extrusion protein 1, BCRP and MRP3) in hepatoma HuH-7 cells than those found in human hepatocytes, whereas other transporters such as OAT7, MRP4 and MRP5 were up-regulated. HuH-7 cells additionally exhibited farnesoid X receptor (FXR)- and nuclear factor erythroid 2-related factor 2 (Nrf2)-related up-regulation of some transporters. Such data indicate that HuH-7 cells, although expressing rather poorly some main hepatic drug transporters, may be useful for investigating interactions of drugs with MRPs, notably MRP2, and for studying FXR- or Nrf2-mediated gene regulation.

The role of quantitative systems pharmacology modeling in the prediction and explanation of idiosyncratic drug-induced liver injury

Idiosyncratic drug-induced liver injury (iDILI) is a serious concern in drug development. The rarity and multifactorial nature of iDILI makes it difficult to predict and explain. Recently, human leukocyte antigen (HLA) allele associations have provided strong support for a role of an adaptive immune response in the pathogenesis of many iDILI cases; however, it is likely that an adaptive immune attack requires several preceding events. Quantitative systems pharmacology (QSP), an in silico modeling technique that leverages known physiology and the results of in vitro experiments in order to make predictions about how drugs affect biological processes, is proposed as a potentially useful tool for predicting and explaining critical events that likely precede immune-mediated iDILI, as well as the immune attack itself. DILIsym, a QSP platform for drug-induced liver injury, has demonstrated success in predicting the presence of delayed hepatocellular stress events that likely precede the iDILI cascade, and has successfully predicted hepatocellular stress likely underlying iDILI attributed to troglitazone and tolvaptan. The incorporation of a model of the adaptive immune system into DILIsym would represent and important advance. In summary, QSP methods can play a key role in the future prediction and understanding of both immune-mediated and non-immune-mediated iDILI.

Prediction of Altered Bile Acid Disposition Due to Inhibition of Multiple Transporters: An Integrated Approach Using Sandwich-Cultured Hepatocytes, Mechanistic Modeling, and Simulation

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 (Ct,Cells) were selected as the model output based on sensitivity analysis. Monte Carlo simulations of TCA Ct,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 (fu,cell,inhibitor), which revealed higher sensitivity of fu,cell,inhibitor for predicting TCA Ct,Cells when inhibitors exhibited larger ([I]t,cell/IC50) 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.