Intravenous zanamivir is recommended for the treatment of hospitalized patients with complicated oseltamivir-resistant influenza virus infections. In a companion paper, we show that the time above the 50 effective concentration (time>EC50) is the pharmacodynamic (PD) index predicting the inhibition of viral replication by intravenous zanamivir. However, for other neuraminidase inhibitors, the ratio of the area under the concentration-time curve to the EC50 (AUC/EC50) is the most predictive index. Our objectives are (i) to explain the dynamically linked variable of intravenous zanamivir by using different half-lives and (ii) to develop a new, mechanism-based population pharmacokinetic (PK)/PD model for the time course of viral load. We conducted dose fractionation studies in the hollow-fiber infection model (HFIM) system with zanamivir against an oseltamivir-resistant influenza virus. A clinical 2.5-h half-life and an artificially prolonged 8-h half-life were simulated for zanamivir. The values for the AUC from 0 to 24 h (AUC0-24) of zanamivir were equivalent for the two half-lives. Viral loads and zanamivir pharmacokinetics were comodeled using data from the present study and a previous dose range experiment via population PK/PD modeling in S-ADAPT. Dosing every 8 h (Q8h) suppressed the viral load better than dosing Q12h or Q24h at the 2.5-h half-life, whereas all regimens suppressed viral growth similarly at the 8-h half-life. The model provided unbiased and precise individual (Bayesian) (r2, >0.96) and population (pre-Bayesian) (r2, >0.87) fits for log10 viral load. Zanamivir inhibited viral release (50 inhibitory concentration [IC50], 0.0168 mg/liter; maximum extent of inhibition, 0.990). We identified AUC/EC50 as the pharmacodynamic index for zanamivir at the 8-h half-life, whereas time>EC50 best predicted viral suppression at the 2.5-h half-life, since the trough concentrations approached the IC50 for the 2.5-h but not for the 8-h half-life. The model explained data at both half-lives and holds promise for optimizing clinical zanamivir dosage regimens.