Fosfomycin is the only expoxide antimicrobial and is currently under development in the United States as an intravenously administered product. We were interested in identifying the exposure indices ...most closely linked to its ability to kill bacterial cells and to suppress amplification of less susceptible subpopulations. We employed the hollow fiber infection model for this investigation and studied wild-type strain
PAO1. Because of anticipated rapid resistance emergence, we shortened the study duration to 24 h but sampled the system more intensively. Doses of 12 and 18 g/day and schedules of daily administration, administration every 8 h, and administration by continuous infusion for each daily dose were studied. We measured fosfomycin concentrations (by liquid chromatography-tandem mass spectrometry), the total bacterial burden, and the burden of less susceptible isolates. We applied a mathematical model to all the data simultaneously. There was a rapid emergence of resistance with all doses and schedules. Prior to resistance emergence, an initial kill of 2 to 3 log
(CFU/ml) was observed. The model demonstrated that the area under the concentration-time curve/MIC ratio was linked to total bacterial kill, while the time that the concentration remained above the MIC (or, equivalently, the minimum concentration/MIC ratio) was linked to resistance suppression. These findings were also seen in other investigations with
(
systems) and
(murine system). We conclude that for serious infections with high bacterial burdens, fosfomycin may be of value as a new therapeutic and may be optimized by administering the agent as a continuous or prolonged infusion or by use of a short dosing interval. For indications such as ventilator-associated bacterial pneumonia, it may be prudent to administer fosfomycin as part of a combination regimen.
Determination of the susceptibility breakpoint for antibiotics is important, as it guides the use of agents in the clinical setting. Currently, breakpoints are often evaluated using a Probability of ...Target Attainment Analysis in which the targets are set through pre-clinical experiments, often by examining a strain of a target pathogen in a murine model such as a neutropenic thigh infection model. However, regulatory authorities are often rightly concerned about the setting of breakpoints when a number of isolates of target pathogens are evaluated and there is a sizeable spread of the drug exposures necessary to achieve the target with a sufficiently high (usually 90%) probability. Here, we propose a method for supporting a breakpoint determination for this circumstance. We examined 8 isolates of resistant Enterobacteriaceae in a neutropenic murine thigh infection model. The stasis exposure was determined and ranged from 5.70 to 43.5 AUC/MIC Ratio. The mean ± standard deviation was 20.05 ± 13.05. A 5000-iterate Monte Carlo simulation was performed to generate a range of stasis targets and Probability of Target Attainment Analyses were calculated at the 1st, 5th, 10th, 25th, 50th, 75th, 90th, 95th, and 99th percentiles of the distribution. Breakpoints were determined at each percentile. Breakpoints ranged from 2 mg/L to 32 mg/L. A weighted (by the percentages of the distribution) breakpoint was calculated and determined to be 4 mg/L. This method is a rational approach to identifying breakpoints when there is substantial between-isolate variability in exposure targets.
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Dose range studies for polymyxin B (PMB) regimens of 0.75 to 12 mg/kg given every 12 h (q12h) were evaluated for bacterial killing and resistance prevention against an AmpC-overexpressing Pseudomonas ...aeruginosa and a
-harboring Klebsiella pneumoniae in 10-day
hollow-fiber models. An exposure-response was observed. But all regimens failed due to regrowth. Lower-dose regimens amplified isolates that expressed transient, lower-level adaptive resistance to PMB (MICs ≤ 4 mg/liter). Higher PMB dosages amplified isolates that expressed this resistance mechanism, a higher-MIC "moderately stable" adaptive resistance, and a higher-MIC stable resistance to PMB. Failure of the highest dose regimens was solely due to subpopulations that expressed the two higher-level resistances. Total and bioactive PMB concentrations in broth declined below targeted PK profiles within hours of treatment initiation and prior to bacterial regrowth. With treatment failure, the total PMB measured in bacteria was substantially higher than in broth. But the bioactive PMB in broth and bacteria were low to nondetectable. Together, these findings suggest a sequence of events for treatment failure of the clinical regimen. First, PMB concentrations in broth are diluted as PMB binds to bacteria, resulting in total and bioactive PMB in broth that is lower than targeted. Bacterial regrowth and treatment failure follow, with emergence of subpopulations that express transient lower-level adaptive resistance to PMB and possibly higher-level adaptive and stable resistances. Higher-dose PMB regimens can prevent the emergence of transient lower-level adaptive resistance, but they do not prevent treatment failure due to isolates that express higher-level resistance mechanisms.
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Because of our current crisis of resistance, particularly in nosocomial pathogens, the discovery and development of new antimicrobial agents has become a societal imperative. Changes ...in regulatory pathways by the Food and Drug Administration and the European Medicines Agency place great emphasis on the use of preclinical models coupled with pharmacokinetic/pharmacodynamic analysis to rapidly and safely move new molecular entities with activity against multi-resistant pathogens through the approval process and into the treatment of patients. In this manuscript, the use of the murine pneumonia system and the Hollow Fiber Infection Model is displayed and the way in which the mathematical analysis of the data arising from these models contributes to the robust choice of dose and schedule for Phase 3 clinical trials is shown. These data and their proper analysis act to de-risk the conduct of Phase 3 trials for anti-infective agents. These trials are the most expensive part of drug development. Further, given the seriousness of the infections treated, they represent the riskiest element for patients. Consequently, these preclinical model systems and their proper analysis have become a central part of accelerated anti-infective development. A final contention of this manuscript is that it is possible to embed these models and in particular, the Hollow Fiber Infection Model earlier in the drug discovery/development process. Examples of ‘dynamic driver switching’ and the impact of this phenomenon on clinical trial outcome are provided. Identifying dynamic drivers early in drug discovery may lead to improved decision making in the lead optimization process, resulting in the best molecules transitioning to clinical development.
Treating high-density bacterial infections is a challenging clinical problem. We have a paucity of new agents that can address this problem.
is a particularly difficult pathogen to treat effectively ...because of the plethora of resistance mechanisms it carries. Fosfomycin is an agent discovered circa 40 years ago. Recently, it has been resurrected in the United States and studied for intravenous therapy. We hypothesized that, to maximize its utility, it would require combination chemotherapy when used in a clinical circumstance in high-bacterial-burden infections. We chose to examine the combination of meropenem plus fosfomycin. These agents were studied in the hollow-fiber infection model. We utilized a fully factorial study design, looking at 2 doses of meropenem alone (1 and 2 g 8-hourly) and two doses of fosfomycin alone (6 and 8 g 8-hourly), as well as all possible combinations plus a no-treatment control. We used a high-dimensional model of 5 inhomogeneous differential equations with 5 system outputs to analyze all data simultaneously. Combination therapy outperformed all monotherapy regimens, with all combinations driving >6 log
CFU/ml of bacterial killing. Combination therapy was able to counterselect resistance emergence (meropenem mutants being killed by the combination, as well as fosfomycin mutants being killed by the combination) in all regimens studied. The analysis demonstrated that the combination was significantly synergistic for bacterial cell killing and resistance suppression. Meropenem plus fosfomycin is a promising combination for therapy of high-burden
infections and requires further study.
Multidrug therapy is often required. Examples include antiviral therapy, nosocomial infections, and, most commonly, anti-
therapy. Our laboratory previously identified a mathematical approach to ...identify 2-drug regimens with a synergistic or additive interaction using a full factorial study design. Our objective here was to generate a method to identify an optimal 3-drug therapy. We studied
isolate H37Rv in log-phase growth in flasks. Pretomanid and moxifloxacin were chosen as the base 2-drug regimen. Bedaquiline (plus M2 metabolite) was chosen as the third drug for evaluation. Total bacterial burden and bacterial burden less-susceptible to study drugs were enumerated. A large mathematical model was fit to all the data. This allowed extension to evaluation of the 3-drug regimen by employing a Monte Carlo simulation. Pretomanid plus moxifloxacin demonstrated excellent bacterial kill and suppressed amplification of less-susceptible pathogens. Total bacterial burden was driven to extinction in 3 weeks in 6 of 9 combination therapy evaluations. Only the lowest pretomanid/moxifloxacin exposures in combination did not extinguish the bacterial burden. No combination regimen allowed resistance amplification. Generation of 95% credible intervals about estimates of the interaction parameters α (α
, α
, and α
) by bootstrapping showed the interaction was near synergistic. The addition of bedaquiline/M2 metabolite was evaluated by forming a 95% confidence interval regarding the decline in bacterial burden. The addition of bedaquiline/M2 metabolite shortened the time to eradication by 1 week and was significantly different. A model-based system approach to evaluating combinations of 3 agents shows promise to rapidly identify the most promising combinations that can then be trialed.
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