Pharmacokinetic-pharmacodynamic (PK-PD) data analyses from early hepatitis C virus (HCV) clinical trials failed to show a good correlation between the plasma inhibitory quotient (IQ) and antiviral activity of different classes of directly acting antiviral agents (DAAs). The present study explored whether use of the liver partition coefficient-corrected IQ (LCIQ) could improve the PK-PD relationship. Animal liver partition coefficients (Kp(liver)) were calculated from liver to plasma exposure ratios. In vitro hepatocyte partition coefficients (Kp(hep)) were determined by the ratio of cellular to medium drug concentrations. Human Kp(liver) was predicted using an in vitro-in vivo proportionality method: the species-averaged animal Kp(liver) multiplied by the ratio of human Kp(hep) over those in animals. LCIQ was calculated using the IQ multiplied by the predicted human Kp(liver). Our results demonstrated that the in vitro-in vivo proportionality approach provided the best human Kp(liver) prediction, with prediction errors of <45% for all 5 benchmark drugs evaluated (doxorubicin, verapamil, digoxin, quinidine, and imipramine). Plasma IQ values correlated poorly (r(2) of 0.48) with maximum viral load reduction and led to a corresponding 50% effective dose (ED(50)) IQ of 42, with a 95% confidence interval (CI) of 0.1 to 148534. In contrast, the LCIQ-maximum VLR relationship fit into a typical sigmoidal curve with an r(2) value of 0.95 and an ED(50) LCIQ of 121, with a 95% CI of 83 to 177. The present study provides a novel human Kp(liver) prediction model, and the LCIQ correlated well with the viral load reductions observed in short-term HCV monotherapy of different DAAs and provides a valuable tool to guide HCV drug discovery.