Pharmacokinetics and Pharmacodynamics of Fosfomycin and Its Activity against Extended-Spectrum-β-Lactamase-, Plasmid-Mediated AmpC-, and Carbapenemase-Producing Escherichia coli in a Murine Urinary Tract Infection Model

Abstract

ABSTRACT Fosfomycin has become an attractive treatment alternative for urinary tract infections (UTIs) due to increasing multidrug resistance (MDR) in Escherichia coli . In this study, we evaluated the pharmacokinetic (PK) and pharmacodynamic (PD) indices of fosfomycin and its in vivo activity in an experimental murine model of ascending UTI. Subcutaneous administration of fosfomycin showed that the mean peak plasma concentrations of fosfomycin were 36, 280, and 750 mg/liter following administration of a single dose of 0.75, 7.5, and 30 mg/mouse, respectively, with an elimination half-life of 28 min, and urine peak concentrations of 1,100, 33,400, and 70,000 mg/liter expected to be sustained above 1 mg/liter (MIC of the test strain, NU14) for 5, 8, and 9.5 h, respectively. The optimal PK/PD indices for reducing urine colony counts (number of CFU per milliliter) were determined to be the area under the concentration-time curve/MIC from 0 to 72 h and the maximum concentration/MIC on the basis of the dose-dependent bloodstream PK and the results of an evaluation of six dosing regimens. With a dosing regimen of 15 mg/mouse twice (every 36 h), fosfomycin significantly reduced the number of CFU per milliliter of all susceptible strains in urine, including clinical MDR strains, except for one clinical strain ( P = 0.062). Variable degrees of reduction were observed in the bladder and kidneys. No significant reductions in the number of CFU per milliliter were observed with the resistant strains. In conclusion, fosfomycin shows concentration-dependent in vivo activity, and the results suggest that fosfomycin is an effective alternative to carbapenems in treating MDR E. coli in uncomplicated UTIs. The data on the effectiveness of fosfomycin against the MDR isolates along with the results of PK/PD modeling should facilitate the further development of improved recommendations for its clinical use.