c Carbapenem-resistant bacteria represent a significant treatment challenge due to the lack of active antimicrobials available. MK-7655 is a novel ␤-lactamase inhibitor under clinical development. We investigated the combined killing activity of imipenem and MK-7655 against four imipenem-resistant bacterial strains, using a mathematical model previously evaluated in our laboratory. Time-kill studies (TKS) were conducted with imipenem and MK-7655 against a KPC-2-producing Klebsiella pneumoniae isolate (KP6339) as well as 3 Pseudomonas aeruginosa isolates (PA24226, PA24227, and PA24228) with OprD porin deletions and overexpression of AmpC. TKS were performed using 25 clinically achievable concentration combinations in a 5-by-5 array. Bacterial burden at 24 h was determined in triplicate by quantitative culture and mathematically modeled using a three-dimensional response surface. Mathematical model assessments were evaluated experimentally using clinically relevant dosing regimens of imipenem, with or without MK-7655, in a hollow-fiber infection model (HFIM). The combination of imipenem and MK-7655 was synergistic for all strains. Interaction indices were as follows: for KP6339, 0.50 (95% confidence interval [CI], 0.42 to 0.58); for PA24226, 0.60 (95% CI, 0.58 to 0.62); for PA24227, 0.70 (95% CI, 0.66 to 0.74); and for PA24228, 0.55 (95% CI, 0.49 to 0.61). In the HFIM, imipenem plus MK-7655 considerably reduced the bacterial burden at 24 h, while failure with imipenem alone was seen against all isolates. Sustained suppression of bacterial growth at 72 h was achieved with simulated doses of 500 mg imipenem plus 500 mg MK-7655 in 2 (KP6339 and PA24227) strains, and it was achieved in an additional strain (PA24228) when the imipenem dose was increased to 1,000 mg. Additional studies are being conducted to determine the optimal dose and combinations to be used in clinical investigations.

Trends of rising rates of resistance in Pseudomonas aeruginosa make selection of appropriate empirical therapy increasingly difficult, but whether multidrug-resistant (MDR) P. aeruginosa is associated with worse clinical outcomes is not well established. The objective of this study was to determine the impact of MDR (resistance to three or more classes of antipseudomonal agents) P. aeruginosa bacteremia on patient outcomes. We performed a retrospective cohort study of adult patients with P. aeruginosa bacteremia from 2005 to 2008. Patients were identified by the microbiology laboratory database, and pertinent clinical data were collected. Logistic regression was used to explore independent risk factors for 30-day mortality. Classification and regression tree analysis was used to determine threshold breakpoints for continuous variables. Kaplan-Meier survival analysis was used to compare time to mortality, after normalization of the patients' underlying risks by propensity scoring. A total of 109 bacteremia episodes were identified; 25 episodes (22.9%) were caused by MDR P. aeruginosa. Patients with MDR P. aeruginosa bacteremia were more likely to receive inappropriate empirical therapy (44.0% and 6.0%, respectively; P < 0.001) and had longer prior hospital stays (32.6 ؎ 37.3 and 14.4 ؎ 43.6 days, respectively; P ‫؍‬ 0.046). Multivariate regression revealed that 30-day mortality was associated with multidrug resistance (odds ratio [OR], 6.8; 95% confidence interval [CI], 1.9 to 24.0), immunosuppression (OR, 5.0; 95% CI, 1.4 to 17.5), and an APACHE II score of >22 (OR, 29.0; 95% CI, 5.0 to 168.2). Time to mortality was also shorter in the MDR cohort (P ‫؍‬ 0.011). Multidrug resistance is a significant risk factor for 30-day mortality in patients with P. aeruginosa bacteremia; efforts to curb the spread of MDR P. aeruginosa could be beneficial.

The scarcity of new antibiotics against drug-resistant bacteria has led to the development of inhibitors targeting specific resistance mechanisms, which aim to restore the effectiveness of existing agents. However, there are few guidelines for the optimal dosing of inhibitors. Extending the utility of mathematical modeling, which has been used as a decision support tool for antibiotic dosing regimen design, we developed a novel mathematical modeling framework to guide optimal dosing strategies for a beta-lactamase inhibitor. To illustrate our approach, MK-7655 was used in combination with imipenem against a clinical isolate of Klebsiella pneumoniae known to produce KPC-2. A theoretical concept capturing fluctuating susceptibility over time was used to define a novel pharmacodynamic index (time above instantaneous MIC [T>MIC i ]). The MK-7655 concentration-dependent MIC reduction was characterized by using a modified sigmoid maximum effect (E max )-type model. Various dosing regimens of MK-7655 were simulated to achieve escalating T>MIC i values in the presence of a clinical dose of imipenem (500 mg every 6 h). The effectiveness of these dosing exposures was subsequently validated by using a hollow-fiber infection model (HFIM). An apparent trend in the bacterial response was observed in the HFIM with increasing T>MIC i values. In addition, different dosing regimens of MK-7655 achieving a similar T>MIC i (69%) resulted in comparable bacterial killing over 48 h. The proposed framework was reasonable in predicting the in vitro activity of a novel beta-lactamase inhibitor, and its utility warrants further investigations.

Our modeling approach appeared to be robust in assessing the effectiveness of various combinations for KPC-producing isolates. Amikacin plus doripenem was the most effective combination in both in vitro and in vivo infection models. Empirical selection of combinations against KPCs may result in antagonism and should be avoided.

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