Pharmacokinetic-Pharmacodynamic Modeling of the In Vitro Activities of Oxazolidinone Antimicrobial Agents against Methicillin-ResistantStaphylococcus aureus

Abstract

Linezolid is the first FDA-approved oxazolidinone with activity against clinically important gram-positive pathogens, including methicillin (meticillin)-resistant Staphylococcus aureus (MRSA). RWJ-416457 is a new oxazolidinone with an antimicrobial spectrum similar to that of linezolid. The goal of the present study was to develop a general pharmacokinetic (PK)-pharmacodynamic (PD) model that allows the characterization and comparison of the in vitro activities of oxazolidinones, determined in time-kill curve experiments, against MRSA. The in vitro activities of RWJ-416457 and the first-in-class representative, linezolid, against MRSA OC2878 were determined in static and dynamic time-kill curve experiments over a wide range of concentrations: 0.125 to 8 g/ml (MIC, 0.5 g/ml) and 0.25 to 16 g/ml (MIC, 1 g/ml), respectively. After correction for drug degradation during the time-kill curve experiments, a two-subpopulation model was simultaneously fitted to all data in the NONMEM VI program. The robustness of the model and the precision of the parameter estimates were evaluated by internal model validation by nonparametric bootstrap analysis. A two-subpopulation model, consisting of a self-replicating, oxazolidinone-susceptible and a persistent, oxazolidinone-insusceptible pool of bacteria was appropriate for the characterization of the time-kill curve data. The PK-PD model identified was capable of accounting for saturation in growth, delays in the onsets of growth and drug-induced killing, as well as naturally occurring bacterial death. The simultaneous fit of the proposed indirect-response, maximum-effect model to the data resulted in concentrations that produced a half-maximum killing effect that were significantly (P < 0.05) lower for RWJ-416457 (0.41 g/ml) than for linezolid (1.39 g/ml). In combination with the appropriate PK data, the susceptibility-based two-subpopulation model identified may provide valuable guidance for the selection of oxazolidinone doses or dose regimens for use in clinical studies.

Pharmacokinetic-Pharmacodynamic Model To Evaluate Intramuscular Tetracycline Treatment Protocols To Prevent Antimicrobial Resistance in Pigs

“…1). The estimated rates (k a , k 12 , k 21 , and k el ) were used to produce different concentration-time profiles for different combinations of treatment durations and dosing frequencies that deliver the same daily dose of 20 mg/kg. Three treatment durations (3, 5, and 8 days) and three dosing frequencies (once every 2 days, once per day, and twice per day) were selected, giving a total of nine combinations of concentration profiles.…”

“…Traditional methods for optimizing treatment strategies are generally based on point estimates (e.g., the MIC, maximum drug concentration [C max ], and the area under the concentration time curve [AUC]) (13)(14)(15). In contrast, recent models include the dynamics of both PK and PD processes over time, providing deeper insight and a more accurate description of the impact of antimicrobial dosing strategies (16)(17)(18)(19)(20)(21). However, these studies were based on the in vitro growth of bacterial populations and were limited to a few (sometimes only one) clinical bacterial strains across the susceptible and resistant subpopulations, providing a poor reflection of the within host bacterial dynamics.…”

Pharmacokinetic-Pharmacodynamic Modeling of Antibacterial Drugs

“…20) or a first-order process (eq. 21) characterized by corresponding degradation rate constants (k deg ) ( Zhi et al, 1986;Nielsen et al, 2007;Schmidt et al, 2009).…”

Predicting In Vitro Antibacterial Efficacy across Experimental Designs with a Semimechanistic Pharmacokinetic-Pharmacodynamic Model

“…In only a couple of examples have data from static and dynamic experiments been simultaneously analyzed, and in these examples, common parameter estimates were generally used for the two experimental settings (6,35). In the present study we evaluated potential differences between in vitro systems using a modeling approach.…”