Amy N. Schilling

Pharmacodynamics of Polymyxin B against Pseudomonas aeruginosa

ABSTRACT Despite limited data, polymyxin B (PB) is increasingly used clinically as the last therapeutic option for multidrug-resistant (MDR) gram-negative bacterial infections. We examined the in vitro pharmacodynamics of PB against four strains of Pseudomonas aeruginosa. Clonal relatedness of the strains was assessed by random amplification of polymorphic DNA. Time-kill studies over 24 h were performed with approximately 105 and 107 CFU/ml of bacteria, using PB at 0, 0.25, 0.5, 1, 2, 4, 8, and 16× MIC. Dose fractionation studies were performed using an in vitro hollow-fiber infection model (HFIM) against a wild-type and a MDR strain. Approximately 105 CFU/ml of bacteria were exposed to placebo and three regimens (every 8 h [q8h], q12h, and q24h) simulating the steady-state unbound PB pharmacokinetics resulting from a daily dose of 2.5 mg/kg of body weight and 20 mg/kg (8 times the clinical dose). Samples were obtained over 4 days to quantify PB concentrations, total bacterial population, and subpopulation with reduced PB susceptibility (>3× MIC). The bactericidal activity of PB was concentration dependent, but killing was significantly reduced with a high inoculum. In HFIM studies, a significant reduction in bacterial load was seen at 4 h in all active regimens, but selective amplification of the resistant subpopulation(s) was apparent at 24 h with the clinical dose (both strains). Regrowth was eventually observed in all dosing regimens with the MDR strain, but its occurrence was prevented in the wild-type strain by using 8 times the clinical dose (regardless of dosing intervals). Our results suggested that the bactericidal activity of PB was concentration dependent and appeared to be related to the ratio of the area under the concentration-time curve to the MIC.

Optimization of Meropenem Minimum Concentration/MIC Ratio To Suppress In Vitro Resistance of Pseudomonas aeruginosa

ABSTRACT Suppression of resistance in a dense Pseudomonas aeruginosa population has previously been shown with optimized quinolone exposures. However, the relevance to β-lactams is unknown. We investigated the bactericidal activity of meropenem and its propensity to suppress P. aeruginosa resistance in an in vitro hollow-fiber infection model (HFIM). Two isogenic strains of P. aeruginosa (wild type and an AmpC stably derepressed mutant [MIC = 1 mg/liter]) were used. An HFIM inoculated with approximately 1 × 108 CFU/ml of bacteria was subjected to various meropenem exposures. Maintenance doses were given every 8 h to simulate the maximum concentration achieved after a 1-g dose in all regimens, but escalating unbound minimum concentrations (Cmins) were simulated with different clearances. Serial samples were obtained over 5 days to quantify the meropenem concentrations, the total bacterial population, and subpopulations with reduced susceptibilities to meropenem (>3× the MIC). For both strains, a significant bacterial burden reduction was seen with all regimens at 24 h. Regrowth was apparent after 3 days, with the Cmin/MIC ratio being ≤1.7 (time above the MIC, 100%). Selective amplification of subpopulations with reduced susceptibilities to meropenem was suppressed with a Cmin/MIC of ≥6.2 or by adding tobramycin to meropenem (Cmin/MIC = 1.7). Investigations that were longer than 24 h and that used high inocula may be necessary to fully evaluate the relationship between drug exposures and the likelihood of resistance suppression. These results suggest that the Cmin/MIC of meropenem can be optimized to suppress the emergence of non-plasmid-mediated P. aeruginosa resistance. Our in vitro data support the use of an extended duration of meropenem infusion for the treatment of severe nosocomial infections in combination with an aminoglycoside.

Comparative Pharmacodynamics of Gentamicin against Staphylococcus aureus and Pseudomonas aeruginosa

ABSTRACT Aminoglycosides are often used to treat severe infections with gram-positive organisms. Previous studies have shown concentration-dependent killing by aminoglycosides of gram-negative bacteria, but limited data are available for gram-positive bacteria. We compared the in vitro pharmacodynamics of gentamicin against Staphylococcus aureus and Pseudomonas aeruginosa. Five S. aureus strains were examined (ATCC 29213 and four clinical isolates). Time-kill studies (TKS) in duplicate (baseline inocula of 107 CFU/ml) were conducted to evaluate bacterial killing in relation to increasing gentamicin concentrations (0 to 16 times the MIC). Serial samples were obtained over 24 h to quantify bacterial burden. Similar TKS with P. aeruginosa ATCC 27853 were conducted, and the time courses of the all bacterial strains were mathematically modeled for quantitative comparison. A dose fractionation study (using identical daily doses of gentamicin) in an in vitro hollow-fiber infection model (HFIM) over 5 days was subsequently used for data validation for the two ATCC strains. Model fits to the data were satisfactory; r2 values for the S. aureus and P. aeruginosa ATCC strains were 0.915 and 0.956, respectively. Gentamicin was found to have a partially concentration-dependent killing effect against S. aureus; concentrations beyond four to 8 times the MIC did not result in significantly faster bacterial killing. In contrast, a concentration-dependent profile was demonstrated in suppressing P. aeruginosa regrowth after initial decline in bacterial burden. In HFIM, thrice-daily gentamicin dosing appeared to be superior to once-daily dosing for S. aureus, but they were similar for P. aeruginosa. Different killing profiles of gentamicin were demonstrated against S. aureus and P. aeruginosa. These results may guide optimal dosing strategies of gentamicin in S. aureus infections and warrant further investigations.

Novel approach to characterization of combined pharmacodynamic effects of antimicrobial agents.

ABSTRACT There is considerable need for new modeling approaches in the study of combined antimicrobial effects. Current methods based on the Loewe additivity and Bliss independence models are associated with implicit assumptions about the interacting system. To circumvent these limitations, we propose an alternative approach to the quantification of pharmacodynamic drug interaction (PDI). Pilot time-kill studies were performed with 108 CFU of Pseudomonas aeruginosa/ml at baseline with meropenem or tobramycin alone. The studies were repeated with 25 concentration combinations of meropenem (0 to 64 mg/liter) and tobramycin (0 to 32 mg/liter) in a five-by-five array. The data were modeled with a three-dimensional response surface using effect summation as the basis of null interaction. The interaction index (Ii) is defined as the ratio of the volumes under the planes (VUP) of the observed and expected surfaces: VUPobserved/VUPexpected. Synergy and antagonism are defined as Ii values of <1 and >1, respectively. In all combinations, an enhanced killing effect was seen compared to that of either drug at the same concentration. The most significant synergism was observed between 1 and 5 mg/liter of meropenem and between 1 and 4 mg/liter of tobramycin; seven out of nine combinations had a >2-log drop compared to the more potent agent. The Ii was found to be 0.76 (95% confidence interval, 0.65 to 0.91) for the concentration ranges of the agents. The results corroborate previous data indicating that meropenem is synergistic with an aminoglycoside when used in combination against P. aeruginosa. Our parametric approach to quantifying PDI appears robust and warrants further investigations.

Impact of AmpC overexpression on outcomes of patients with Pseudomonas aeruginosa bacteremia

AmpC overexpression (AmpC++) is a significant mechanism of beta-lactam resistance in Pseudomonas aeruginosa, but its impact on clinical outcomes is not well established. To examine the influence of AmpC++ on clinical outcomes of patients with P. aeruginosa bacteremia, we screened all bloodstream P. aeruginosa isolates obtained from 2003 to 2006 for AmpC++. Demographics and outcomes were retrospectively compared between patients with P. aeruginosa bacteremia caused by AmpC++ and pan-susceptible strains (wild-type controls). Of the 263 isolates screened, 63 (24.0%) were nonsusceptible to ceftazidime. Clinical data of 42 AmpC++ isolates from 21 patients were compared with 33 control patients. The 2 groups were similar in sex and race. Patients in the AmpC++ group was more likely to receive inappropriate empiric antibiotics (odds ratio [OR] = 67.5; 95% confidence interval [CI], 6.3-720.0) and experience microbiologic persistence (OR = 12.2; 95% CI, 1.7-87.7). In institutions with a high prevalence of AmpC++, empiric therapy with agents with activity against AmpC++ strains may be warranted.

In vivo dynamics of carbapenem-resistant Pseudomonas aeruginosa selection after suboptimal dosing

We have previously demonstrated Pseudomonas aeruginosa resistance selection because of suboptimal carbapenem exposures in an in vitro infection model, but the in vivo relevance of the observations is not well established. In this study, we examined the impact of carbapenem exposures on resistance selection using a neutropenic murine pneumonia model. Neutropenic mice were infected with approximately 10(6) CFU of P. aeruginosa intratracheally. Ten animals each were treated with 400 or 50 mg/kg of meropenem intraperitoneally or placebo every 8 h, given 2 h after infection for 2 to 4 days. Quantitative assessment of bacterial burden in lung tissues was performed at baseline, upon death, or at the end of experiment. Meropenem (400 mg/kg) offered a significant survival benefit, but selective amplification of the OprD(-) mutant population in lung tissue was observed in 20% to 30% of the animals. Our data suggested that suboptimal meropenem exposures might facilitate in vivo selection of resistance in a heterogeneous P. aeruginosa population.

Modeling of Microbial Population Responses to Time-Periodic Concentrations of Antimicrobial Agents

We present the development and first experimental validation of a mathematical modeling framework for predicting the eventual response of heterogeneous (distributed-resistance) microbial populations to antimicrobial agents at time-periodic (hence pharmacokinetically realistic) concentrations. Our mathematical model predictions are validated in a hollow-fiber in vitro experimental infection model. They are in agreement with the threshold levofloxacin exposure necessary to suppress resistance development of Pseudomonas aeruginosa in a murine thigh infection model. Predictions made by the proposed mathematical modeling framework can offer guidance for targeted testing of promising regimens. This can aid the development and clinical use of antimicrobial agents that combat microbial resistance.