Elucidation of the pharmacokinetic/pharmacodynamic determinants of fosfomycin activity against Pseudomonas aeruginosa using a dynamic in vitro model

Elucidation of the pharmacokinetic/pharmacodynamic determinants of fosfomycin activity against... Abstract Objectives To identify the fosfomycin pharmacokinetic (PK)/pharmacodynamic (PD) index (fT>MIC, fAUC/MIC or fCmax/MIC) most closely correlated with activity against Pseudomonas aeruginosa and determine the PK/PD target associated with various extents of bacterial killing and the prevention of emergence of resistance. Methods Dose fractionation was conducted over 24 h in a dynamic one-compartment in vitro PK/PD model utilizing P. aeruginosa ATCC 27853 and two MDR clinical isolates (CR 1005 and CW 7). In total, 35 different dosing regimens were examined across the three strains. Microbiological response was examined by log changes and population analysis profiles. A Hill-type Emax model was fitted to the killing effect data (expressed as the log10 ratio of the area under the cfu/mL curve for treated regimens versus controls). Results Bacterial killing of no more than ∼3 log10 cfu/mL was achieved irrespective of regimen. The fAUC/MIC was the PK/PD index most closely correlated with efficacy (R2 = 0.80). The fAUC/MIC targets required to achieve 1 and 2 log10 reductions in the area under the cfu/mL curve relative to growth control were 489 and 1024, respectively. No regimen was able to suppress the emergence of resistance, and near-complete replacement of susceptible with resistant subpopulations occurred with virtually all regimens. Conclusions Bacterial killing for fosfomycin against P. aeruginosa was most closely associated with the fAUC/MIC. Suppression of fosfomycin-resistant subpopulations could not be achieved even with fosfomycin exposures well above those that can be safely achieved clinically. Introduction Effective treatment of infections caused by MDR Gram-negative pathogens such as Pseudomonas aeruginosa is a major medical challenge.1–3,P. aeruginosa, previously identified by the IDSA as one of the top six pathogens threatening healthcare systems,4,5 has now been categorized as a ‘Serious’ threat level by the US CDC.6 With numerous intrinsic and acquired resistance mechanisms present in this organism,7 antibiotic resistance across all P. aeruginosa infections emerges during therapy in up to 25% of cases and is associated with treatment failure in 50%–85% of patients and greater risk of mortality.8,9 With a shortage of new antibiotics with novel mechanisms of action in the drug discovery and development pipeline,10 there is a growing need to optimize the use of older ‘forgotten’ antibiotics11 to treat infections, including those caused by P. aeruginosa.12 Fosfomycin is an older antibiotic exhibiting activity against many Gram-negative pathogens, including a significant subset of MDR P. aeruginosa strains.13–15 Given that it is generally well tolerated,16 fosfomycin has been suggested as a promising agent for managing infections caused by Gram-negative bacilli that are resistant to commonly used antibiotics.17 Unfortunately the development of fosfomycin (first isolated from Streptomyces species in 1969)18 occurred when drug development was conducted more or less on a trial-and-error basis.19 Consequently, there is a dearth of knowledge on the pharmacokinetic (PK) and pharmacodynamic (PD) properties of fosfomycin required to optimize therapy.20 This lack of established regimens specifically for complicated infections is a primary limitation to the use of fosfomycin and carries significant risks for patient outcomes, adverse events and resistance emergence.13,21 It has been recommended that exposure–response relationships for older antimicrobials, including fosfomycin, be urgently established.17,20 The determination of the relationship between bacterial killing and emergence of resistance with respect to PK/PD indices and the determination of PK/PD targets will assist in the design of rational dosing strategies for fosfomycin. Therefore, we utilized an in vitro PK/PD model (i) to identify the PK/PD index [i.e. the cumulative percentage of a 24 h period for which unbound concentrations exceed the MIC (fT>MIC), the area under the unbound concentration–time curve to MIC ratio (fAUC/MIC) or the unbound maximal concentration to MIC ratio (fCmax/MIC)] that best predicts bacterial killing of fosfomycin against P. aeruginosa; and (ii) to determine the magnitude of the predictive PK/PD index required to achieve various extents of bacterial killing and/or prevent the emergence or amplification of fosfomycin-resistant mutants. Materials and methods Antibiotics, bacterial isolates and MIC testing Fosfomycin disodium (Lot 20131012, Waterstone Technology, Carmel, IN, USA) and glucose-6-phosphate (G6P; Lot SLBD7775V, Sigma-Aldrich, Castle Hill, NSW, Australia) were supplied by their respective manufacturers. Sterile stock solutions were prepared in Milli-Q water immediately prior to each experiment. Cation-adjusted Mueller–Hinton agar and CAMHB supplemented with 25 mg/L G6P per CLSI guidelines were used in all experiments.22 Three fosfomycin-susceptible strains of P. aeruginosa were examined: reference strain ATCC 27853 (ATCC, Manassas, VA, USA) and two previously described MDR clinical isolates [CR 1005 (non-mucoid) and CW 7 (mucoid)].23 MDR was defined as non-susceptibility to at least one antimicrobial agent in three or more antimicrobial categories.24 The MICs, determined in duplicate on separate days using agar dilution per CLSI guidelines,22 were 8 mg/L for ATCC 27853, 32 mg/L for CR 1005 and 16 mg/L for CW 7. As breakpoints for fosfomycin against Pseudomonas spp. are currently lacking, we applied modified CLSI breakpoints for Escherichia coli with an MIC ≤64 mg/L considered susceptible and >64 mg/L resistant.22 Population analysis profiles The possible presence of fosfomycin-resistant subpopulations within the predominant (susceptible) population at baseline was determined via population analysis profiles (PAPs) (inoculum ∼108 cfu/mL) for each strain as described previously.23 Fosfomycin heteroresistance was defined as the presence within a fosfomycin-susceptible isolate (i.e. MIC ≤64 mg/L) of subpopulations able to grow on agar containing >64 mg/L fosfomycin. Random colonies were selected from fosfomycin-containing agar plates for repeated MIC testing to confirm the increased MICs. Dynamic in vitro PK/PD model, fosfomycin dosing regimens and emergence of resistance A previously described dynamic in vitro PK/PD model25 was used over 24 h to examine the PK/PD index that best predicts the antimicrobial response of fosfomycin. Prior to each experiment, strains were subcultured onto Mueller–Hinton agar (Media Preparation Unit) and incubated overnight at 35°C. One colony was then selected and grown overnight in 10 mL of CAMHB from which early log-phase growth was obtained. A 1 mL aliquot was then injected into each central compartment to yield a starting inoculum of ∼106 cfu/mL. Both continuous infusion and intermittent dosing regimens were simulated as described previously,25 with serial samples for viable cell counting and determination of fosfomycin concentrations collected aseptically as shown in Table 1. For intermittent regimens an elimination half-life (t½) of 4 h was simulated, approximating fosfomycin elimination in critically ill patients26,27 and healthy volunteers.28,29 Given that fosfomycin has negligible plasma protein binding,30,31 concentrations were assumed to constitute unbound fosfomycin. Viability counting was undertaken as previously described23 and antibiotic carryover minimized by centrifuging all samples for 5 min at 10 000 rpm with resuspension in prewarmed saline (37°C). To additionally examine the presence of fosfomycin-resistant subpopulations at baseline (0 h) and following 24 h of treatment, PAPs were conducted on all isolates for a subset of experiments at these times on Mueller–Hinton agar containing G6P (25 mg/L) and fosfomycin at 32, 64, 128 and 256 mg/L. Table 1. Fosfomycin dosing regimens and sampling times in the in vitro PK/PD modela,b Dosing regimen 8 h 12 h 24 h CC Target fCmax (mg/L)  ATCC 27853 250, 125, 75, 50, 12.5, 6.25 2500, 1500, 1125, 1000, 750, 425, 250, 63, 32 3000, 2000, 1300, 1000e, 750, 500e, 250e, 125e, 63e, 16e 50, 25  CR 1005 250, 125, 75, 50, 25, 12.5 750, 500, 63, 32, 16, 8 3000, 2500, 2000, 1500, 750, 500, 250, 63, 32 500, 250, 50, 25  CW 7 250, 125, 75, 50, 12.5, 6.25 500, 63, 32, 16 3000, 2500, 2000, 1500, 500, 250, 63, 32 500, 250, 50, 25 Sampling times (h) for  microbiological measurementsc 0, 1, 3, 5, 8, 16, 24 0, 1, 3, 5, 8, 12, 24 0, 1, 3, 5, 8, 24 0, 1, 3, 5, 8, 24  fosfomycin quantificationc,d 0, 4, 8, 9, 12, 13, 16, 17, 24 0, 4, 8, 12, 13, 24 0, 4, 8, 24 0, 4, 8, 24 Dosing regimen 8 h 12 h 24 h CC Target fCmax (mg/L)  ATCC 27853 250, 125, 75, 50, 12.5, 6.25 2500, 1500, 1125, 1000, 750, 425, 250, 63, 32 3000, 2000, 1300, 1000e, 750, 500e, 250e, 125e, 63e, 16e 50, 25  CR 1005 250, 125, 75, 50, 25, 12.5 750, 500, 63, 32, 16, 8 3000, 2500, 2000, 1500, 750, 500, 250, 63, 32 500, 250, 50, 25  CW 7 250, 125, 75, 50, 12.5, 6.25 500, 63, 32, 16 3000, 2500, 2000, 1500, 500, 250, 63, 32 500, 250, 50, 25 Sampling times (h) for  microbiological measurementsc 0, 1, 3, 5, 8, 16, 24 0, 1, 3, 5, 8, 12, 24 0, 1, 3, 5, 8, 24 0, 1, 3, 5, 8, 24  fosfomycin quantificationc,d 0, 4, 8, 9, 12, 13, 16, 17, 24 0, 4, 8, 12, 13, 24 0, 4, 8, 24 0, 4, 8, 24 a Dosing regimens involved intermittent administration at 8, 12 or 24 h to achieve the target steady-state fCmax or CC simulating continuous infusion. b Fosfomycin MICs were 8 mg/L for ATCC 27853, 32 mg/L for CR 1005 and 16 mg/L for CW 7. c Initial experiments with multiple-dose regimens (dosing every 8 and 12 h) at high concentrations showed no further bacterial killing at later timepoints (12 and 16 h). Consequently, for subsequent experiments sampling was conducted up to 8 h and then at 24 h. d A subset of each dosing regimen (8 h, 12 h, 24 h and CC) was assayed to determine fosfomycin concentrations. e Results from a previous study.23 Table 1. Fosfomycin dosing regimens and sampling times in the in vitro PK/PD modela,b Dosing regimen 8 h 12 h 24 h CC Target fCmax (mg/L)  ATCC 27853 250, 125, 75, 50, 12.5, 6.25 2500, 1500, 1125, 1000, 750, 425, 250, 63, 32 3000, 2000, 1300, 1000e, 750, 500e, 250e, 125e, 63e, 16e 50, 25  CR 1005 250, 125, 75, 50, 25, 12.5 750, 500, 63, 32, 16, 8 3000, 2500, 2000, 1500, 750, 500, 250, 63, 32 500, 250, 50, 25  CW 7 250, 125, 75, 50, 12.5, 6.25 500, 63, 32, 16 3000, 2500, 2000, 1500, 500, 250, 63, 32 500, 250, 50, 25 Sampling times (h) for  microbiological measurementsc 0, 1, 3, 5, 8, 16, 24 0, 1, 3, 5, 8, 12, 24 0, 1, 3, 5, 8, 24 0, 1, 3, 5, 8, 24  fosfomycin quantificationc,d 0, 4, 8, 9, 12, 13, 16, 17, 24 0, 4, 8, 12, 13, 24 0, 4, 8, 24 0, 4, 8, 24 Dosing regimen 8 h 12 h 24 h CC Target fCmax (mg/L)  ATCC 27853 250, 125, 75, 50, 12.5, 6.25 2500, 1500, 1125, 1000, 750, 425, 250, 63, 32 3000, 2000, 1300, 1000e, 750, 500e, 250e, 125e, 63e, 16e 50, 25  CR 1005 250, 125, 75, 50, 25, 12.5 750, 500, 63, 32, 16, 8 3000, 2500, 2000, 1500, 750, 500, 250, 63, 32 500, 250, 50, 25  CW 7 250, 125, 75, 50, 12.5, 6.25 500, 63, 32, 16 3000, 2500, 2000, 1500, 500, 250, 63, 32 500, 250, 50, 25 Sampling times (h) for  microbiological measurementsc 0, 1, 3, 5, 8, 16, 24 0, 1, 3, 5, 8, 12, 24 0, 1, 3, 5, 8, 24 0, 1, 3, 5, 8, 24  fosfomycin quantificationc,d 0, 4, 8, 9, 12, 13, 16, 17, 24 0, 4, 8, 12, 13, 24 0, 4, 8, 24 0, 4, 8, 24 a Dosing regimens involved intermittent administration at 8, 12 or 24 h to achieve the target steady-state fCmax or CC simulating continuous infusion. b Fosfomycin MICs were 8 mg/L for ATCC 27853, 32 mg/L for CR 1005 and 16 mg/L for CW 7. c Initial experiments with multiple-dose regimens (dosing every 8 and 12 h) at high concentrations showed no further bacterial killing at later timepoints (12 and 16 h). Consequently, for subsequent experiments sampling was conducted up to 8 h and then at 24 h. d A subset of each dosing regimen (8 h, 12 h, 24 h and CC) was assayed to determine fosfomycin concentrations. e Results from a previous study.23 Three intermittent dosing intervals (8, 12 and 24 h) with fCmax varied across each schedule plus constant concentration (CC) regimens were examined (Table 1). Dosing regimens were selected to maximally differentiate among the PK/PD indices under investigation (fAUC/MIC, fCmax/MIC and fT>MIC) and included a wide concentration range to allow exploration of the complete dose–response relationship from essentially no effect to maximum effect. Fosfomycin concentrations were determined using a previously published LC-MS/MS assay with minor modification.32 The assay range was 1–500 mg/L; samples were diluted if the expected fosfomycin concentrations were higher than the upper limit of quantification. Investigation of PK/PD indices For each dosing regimen the %fT>MIC, fAUC/MIC, fCmax/MIC and the area under the killing curve (AUCcfu) of the time-course profile of bacterial numbers (cfu/mL from 0 to 24 h) were determined as described previously at both 1× and 10× MIC.25 The log ratio area method, which mostly compensates for the bacterial loss from the model,33 was used to quantify the killing effect (drug effect) chosen as the measure of efficacy (E) per the equation: E = log10[AUCcfu(treatment)/AUCcfu(growth control)]. The relationship between killing effect (E) and each PK/PD index was analysed as described previously using a Hill equation with a baseline and an inhibitory effect, with the magnitude of the most predictive PK/PD index required to achieve 1 or 2 log10 reduction in the area under the cfu/mL curve relative to growth control estimated from the E0, Emax, EI50 and γ.25 Results Baseline PAPs Baseline PAPs are shown in Figure 1. Despite all strains being considered fosfomycin susceptible based on MICs (MICs of 8, 16 and 32 mg/L), growth occurred on all PAP plates up to and including 256 mg/L. Colonies obtained from plates containing fosfomycin at 128 and 256 mg/L had elevated MICs (≥128 mg/L for ATCC 27853 and ≥256 mg/L for CR 1005 and CW 7), indicating that resistant subpopulations were present in all strains prior to treatment. The proportion of bacterial colonies growing on plates containing fosfomycin at 128 mg/L were 4.20 × 10−6, 1.87 × 10−5 and 2.57 × 10−6 for ATCC 27853, CR 1005 and CW 7, respectively; a similar proportion of subpopulations grew in the presence of 256 mg/L. Figure 1. View largeDownload slide Baseline PAPs of reference strain ATCC 27853 and two clinical isolates. All strains were considered susceptible based on MIC determinations (MICs of 8, 32 and 16 mg/L). Figure 1. View largeDownload slide Baseline PAPs of reference strain ATCC 27853 and two clinical isolates. All strains were considered susceptible based on MIC determinations (MICs of 8, 32 and 16 mg/L). Quantification of fosfomycin concentrations, bacterial killing and emergence of resistance Observed fosfomycin concentrations were on average within 15% of those targeted. Typical profiles showing the relationship between targeted and observed concentrations are shown in Figure 2. Representative time-course profiles of bacterial numbers for each isolate, including the PAPs, are presented in Figure 3. The initial inocula in the control and treatment compartments (mean ± SD) were: 6.03 (n = 2) and 5.91 ± 0.24 (n = 27) log10 cfu/mL for ATCC 27853, 6.07 ± 0.30 (n = 3) and 6.34 ± 0.18 (n = 25) log10 cfu/mL for CR 1005, and 6.35 ± 0.12 (n = 4) and 6.01 ± 0.15 (n = 30) log10 cfu/mL for CW 7. After 24 h, bacterial numbers in the control compartments had increased to 8.1 (n = 2), 8.15 ± 0.26 (n = 3) and 8.30 ± 0.27 (n = 4) log10 cfu/mL for ATCC 27853, CR 1005 and CW 7, respectively. Figure 2. View largeDownload slide Typical simulated PK profiles showing the relationship between targeted and achieved fosfomycin concentrations in the PK/PD model. Figure 2. View largeDownload slide Typical simulated PK profiles showing the relationship between targeted and achieved fosfomycin concentrations in the PK/PD model. Figure 3. View largeDownload slide Left-hand panels: representative microbiological responses observed in the in vitro PK/PD model simulating the fosfomycin PK of different dosing regimens using ATCC 27853, CR 1005 and CW 7. Right-hand panels: PAPs at baseline (0 h) and after 24 h of exposure to fosfomycin at an initial inoculum of ∼106 cfu/mL. Figure 3. View largeDownload slide Left-hand panels: representative microbiological responses observed in the in vitro PK/PD model simulating the fosfomycin PK of different dosing regimens using ATCC 27853, CR 1005 and CW 7. Right-hand panels: PAPs at baseline (0 h) and after 24 h of exposure to fosfomycin at an initial inoculum of ∼106 cfu/mL. The rate of initial bacterial killing against each isolate generally increased with increasing fosfomycin concentrations up to ∼10× MIC; further increases did not produce more rapid or extensive killing. With the majority of fosfomycin regimens, initial killing of no more than ∼3 log10 cfu/mL occurred across the first 4–8 h for all isolates followed by regrowth close to control values at 24 h. In a small number of cases with very high-dose regimens [e.g. fCmax of 750 mg/L and 1500 mg/L every 12 h against ATCC 27853 (Figure 3, left-hand panel)], regrowth remained below the initial inoculum at 24 h. Maximum bacterial killing achieved against ATCC 27853 was 3.0 log10 cfu/mL using an fCmax of 1500 mg/L administered every 12 h. The equivalent values and regimens for CR 1005 and CW 7 were 3.1 log10 cfu/mL with an fCmax of 750 mg/L every 12 h and 3.2 log10 cfu/mL with two regimens, fCmax of 1500 mg/L every 12 h and 500 mg/L as a CC, respectively. For the subset of experiments that included PAPs, no fosfomycin-resistant colonies for any strain were detected immediately prior to the commencement of therapy at the starting inoculum of ∼106 cfu/mL (Figure 3, right-hand panels). For the growth controls, PAPs following 24 h of incubation indicated the presence of resistant subpopulations in all three strains; growth at this time was ∼108–8.5 cfu/mL. The proportion of resistant colonies growing on plates containing fosfomycin at 128 mg/L at 24 h was 1.87 × 10−6, 1.02 × 10−4 and 1.81 × 10−6 for ATCC 27853, CR 1005 and CW 7, respectively. These proportions were similar to those observed with the baseline PAPs (inoculum ∼108 cfu/mL). With the exception of the fCmax 32 mg/L 12 h regimen against CW 7 (in which the proportion of resistant colonies at 24 h was 3.33 × 10−4), with all other regimens in which PAPs were performed virtually the entire population at 24 h grew in the presence of fosfomycin at 256 mg/L (Figure 3, right-hand panels). Relationships between bacterial killing and PK/PD indices The relationships between killing effect and fAUC/MIC, fCmax/MIC and fT>MIC are shown in Figure 4. At 1× and 10 × MIC the PK/PD index that best predicted efficacy was fAUC/MIC (R2 = 0.80; Figure 4, top row). A poorer relationship existed between the killing effect and fCmax/MIC, for which greater scatter and systemic deviations from the curve fit were observed (R2 = 0.71; Figure 4, middle row). No relationship was observed for fT>MIC at 1× MIC (Figure 4c), but one was found at 10 × MIC (R2 = 0.70; Figure 4f). The magnitudes of the fAUC/MIC indexes required for 1 and 2 log10 reduction in the area under the cfu/mL curve relative to growth control for each strain were 489 and 1024, respectively. Figure 4. View largeDownload slide Relationship between the killing effect of fosfomycin against P. aeruginosa ATCC 27853 (open circles), CR 1005 (open squares) and CW 7 (open triangles) as a function of three PK/PD indices (calculated at 1× and 10× MIC): fAUC/MIC, fCmax/MIC and fT>MIC. Each data point represents the result from a single treatment run in the dynamic in vitro PK/PD model. Figure 4. View largeDownload slide Relationship between the killing effect of fosfomycin against P. aeruginosa ATCC 27853 (open circles), CR 1005 (open squares) and CW 7 (open triangles) as a function of three PK/PD indices (calculated at 1× and 10× MIC): fAUC/MIC, fCmax/MIC and fT>MIC. Each data point represents the result from a single treatment run in the dynamic in vitro PK/PD model. Discussion Oral fosfomycin (fosfomycin tromethamine) is currently indicated for treatment of uncomplicated urinary tract infections caused by E. coli and Enterococcus faecalis in women.34 However, the parenteral (disodium) formulation is increasingly used to treat systemic infections caused by MDR organisms, including P.aeruginosa.35–37 Unfortunately, the information required to optimize dosing regimens using exposure–response relationships is not available. It has therefore been suggested that establishing the exposure–response relationships for fosfomycin for both efficacy and resistance selection—which are often distinctly different—be made a priority.20 We sought to determine the predictive performance of potential PK/PD indices with respect to bacterial killing and the emergence of resistance against P. aeruginosa, including MDR isolates. We have previously reported maximal bacterial killing of ∼3 log10 cfu/mL followed by rapid regrowth against P. aeruginosa ATCC 27853 in a 24 h PK/PD model using once-daily dosing (fCmax, 1000 mg/L).23 Similar maximal killing was recently shown for the same strain using static time–kill studies (Cmax, 128 mg/L) and a tissue-cage infection model.38 This maximal level of killing is almost identical to that achieved here against the same reference strain and two additional MDR clinical isolates with dosing regimens providing a much greater exposure to fosfomycin (e.g. fCmax 1000 mg/L every 12 h or fCmax 3000 mg/L every 24 h). Importantly, near-complete replacement of susceptible with resistant subpopulations occurred with virtually all regimens. Although fosfomycin-resistant colonies were not detected immediately prior to commencement of therapy in the dose-fractionation studies (inoculum ∼106 cfu/mL), ∼2–3 log10 cfu/mL of resistant colonies growing on agar containing 256 mg/L fosfomycin were present in the baseline PAPs (inoculum ∼108 cfu/mL). Thus, it is highly likely that resistant subpopulations were present at the commencement of therapy in the dose-fractionation studies but were simply not detected at the lower inoculum. The rapid regrowth observed following commencement of fosfomycin administration was driven, at least in part, by amplification of these pre-existing, highly fosfomycin-resistant subpopulations. This is similar to what we observed previously against P. aeruginosa at much lower fosfomycin exposures [maximum AUC0–24 of 5680, 2840 mg·h/L (fCmax of 1000 and 500 mg/L administered every 24 h)].23 However, even an AUC0–24 of 25 247 mg·h/L (fCmax of 2500 mg/L administered every 12 h) in the present study could not suppress the emergence of resistance; this is much greater than achieved in patients with standard dosing regimens (typically 4–8 g intravenously every 8 h for serious systemic infections) in which fCmax typically ranges from 400 to 1000 mg/L.26,31,32,39 Very few studies have previously examined the emergence of fosfomycin resistance. Using a hollow-fibre infection model (half-life, 4 h; initial inoculum, ∼1 × 106 cfu/mL) and a single clinical isolate of E. coli, Docobo-Pérez et al.40 simulated human-like concentration–time profiles corresponding to fosfomycin regimens of 4, 5, 6 and 8 g every 8 h, with each dose infused over 1 h, or 24 g every 24 h administered as a single bolus. For the two 24 g/day regimens (administered once daily or as divided doses) no viable bacteria were detected at 40 h. For all other regimens, rapid regrowth with amplification of fosfomycin-resistant subpopulations occurred such that by ∼64 h the entire population grew on agar containing fosfomycin at 256 mg/L. These results indicate that at least for this single isolate of E. coli resistance suppression is achievable. Given that both the 8 g/8 h and 24 g/24 h regimens eradicated the entire population, the authors concluded that the fAUC/MIC was the dynamic index best linked to resistance suppression. VanScoy et al.41 were similarly able to suppress bacterial regrowth and the emergence of fosfomycin-resistant subpopulations of a heteroresistant E. coli reference strain with regimens containing ≥1 g of fosfomycin administered every 6 h. However, even with these dosing regimens the total population was not eradicated. With regimens containing ≤0.5 g administered every 6 h, rapid bacterial regrowth with amplification of fosfomycin-resistant subpopulations occurred such that the latter completely replaced the total population. They obtained similar results against the same strain in dose-fractionation studies (discussed below) in which emergence of resistant subpopulations, often completely dominating the total population, occurred with lower-dose regimens but was suppressed or even eliminated completely with higher-dose regimens. The relationship between fosfomycin dose and the emergence of resistant subpopulations matched an inverted-U-shaped function, described previously with other antibiotics, including against P. aeruginosa.42,43 Using single reference strains of E. coli and P. aeruginosa (ATCC 27853), Pan et al.38 reported selective enrichment of resistant subpopulations (growing on agar containing fosfomycin at 4, 8 and 16× MIC) for both isolates across a specific concentration range, but no development of fosfomycin resistance at a higher concentration. For P. aeruginosa, enrichment occurred with concentrations of 16–64 mg/L for time–kill studies, with resistance suppression occurring at 128 mg/L; a similar result was achieved with in vivo tissue-cage experiments (24 h dosing with a maximum achieved concentration of ∼300 mg/L). To the best of our knowledge this is the only report indicating suppression of resistance against P. aeruginosa with fosfomycin monotherapy. This is an interesting and unexplained result given the extremely high initial inoculum (∼109 cfu/mL). We have previously shown in static time–kill studies a pronounced inoculum effect for fosfomycin against three strains of P. aeruginosa, including ATCC 27853, with bacterial killing essentially eliminated at an inoculum of ∼108 cfu/mL across a concentration range of 1–1024 mg/L; highly resistant subpopulations were enriched with all but the lowest concentrations used.23 Given our previous observations of a near-complete lack of activity with monotherapy at a high inoculum, we chose a lower inoculum (∼106 cfu/mL) for the present study. However, extremely high exposures in the present study (up to an fCmax of 3000 mg/L) with a lower starting inoculum were similarly unable to suppress amplification of resistant subpopulations, even with the loss of some bacteria from the system; bacterial loss is a limitation of one-compartment models. This situation would only be made worse if a shorter half-life, which would reduce bacterial killing even further, were to be used; half-lives of 2–3 h have been reported in some critically ill patients.44,45 Regardless of resistance emergence, absolute bacterial numbers in the study by Pan et al.38 never dropped below ∼5–6 log10 cfu/mL. That study notwithstanding, although increasing fosfomycin exposures may prevent or limit the emergence of resistance against other organisms such as E. coli, such a relationship does not appear to exist against P. aeruginosa. Indeed, we previously found that all of the 14 P. aeruginosa isolates examined (MIC range: 1–64 mg/L) contained resistant subpopulations,23 and that only moderate bacterial killing is achievable even with supra-therapeutic exposures (maximum killing of ∼3 log10 cfu/mL). Therefore, against P. aeruginosa, treatment failure with fosfomycin monotherapy would appear likely even considering the potential added effect of the immune system,46 with monotherapy regimens serving only to amplify pre-existing and highly resistant subpopulations. This situation is compounded by the fact that resistance to fosfomycin in P. aeruginosa appears to come with no apparent fitness cost.14,47,48 The difference in resistance suppression between P. aeruginosa and E. coli may be due to differences in the transport systems required for fosfomycin entry into the cells. E. coli contains two transport systems, the glycerol-3-phosphate (GlpT) and a hexose phosphate (UhpT), whereas P. aeruginosa contains only GlpT.49,50 Thus only a single mutation is required in P. aeruginosa to prevent fosfomycin entry and render the organism resistant, whereas in E. coli two mutations would be required.47,48,51–53 Only two previous studies have purported to examine the exposure–response relationships for bacterial killing of fosfomycin against any organisms. VanScoy et al.41 used a one-compartment PK/PD model similar to ours to examine bacterial killing and resistance emergence against one reference strain and two clinical isolates of E. coli. Experiments were conducted over 24 h (starting inoculum ∼1 × 106 cfu/mL) and simulated a fosfomycin half-life of 2 h. Three regimens with intermittent administration every 6, 8 and 12 h, as well as a continuous-infusion regimen, were examined, with each providing the same total daily fosfomycin exposure (as measured by the AUC0–24). The authors concluded that fosfomycin activity was most likely linked to fAUC/MIC (R2 = 0.76), although there was also a strong correlation with fCmax/MIC (R2 = 0.62); there was a poor relationship between bacterial killing and fT>MIC (R2 = 0.42). However, it was noted that given the majority of fT>MIC values were 100%, the PK/PD relationship based on this index could not be adequately explored. Lepak et al.54 used the neutropenic murine thigh infection model to examine the PK/PD activity of fosfomycin against five strains of E. coli, three of Klebsiella pneumoniae and two of P. aeruginosa. Although they determined that the PK/PD index best correlated with activity against these organisms was the AUC/MIC (R2 = 0.70; protein binding was not stated), dose-fractionation was only conducted on a single strain of E. coli; for K. pneumoniae and P. aeruginosa, only increasing doses administered every 3 h were used, with the index determined for E. coli assumed to also apply to these organisms. Our dose-fractionation study employed the largest range of fosfomycin concentrations (fCmax range: 6.25–3000 mg/L) and dosing regimens (30 different regimens) used against any organism and is the first to specifically use a dose-fractionation design to examine the PK/PD index driving bacterial activity and the emergence of resistance for fosfomycin against P. aeruginosa. In agreement with the E. coli studies of VanScoy et al.41 and Lepak et al.,54 bacterial killing was most closely correlated with fAUC/MIC. Although we have previously shown using both MDR and non-MDR isolates of P. aeruginosa that bacterial killing by fosfomycin against this organism is time dependent,23 we were unable to find a relationship between activity and fT>1×MIC. This may be explained by a large number of the dosing regimens having a fT>1×MIC of 100%. To account for this we also analysed each index at 10× MIC. Although a relationship was present between activity and fT>10×MIC (Figure 4f), the fAUC/MIC nevertheless remained the index most closely associated with activity. This is the first study to utilize a dose-fractionation design to investigate the relationship between PK/PD indices and bacterial killing for fosfomycin against P. aeruginosa. The fAUC/MIC was most closely correlated with bacterial killing. No fosfomycin exposures, including exposures well above those that are clinically achievable in plasma following intravenous administration, were able to suppress the emergence of resistant subpopulations. Our results suggest that for systemic infections involving P. aeruginosa, fosfomycin monotherapy will be ineffective. Funding This study was supported by a Ramaciotti Establishment Grant provided by the Ramaciotti Foundations and an Australian Society for Antimicrobials Research Grant provided by the Australian Society for Antimicrobials. C. B. L. is the recipient of an Australian National Health and Medical Research Council Career Development Fellowship (APP1062509). A. Y. P was supported by an Australian National Health and Medical Research Council Practitioner Fellowship. Transparency declarations None to declare. References 1 Harris P , Paterson D , Rogers B. Facing the challenge of multidrug-resistant gram-negative bacilli in Australia . Med J Aust 2015 ; 202 : 243 – 7 . Google Scholar CrossRef Search ADS 2 Wilson R , Aksamit T , Aliberti S et al. Challenges in managing Pseudomonas aeruginosa in non-cystic fibrosis bronchiectasis . Respir Med 2016 ; 117 : 179 – 89 . Google Scholar CrossRef Search ADS 3 Berdy J. Thoughts and facts about antibiotics: where we are now and where we are heading . J Antibiot 2012 ; 65 : 385 – 95 . Google Scholar CrossRef Search ADS 4 Boucher HW , Talbot GH , Bradley JS et al. Bad bugs, no drugs: no ESKAPE! An update from the Infectious Diseases Society of America . Clin Infect Dis 2009 ; 48 : 1 – 12 . Google Scholar CrossRef Search ADS 5 Talbot GH , Bradley J , Edwards JE et al. Bad bugs need drugs: an update on the development pipeline from the Antimicrobial Availability Task Force of the Infectious Diseases Society of America . Clin Infect Dis 2006 ; 42 : 657 – 68 . Google Scholar CrossRef Search ADS 6 CDC . Antibiotic/Antimicrobial Resistance: Antimicrobial Resistance Threats in the United States . Atlanta, GA, USA : CDC , 2013 . 7 Driscoll JA , Brody SL , Kollef MH. The epidemiology, pathogenesis and treatment of Pseudomonas aeruginosa infections . Drugs 2007 ; 67 : 351 – 68 . Google Scholar CrossRef Search ADS 8 Carmeli Y , Troillet N , Karchmer AW et al. Health and economic outcomes of antibiotic resistance in Pseudomonas aeruginosa . Arch Intern Med 1999 ; 159 : 1127 – 32 . Google Scholar CrossRef Search ADS 9 Milatovic D , Braveny I. Development of resistance during antibiotic therapy . Eur J Clin Microbiol 1987 ; 6 : 234 – 44 . Google Scholar CrossRef Search ADS 10 Boucher HW , Talbot GH , Benjamin DK Jr et al. 10×'20 Progress—development of new drugs active against Gram-negative bacilli: an update from the Infectious Diseases Society of America . Clin Infect Dis 2013 ; 56 : 1685 – 94 . Google Scholar CrossRef Search ADS 11 Zayyad H , Eliakim-Raz N , Leibovici L et al. Revival of old antibiotics: needs, the state of evidence and expectations . Int J Antimicrob Agents 2017 ; 49 : 536 – 41 . Google Scholar CrossRef Search ADS 12 Taneja N , Kaur H. Insights into newer antimicrobial agents against Gram-negative bacteria . Microbiol Insights 2016 ; 9 : 9 – 19 . 13 Reffert JL , Smith WJ. Fosfomycin for the treatment of resistant gram-negative bacterial infections. Insights from the Society of Infectious Diseases Pharmacists . Pharmacotherapy 2014 ; 34 : 845 – 57 . Google Scholar CrossRef Search ADS 14 Karageorgopoulos DE , Wang R , Yu X-H et al. Fosfomycin: evaluation of the published evidence on the emergence of antimicrobial resistance in Gram-negative pathogens . J Antimicrob Chemother 2012 ; 67 : 255 – 68 . Google Scholar CrossRef Search ADS 15 Hirsch EB , Raux BR , Zucchi PC et al. Activity of fosfomycin and comparison of several susceptibility testing methods against contemporary urine isolates . Int J Antimicrob Agents 2015 ; 46 : 642 – 7 . Google Scholar CrossRef Search ADS 16 Falagas ME , Vouloumanou EK , Samonis G et al. Fosfomycin . Clin Microbiol Rev 2016 ; 29 : 321 – 47 . Google Scholar CrossRef Search ADS 17 Pulcini C , Bush K , Craig WA et al. Forgotten antibiotics: an inventory in Europe, the United States, Canada, and Australia . Clin Infect Dis 2012 ; 54 : 268 – 74 . Google Scholar CrossRef Search ADS 18 Hendlin D , Stapley EO , Jackson M et al. Phosphonomycin, a new antibiotic produced by strains of streptomyces . Science 1969 ; 166 : 122 – 3 . Google Scholar CrossRef Search ADS 19 Podolsky SH. Antibiotics and the social history of the controlled clinical trial, 1950-1970 . J Hist Med Allied Sci 2010 ; 65 : 327 – 67 . Google Scholar CrossRef Search ADS 20 Mouton JW , Ambrose PG , Canton R et al. Conserving antibiotics for the future: new ways to use old and new drugs from a pharmacokinetic and pharmacodynamic perspective . Drug Resist Updat 2011 ; 14 : 107 – 17 . Google Scholar CrossRef Search ADS 21 Theuretzbacher U , Van Bambeke F , Canton R et al. Reviving old antibiotics . J Antimicrob Chemother 2015 ; 70 : 2177 – 81 . Google Scholar CrossRef Search ADS 22 Clinical and Laboratory Standards Institute . Performance Standards for Antimicrobial Susceptibility Testing: Twenty-Fifth Informational Supplement M100-S26 . CLSI, Wayne, PA, USA , 2016 . 23 Walsh CC , McIntosh MP , Peleg AY et al. In vitro pharmacodynamics of fosfomycin against clinical isolates of Pseudomonas aeruginosa . J Antimicrob Chemother 2015 ; 70 : 3042 – 50 . Google Scholar CrossRef Search ADS 24 Magiorakos AP , Srinivasan A , Carey RB et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance . Clin Microbiol Infect 2012 ; 18 : 268 – 81 . Google Scholar CrossRef Search ADS 25 Bergen PJ , Bulitta JB , Forrest A et al. Pharmacokinetic/pharmacodynamic investigation of colistin against Pseudomonas aeruginosa using an in vitro model . Antimicrob Agents Chemother 2010 ; 54 : 3783 . Google Scholar CrossRef Search ADS 26 Pfausler B , Spiss H , Dittrich P et al. Concentrations of fosfomycin in the cerebrospinal fluid of neurointensive care patients with ventriculostomy-associated ventriculitis . J Antimicrob Chemother 2004 ; 53 : 848 – 52 . Google Scholar CrossRef Search ADS 27 Joukhadar C , Klein N , Dittrich P et al. Target site penetration of fosfomycin in critically ill patients . J Antimicrob Chemother 2003 ; 51 : 1247 – 52 . Google Scholar CrossRef Search ADS 28 Schintler MV , Traunmüller F , Metzler J et al. High fosfomycin concentrations in bone and peripheral soft tissue in diabetic patients presenting with bacterial foot infection . J Antimicrob Chemother 2009 ; 64 : 574 – 8 . Google Scholar CrossRef Search ADS 29 Sauermann R , Karch R , Langenberger H et al. Antibiotic abscess penetration: fosfomycin levels measured in pus and simulated concentration-time profiles . Antimicrob Agents Chemother 2005 ; 49 : 4448 – 54 . Google Scholar CrossRef Search ADS 30 Gonzalez D , Schmidt S , Derendorf H. Importance of relating efficacy measures to unbound drug concentrations for anti-infective agents . Clin Microbiol Rev 2013 ; 26 : 274 – 88 . Google Scholar CrossRef Search ADS 31 Roussos N , Karageorgopoulos DE , Samonis G et al. Clinical significance of the pharmacokinetic and pharmacodynamic characteristics of fosfomycin for the treatment of patients with systemic infections . Int J Antimicrob Agents 2009 ; 34 : 506 – 15 . Google Scholar CrossRef Search ADS 32 Parker SL , Frantzeskaki F , Wallis SC et al. Population pharmacokinetics of fosfomycin in critically ill patients . Antimicrob Agents Chemother 2015 ; 59 : 6471 – 6 . Google Scholar CrossRef Search ADS 33 Harigaya Y , Bulitta JB , Forrest A et al. Pharmacodynamics of vancomycin at simulated epithelial lining fluid concentrations against methicillin-resistant Staphylococcus aureus (MRSA): implications for dosing in MRSA pneumonia . Antimicrob Agents Chemother 2009 ; 53 : 3894 – 901 . Google Scholar CrossRef Search ADS 34 Forest Pharmaceuticals Inc . Monurol (Fosfomycin) Package Insert . St Louis, MO, USA : Forest Pharmaceuticals Inc ., 2014 . PubMed PubMed 35 Falagas ME , Roussos N , Gkegkes LD et al. Fosfomycin for the treatment of infections caused by Gram-positive cocci with advanced antimicrobial drug resistance: a review of microbiological, animal and clinical studies . Expert Opin Investig Drugs 2009 ; 18 : 921 – 44 . Google Scholar CrossRef Search ADS 36 Falagas ME , Giannopoulou KP , Kokolakis GN et al. Fosfomycin: use beyond urinary tract and gastrointestinal infections . Clin Infect Dis 2008 ; 46 : 1069 – 77 . Google Scholar CrossRef Search ADS 37 Michalopoulos AS , Livaditis IG , Gougoutas V. The revival of fosfomycin . Int J Infect Dis 2011 ; 15 : e732 – 9 . Google Scholar CrossRef Search ADS 38 Pan A-J , Mei Q , Ye Y et al. Validation of the mutant selection window hypothesis with fosfomycin against Escherichia coli and Pseudomonas aeruginosa: an in vitro and in vivo comparative study . J Antibiot 2017 ; 70 : 166 – 73 . Google Scholar CrossRef Search ADS 39 Traunmuller F , Popovic M , Konz KH et al. A reappraisal of current dosing strategies for intravenous fosfomycin in children and neonates . Clin Pharmacokinet 2011 ; 50 : 493 – 503 . Google Scholar CrossRef Search ADS 40 Docobo-Pérez F , Drusano GL , Johnson A et al. Pharmacodynamics of fosfomycin: insights into clinical use for antimicrobial resistance . Antimicrob Agents Chemother 2015 ; 59 : 5602 – 10 . Google Scholar CrossRef Search ADS 41 VanScoy BD , McCauley J , Ellis-Grosse EJ et al. Exploration of the pharmacokinetic-pharmacodynamic relationships for fosfomycin efficacy using an in vitro infection model . Antimicrob Agents Chemother 2015 ; 59 : 7170 – 7 . Google Scholar CrossRef Search ADS 42 Tam VH , Schilling AN , Neshat S et al. Optimization of meropenem minimum concentration/MIC ratio to suppress in vitro resistance of Pseudomonas aeruginosa . Antimicrob Agents Chemother 2005 ; 49 : 4920 – 7 . Google Scholar CrossRef Search ADS 43 Tam VH , Louie A , Deziel MR et al. The relationship between quinolone exposures and resistance amplification is characterized by an inverted U: a new paradigm for optimizing pharmacodynamics to counterselect resistance . Antimicrob Agents Chemother 2007 ; 51 : 744 – 7 . Google Scholar CrossRef Search ADS 44 Bergan T , Thorsteinsson SB , Albini E. Pharmacokinetic profile of fosfomycin trometamol . Chemotherapy 1993 ; 39 : 297 – 301 . Google Scholar CrossRef Search ADS 45 Matzi V , Lindenmann J , Porubsky C et al. Extracellular concentrations of fosfomycin in lung tissue of septic patients . J Antimicrob Chemother 2010 ; 65 : 995 – 8 . Google Scholar CrossRef Search ADS 46 Drusano GL , Liu W , Fikes S et al. Interaction of drug- and granulocyte-mediated killing of Pseudomonas aeruginosa in a murine pneumonia model . J Infect Dis 2014 ; 210 : 1319 – 24 . Google Scholar CrossRef Search ADS 47 Rodriguez-Rojas A , Couce A , Blazquez J. Frequency of spontaneous resistance to fosfomycin combined with different antibiotics in Pseudomonas aeruginosa . Antimicrob Agents Chemother 2010 ; 54 : 4948 – 9 . Google Scholar CrossRef Search ADS 48 Rodriguez-Rojas A , Macia MD , Couce A et al. Assessing the emergence of resistance: the absence of biological cost in vivo may compromise fosfomycin treatments for P. aeruginosa infections . PLoS One 2010 ; 5 : e10193 . Google Scholar CrossRef Search ADS 49 Castañeda-García A , Rodríguez-Rojas A , Guelfo JR et al. The glycerol-3-phosphate permease GlpT is the only fosfomycin transporter in Pseudomonas aeruginosa . J Bacteriol 2009 ; 191 : 6968 – 74 . Google Scholar CrossRef Search ADS 50 Kahan FM , Kahan JS , Cassidy PJ et al. The mechanism of action of fosfomycin (phosphonomycin) . Ann N Y Acad Sci 1974 ; 235 : 364 – 86 . Google Scholar CrossRef Search ADS 51 MacLeod DL , Velayudhan J , Kenney TF et al. Fosfomycin enhances the active transport of tobramycin in Pseudomonas aeruginosa . Antimicrob Agents Chemother 2012 ; 56 : 1529 – 38 . Google Scholar CrossRef Search ADS 52 MacLeod DL , Barker LM , Sutherland JL et al. Antibacterial activities of a fosfomycin/tobramycin combination: a novel inhaled antibiotic for bronchiectasis . J Antimicrob Chemother 2009 ; 64 : 829 – 36 . Google Scholar CrossRef Search ADS 53 Kunakonvichaya B , Thirapanmethee K , Khuntayaporn P et al. Synergistic effects of fosfomycin and carbapenems against carbapenem-resistant Pseudomonas aeruginosa clinical isolates . Int J Antimicrob Agents 2015 ; 45 : 556 – 7 . Google Scholar CrossRef Search ADS 54 Lepak AJ , Zhao M , VanScoy B et al. In vivo pharmacokinetics and pharmacodynamics of ZTI-01 (fosfomycin for injection) in the neutropenic murine thigh infection model against Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa . Antimicrob Agents Chemother 2017 ; 61 . © The Author(s) 2018. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please email: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Antimicrobial Chemotherapy Oxford University Press

Elucidation of the pharmacokinetic/pharmacodynamic determinants of fosfomycin activity against Pseudomonas aeruginosa using a dynamic in vitro model

Loading next page...
 
/lp/ou_press/elucidation-of-the-pharmacokinetic-pharmacodynamic-determinants-of-sKJi2Lpdbu
Publisher
Oxford University Press
Copyright
© The Author(s) 2018. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
ISSN
0305-7453
eISSN
1460-2091
D.O.I.
10.1093/jac/dky045
Publisher site
See Article on Publisher Site

Abstract

Abstract Objectives To identify the fosfomycin pharmacokinetic (PK)/pharmacodynamic (PD) index (fT>MIC, fAUC/MIC or fCmax/MIC) most closely correlated with activity against Pseudomonas aeruginosa and determine the PK/PD target associated with various extents of bacterial killing and the prevention of emergence of resistance. Methods Dose fractionation was conducted over 24 h in a dynamic one-compartment in vitro PK/PD model utilizing P. aeruginosa ATCC 27853 and two MDR clinical isolates (CR 1005 and CW 7). In total, 35 different dosing regimens were examined across the three strains. Microbiological response was examined by log changes and population analysis profiles. A Hill-type Emax model was fitted to the killing effect data (expressed as the log10 ratio of the area under the cfu/mL curve for treated regimens versus controls). Results Bacterial killing of no more than ∼3 log10 cfu/mL was achieved irrespective of regimen. The fAUC/MIC was the PK/PD index most closely correlated with efficacy (R2 = 0.80). The fAUC/MIC targets required to achieve 1 and 2 log10 reductions in the area under the cfu/mL curve relative to growth control were 489 and 1024, respectively. No regimen was able to suppress the emergence of resistance, and near-complete replacement of susceptible with resistant subpopulations occurred with virtually all regimens. Conclusions Bacterial killing for fosfomycin against P. aeruginosa was most closely associated with the fAUC/MIC. Suppression of fosfomycin-resistant subpopulations could not be achieved even with fosfomycin exposures well above those that can be safely achieved clinically. Introduction Effective treatment of infections caused by MDR Gram-negative pathogens such as Pseudomonas aeruginosa is a major medical challenge.1–3,P. aeruginosa, previously identified by the IDSA as one of the top six pathogens threatening healthcare systems,4,5 has now been categorized as a ‘Serious’ threat level by the US CDC.6 With numerous intrinsic and acquired resistance mechanisms present in this organism,7 antibiotic resistance across all P. aeruginosa infections emerges during therapy in up to 25% of cases and is associated with treatment failure in 50%–85% of patients and greater risk of mortality.8,9 With a shortage of new antibiotics with novel mechanisms of action in the drug discovery and development pipeline,10 there is a growing need to optimize the use of older ‘forgotten’ antibiotics11 to treat infections, including those caused by P. aeruginosa.12 Fosfomycin is an older antibiotic exhibiting activity against many Gram-negative pathogens, including a significant subset of MDR P. aeruginosa strains.13–15 Given that it is generally well tolerated,16 fosfomycin has been suggested as a promising agent for managing infections caused by Gram-negative bacilli that are resistant to commonly used antibiotics.17 Unfortunately the development of fosfomycin (first isolated from Streptomyces species in 1969)18 occurred when drug development was conducted more or less on a trial-and-error basis.19 Consequently, there is a dearth of knowledge on the pharmacokinetic (PK) and pharmacodynamic (PD) properties of fosfomycin required to optimize therapy.20 This lack of established regimens specifically for complicated infections is a primary limitation to the use of fosfomycin and carries significant risks for patient outcomes, adverse events and resistance emergence.13,21 It has been recommended that exposure–response relationships for older antimicrobials, including fosfomycin, be urgently established.17,20 The determination of the relationship between bacterial killing and emergence of resistance with respect to PK/PD indices and the determination of PK/PD targets will assist in the design of rational dosing strategies for fosfomycin. Therefore, we utilized an in vitro PK/PD model (i) to identify the PK/PD index [i.e. the cumulative percentage of a 24 h period for which unbound concentrations exceed the MIC (fT>MIC), the area under the unbound concentration–time curve to MIC ratio (fAUC/MIC) or the unbound maximal concentration to MIC ratio (fCmax/MIC)] that best predicts bacterial killing of fosfomycin against P. aeruginosa; and (ii) to determine the magnitude of the predictive PK/PD index required to achieve various extents of bacterial killing and/or prevent the emergence or amplification of fosfomycin-resistant mutants. Materials and methods Antibiotics, bacterial isolates and MIC testing Fosfomycin disodium (Lot 20131012, Waterstone Technology, Carmel, IN, USA) and glucose-6-phosphate (G6P; Lot SLBD7775V, Sigma-Aldrich, Castle Hill, NSW, Australia) were supplied by their respective manufacturers. Sterile stock solutions were prepared in Milli-Q water immediately prior to each experiment. Cation-adjusted Mueller–Hinton agar and CAMHB supplemented with 25 mg/L G6P per CLSI guidelines were used in all experiments.22 Three fosfomycin-susceptible strains of P. aeruginosa were examined: reference strain ATCC 27853 (ATCC, Manassas, VA, USA) and two previously described MDR clinical isolates [CR 1005 (non-mucoid) and CW 7 (mucoid)].23 MDR was defined as non-susceptibility to at least one antimicrobial agent in three or more antimicrobial categories.24 The MICs, determined in duplicate on separate days using agar dilution per CLSI guidelines,22 were 8 mg/L for ATCC 27853, 32 mg/L for CR 1005 and 16 mg/L for CW 7. As breakpoints for fosfomycin against Pseudomonas spp. are currently lacking, we applied modified CLSI breakpoints for Escherichia coli with an MIC ≤64 mg/L considered susceptible and >64 mg/L resistant.22 Population analysis profiles The possible presence of fosfomycin-resistant subpopulations within the predominant (susceptible) population at baseline was determined via population analysis profiles (PAPs) (inoculum ∼108 cfu/mL) for each strain as described previously.23 Fosfomycin heteroresistance was defined as the presence within a fosfomycin-susceptible isolate (i.e. MIC ≤64 mg/L) of subpopulations able to grow on agar containing >64 mg/L fosfomycin. Random colonies were selected from fosfomycin-containing agar plates for repeated MIC testing to confirm the increased MICs. Dynamic in vitro PK/PD model, fosfomycin dosing regimens and emergence of resistance A previously described dynamic in vitro PK/PD model25 was used over 24 h to examine the PK/PD index that best predicts the antimicrobial response of fosfomycin. Prior to each experiment, strains were subcultured onto Mueller–Hinton agar (Media Preparation Unit) and incubated overnight at 35°C. One colony was then selected and grown overnight in 10 mL of CAMHB from which early log-phase growth was obtained. A 1 mL aliquot was then injected into each central compartment to yield a starting inoculum of ∼106 cfu/mL. Both continuous infusion and intermittent dosing regimens were simulated as described previously,25 with serial samples for viable cell counting and determination of fosfomycin concentrations collected aseptically as shown in Table 1. For intermittent regimens an elimination half-life (t½) of 4 h was simulated, approximating fosfomycin elimination in critically ill patients26,27 and healthy volunteers.28,29 Given that fosfomycin has negligible plasma protein binding,30,31 concentrations were assumed to constitute unbound fosfomycin. Viability counting was undertaken as previously described23 and antibiotic carryover minimized by centrifuging all samples for 5 min at 10 000 rpm with resuspension in prewarmed saline (37°C). To additionally examine the presence of fosfomycin-resistant subpopulations at baseline (0 h) and following 24 h of treatment, PAPs were conducted on all isolates for a subset of experiments at these times on Mueller–Hinton agar containing G6P (25 mg/L) and fosfomycin at 32, 64, 128 and 256 mg/L. Table 1. Fosfomycin dosing regimens and sampling times in the in vitro PK/PD modela,b Dosing regimen 8 h 12 h 24 h CC Target fCmax (mg/L)  ATCC 27853 250, 125, 75, 50, 12.5, 6.25 2500, 1500, 1125, 1000, 750, 425, 250, 63, 32 3000, 2000, 1300, 1000e, 750, 500e, 250e, 125e, 63e, 16e 50, 25  CR 1005 250, 125, 75, 50, 25, 12.5 750, 500, 63, 32, 16, 8 3000, 2500, 2000, 1500, 750, 500, 250, 63, 32 500, 250, 50, 25  CW 7 250, 125, 75, 50, 12.5, 6.25 500, 63, 32, 16 3000, 2500, 2000, 1500, 500, 250, 63, 32 500, 250, 50, 25 Sampling times (h) for  microbiological measurementsc 0, 1, 3, 5, 8, 16, 24 0, 1, 3, 5, 8, 12, 24 0, 1, 3, 5, 8, 24 0, 1, 3, 5, 8, 24  fosfomycin quantificationc,d 0, 4, 8, 9, 12, 13, 16, 17, 24 0, 4, 8, 12, 13, 24 0, 4, 8, 24 0, 4, 8, 24 Dosing regimen 8 h 12 h 24 h CC Target fCmax (mg/L)  ATCC 27853 250, 125, 75, 50, 12.5, 6.25 2500, 1500, 1125, 1000, 750, 425, 250, 63, 32 3000, 2000, 1300, 1000e, 750, 500e, 250e, 125e, 63e, 16e 50, 25  CR 1005 250, 125, 75, 50, 25, 12.5 750, 500, 63, 32, 16, 8 3000, 2500, 2000, 1500, 750, 500, 250, 63, 32 500, 250, 50, 25  CW 7 250, 125, 75, 50, 12.5, 6.25 500, 63, 32, 16 3000, 2500, 2000, 1500, 500, 250, 63, 32 500, 250, 50, 25 Sampling times (h) for  microbiological measurementsc 0, 1, 3, 5, 8, 16, 24 0, 1, 3, 5, 8, 12, 24 0, 1, 3, 5, 8, 24 0, 1, 3, 5, 8, 24  fosfomycin quantificationc,d 0, 4, 8, 9, 12, 13, 16, 17, 24 0, 4, 8, 12, 13, 24 0, 4, 8, 24 0, 4, 8, 24 a Dosing regimens involved intermittent administration at 8, 12 or 24 h to achieve the target steady-state fCmax or CC simulating continuous infusion. b Fosfomycin MICs were 8 mg/L for ATCC 27853, 32 mg/L for CR 1005 and 16 mg/L for CW 7. c Initial experiments with multiple-dose regimens (dosing every 8 and 12 h) at high concentrations showed no further bacterial killing at later timepoints (12 and 16 h). Consequently, for subsequent experiments sampling was conducted up to 8 h and then at 24 h. d A subset of each dosing regimen (8 h, 12 h, 24 h and CC) was assayed to determine fosfomycin concentrations. e Results from a previous study.23 Table 1. Fosfomycin dosing regimens and sampling times in the in vitro PK/PD modela,b Dosing regimen 8 h 12 h 24 h CC Target fCmax (mg/L)  ATCC 27853 250, 125, 75, 50, 12.5, 6.25 2500, 1500, 1125, 1000, 750, 425, 250, 63, 32 3000, 2000, 1300, 1000e, 750, 500e, 250e, 125e, 63e, 16e 50, 25  CR 1005 250, 125, 75, 50, 25, 12.5 750, 500, 63, 32, 16, 8 3000, 2500, 2000, 1500, 750, 500, 250, 63, 32 500, 250, 50, 25  CW 7 250, 125, 75, 50, 12.5, 6.25 500, 63, 32, 16 3000, 2500, 2000, 1500, 500, 250, 63, 32 500, 250, 50, 25 Sampling times (h) for  microbiological measurementsc 0, 1, 3, 5, 8, 16, 24 0, 1, 3, 5, 8, 12, 24 0, 1, 3, 5, 8, 24 0, 1, 3, 5, 8, 24  fosfomycin quantificationc,d 0, 4, 8, 9, 12, 13, 16, 17, 24 0, 4, 8, 12, 13, 24 0, 4, 8, 24 0, 4, 8, 24 Dosing regimen 8 h 12 h 24 h CC Target fCmax (mg/L)  ATCC 27853 250, 125, 75, 50, 12.5, 6.25 2500, 1500, 1125, 1000, 750, 425, 250, 63, 32 3000, 2000, 1300, 1000e, 750, 500e, 250e, 125e, 63e, 16e 50, 25  CR 1005 250, 125, 75, 50, 25, 12.5 750, 500, 63, 32, 16, 8 3000, 2500, 2000, 1500, 750, 500, 250, 63, 32 500, 250, 50, 25  CW 7 250, 125, 75, 50, 12.5, 6.25 500, 63, 32, 16 3000, 2500, 2000, 1500, 500, 250, 63, 32 500, 250, 50, 25 Sampling times (h) for  microbiological measurementsc 0, 1, 3, 5, 8, 16, 24 0, 1, 3, 5, 8, 12, 24 0, 1, 3, 5, 8, 24 0, 1, 3, 5, 8, 24  fosfomycin quantificationc,d 0, 4, 8, 9, 12, 13, 16, 17, 24 0, 4, 8, 12, 13, 24 0, 4, 8, 24 0, 4, 8, 24 a Dosing regimens involved intermittent administration at 8, 12 or 24 h to achieve the target steady-state fCmax or CC simulating continuous infusion. b Fosfomycin MICs were 8 mg/L for ATCC 27853, 32 mg/L for CR 1005 and 16 mg/L for CW 7. c Initial experiments with multiple-dose regimens (dosing every 8 and 12 h) at high concentrations showed no further bacterial killing at later timepoints (12 and 16 h). Consequently, for subsequent experiments sampling was conducted up to 8 h and then at 24 h. d A subset of each dosing regimen (8 h, 12 h, 24 h and CC) was assayed to determine fosfomycin concentrations. e Results from a previous study.23 Three intermittent dosing intervals (8, 12 and 24 h) with fCmax varied across each schedule plus constant concentration (CC) regimens were examined (Table 1). Dosing regimens were selected to maximally differentiate among the PK/PD indices under investigation (fAUC/MIC, fCmax/MIC and fT>MIC) and included a wide concentration range to allow exploration of the complete dose–response relationship from essentially no effect to maximum effect. Fosfomycin concentrations were determined using a previously published LC-MS/MS assay with minor modification.32 The assay range was 1–500 mg/L; samples were diluted if the expected fosfomycin concentrations were higher than the upper limit of quantification. Investigation of PK/PD indices For each dosing regimen the %fT>MIC, fAUC/MIC, fCmax/MIC and the area under the killing curve (AUCcfu) of the time-course profile of bacterial numbers (cfu/mL from 0 to 24 h) were determined as described previously at both 1× and 10× MIC.25 The log ratio area method, which mostly compensates for the bacterial loss from the model,33 was used to quantify the killing effect (drug effect) chosen as the measure of efficacy (E) per the equation: E = log10[AUCcfu(treatment)/AUCcfu(growth control)]. The relationship between killing effect (E) and each PK/PD index was analysed as described previously using a Hill equation with a baseline and an inhibitory effect, with the magnitude of the most predictive PK/PD index required to achieve 1 or 2 log10 reduction in the area under the cfu/mL curve relative to growth control estimated from the E0, Emax, EI50 and γ.25 Results Baseline PAPs Baseline PAPs are shown in Figure 1. Despite all strains being considered fosfomycin susceptible based on MICs (MICs of 8, 16 and 32 mg/L), growth occurred on all PAP plates up to and including 256 mg/L. Colonies obtained from plates containing fosfomycin at 128 and 256 mg/L had elevated MICs (≥128 mg/L for ATCC 27853 and ≥256 mg/L for CR 1005 and CW 7), indicating that resistant subpopulations were present in all strains prior to treatment. The proportion of bacterial colonies growing on plates containing fosfomycin at 128 mg/L were 4.20 × 10−6, 1.87 × 10−5 and 2.57 × 10−6 for ATCC 27853, CR 1005 and CW 7, respectively; a similar proportion of subpopulations grew in the presence of 256 mg/L. Figure 1. View largeDownload slide Baseline PAPs of reference strain ATCC 27853 and two clinical isolates. All strains were considered susceptible based on MIC determinations (MICs of 8, 32 and 16 mg/L). Figure 1. View largeDownload slide Baseline PAPs of reference strain ATCC 27853 and two clinical isolates. All strains were considered susceptible based on MIC determinations (MICs of 8, 32 and 16 mg/L). Quantification of fosfomycin concentrations, bacterial killing and emergence of resistance Observed fosfomycin concentrations were on average within 15% of those targeted. Typical profiles showing the relationship between targeted and observed concentrations are shown in Figure 2. Representative time-course profiles of bacterial numbers for each isolate, including the PAPs, are presented in Figure 3. The initial inocula in the control and treatment compartments (mean ± SD) were: 6.03 (n = 2) and 5.91 ± 0.24 (n = 27) log10 cfu/mL for ATCC 27853, 6.07 ± 0.30 (n = 3) and 6.34 ± 0.18 (n = 25) log10 cfu/mL for CR 1005, and 6.35 ± 0.12 (n = 4) and 6.01 ± 0.15 (n = 30) log10 cfu/mL for CW 7. After 24 h, bacterial numbers in the control compartments had increased to 8.1 (n = 2), 8.15 ± 0.26 (n = 3) and 8.30 ± 0.27 (n = 4) log10 cfu/mL for ATCC 27853, CR 1005 and CW 7, respectively. Figure 2. View largeDownload slide Typical simulated PK profiles showing the relationship between targeted and achieved fosfomycin concentrations in the PK/PD model. Figure 2. View largeDownload slide Typical simulated PK profiles showing the relationship between targeted and achieved fosfomycin concentrations in the PK/PD model. Figure 3. View largeDownload slide Left-hand panels: representative microbiological responses observed in the in vitro PK/PD model simulating the fosfomycin PK of different dosing regimens using ATCC 27853, CR 1005 and CW 7. Right-hand panels: PAPs at baseline (0 h) and after 24 h of exposure to fosfomycin at an initial inoculum of ∼106 cfu/mL. Figure 3. View largeDownload slide Left-hand panels: representative microbiological responses observed in the in vitro PK/PD model simulating the fosfomycin PK of different dosing regimens using ATCC 27853, CR 1005 and CW 7. Right-hand panels: PAPs at baseline (0 h) and after 24 h of exposure to fosfomycin at an initial inoculum of ∼106 cfu/mL. The rate of initial bacterial killing against each isolate generally increased with increasing fosfomycin concentrations up to ∼10× MIC; further increases did not produce more rapid or extensive killing. With the majority of fosfomycin regimens, initial killing of no more than ∼3 log10 cfu/mL occurred across the first 4–8 h for all isolates followed by regrowth close to control values at 24 h. In a small number of cases with very high-dose regimens [e.g. fCmax of 750 mg/L and 1500 mg/L every 12 h against ATCC 27853 (Figure 3, left-hand panel)], regrowth remained below the initial inoculum at 24 h. Maximum bacterial killing achieved against ATCC 27853 was 3.0 log10 cfu/mL using an fCmax of 1500 mg/L administered every 12 h. The equivalent values and regimens for CR 1005 and CW 7 were 3.1 log10 cfu/mL with an fCmax of 750 mg/L every 12 h and 3.2 log10 cfu/mL with two regimens, fCmax of 1500 mg/L every 12 h and 500 mg/L as a CC, respectively. For the subset of experiments that included PAPs, no fosfomycin-resistant colonies for any strain were detected immediately prior to the commencement of therapy at the starting inoculum of ∼106 cfu/mL (Figure 3, right-hand panels). For the growth controls, PAPs following 24 h of incubation indicated the presence of resistant subpopulations in all three strains; growth at this time was ∼108–8.5 cfu/mL. The proportion of resistant colonies growing on plates containing fosfomycin at 128 mg/L at 24 h was 1.87 × 10−6, 1.02 × 10−4 and 1.81 × 10−6 for ATCC 27853, CR 1005 and CW 7, respectively. These proportions were similar to those observed with the baseline PAPs (inoculum ∼108 cfu/mL). With the exception of the fCmax 32 mg/L 12 h regimen against CW 7 (in which the proportion of resistant colonies at 24 h was 3.33 × 10−4), with all other regimens in which PAPs were performed virtually the entire population at 24 h grew in the presence of fosfomycin at 256 mg/L (Figure 3, right-hand panels). Relationships between bacterial killing and PK/PD indices The relationships between killing effect and fAUC/MIC, fCmax/MIC and fT>MIC are shown in Figure 4. At 1× and 10 × MIC the PK/PD index that best predicted efficacy was fAUC/MIC (R2 = 0.80; Figure 4, top row). A poorer relationship existed between the killing effect and fCmax/MIC, for which greater scatter and systemic deviations from the curve fit were observed (R2 = 0.71; Figure 4, middle row). No relationship was observed for fT>MIC at 1× MIC (Figure 4c), but one was found at 10 × MIC (R2 = 0.70; Figure 4f). The magnitudes of the fAUC/MIC indexes required for 1 and 2 log10 reduction in the area under the cfu/mL curve relative to growth control for each strain were 489 and 1024, respectively. Figure 4. View largeDownload slide Relationship between the killing effect of fosfomycin against P. aeruginosa ATCC 27853 (open circles), CR 1005 (open squares) and CW 7 (open triangles) as a function of three PK/PD indices (calculated at 1× and 10× MIC): fAUC/MIC, fCmax/MIC and fT>MIC. Each data point represents the result from a single treatment run in the dynamic in vitro PK/PD model. Figure 4. View largeDownload slide Relationship between the killing effect of fosfomycin against P. aeruginosa ATCC 27853 (open circles), CR 1005 (open squares) and CW 7 (open triangles) as a function of three PK/PD indices (calculated at 1× and 10× MIC): fAUC/MIC, fCmax/MIC and fT>MIC. Each data point represents the result from a single treatment run in the dynamic in vitro PK/PD model. Discussion Oral fosfomycin (fosfomycin tromethamine) is currently indicated for treatment of uncomplicated urinary tract infections caused by E. coli and Enterococcus faecalis in women.34 However, the parenteral (disodium) formulation is increasingly used to treat systemic infections caused by MDR organisms, including P.aeruginosa.35–37 Unfortunately, the information required to optimize dosing regimens using exposure–response relationships is not available. It has therefore been suggested that establishing the exposure–response relationships for fosfomycin for both efficacy and resistance selection—which are often distinctly different—be made a priority.20 We sought to determine the predictive performance of potential PK/PD indices with respect to bacterial killing and the emergence of resistance against P. aeruginosa, including MDR isolates. We have previously reported maximal bacterial killing of ∼3 log10 cfu/mL followed by rapid regrowth against P. aeruginosa ATCC 27853 in a 24 h PK/PD model using once-daily dosing (fCmax, 1000 mg/L).23 Similar maximal killing was recently shown for the same strain using static time–kill studies (Cmax, 128 mg/L) and a tissue-cage infection model.38 This maximal level of killing is almost identical to that achieved here against the same reference strain and two additional MDR clinical isolates with dosing regimens providing a much greater exposure to fosfomycin (e.g. fCmax 1000 mg/L every 12 h or fCmax 3000 mg/L every 24 h). Importantly, near-complete replacement of susceptible with resistant subpopulations occurred with virtually all regimens. Although fosfomycin-resistant colonies were not detected immediately prior to commencement of therapy in the dose-fractionation studies (inoculum ∼106 cfu/mL), ∼2–3 log10 cfu/mL of resistant colonies growing on agar containing 256 mg/L fosfomycin were present in the baseline PAPs (inoculum ∼108 cfu/mL). Thus, it is highly likely that resistant subpopulations were present at the commencement of therapy in the dose-fractionation studies but were simply not detected at the lower inoculum. The rapid regrowth observed following commencement of fosfomycin administration was driven, at least in part, by amplification of these pre-existing, highly fosfomycin-resistant subpopulations. This is similar to what we observed previously against P. aeruginosa at much lower fosfomycin exposures [maximum AUC0–24 of 5680, 2840 mg·h/L (fCmax of 1000 and 500 mg/L administered every 24 h)].23 However, even an AUC0–24 of 25 247 mg·h/L (fCmax of 2500 mg/L administered every 12 h) in the present study could not suppress the emergence of resistance; this is much greater than achieved in patients with standard dosing regimens (typically 4–8 g intravenously every 8 h for serious systemic infections) in which fCmax typically ranges from 400 to 1000 mg/L.26,31,32,39 Very few studies have previously examined the emergence of fosfomycin resistance. Using a hollow-fibre infection model (half-life, 4 h; initial inoculum, ∼1 × 106 cfu/mL) and a single clinical isolate of E. coli, Docobo-Pérez et al.40 simulated human-like concentration–time profiles corresponding to fosfomycin regimens of 4, 5, 6 and 8 g every 8 h, with each dose infused over 1 h, or 24 g every 24 h administered as a single bolus. For the two 24 g/day regimens (administered once daily or as divided doses) no viable bacteria were detected at 40 h. For all other regimens, rapid regrowth with amplification of fosfomycin-resistant subpopulations occurred such that by ∼64 h the entire population grew on agar containing fosfomycin at 256 mg/L. These results indicate that at least for this single isolate of E. coli resistance suppression is achievable. Given that both the 8 g/8 h and 24 g/24 h regimens eradicated the entire population, the authors concluded that the fAUC/MIC was the dynamic index best linked to resistance suppression. VanScoy et al.41 were similarly able to suppress bacterial regrowth and the emergence of fosfomycin-resistant subpopulations of a heteroresistant E. coli reference strain with regimens containing ≥1 g of fosfomycin administered every 6 h. However, even with these dosing regimens the total population was not eradicated. With regimens containing ≤0.5 g administered every 6 h, rapid bacterial regrowth with amplification of fosfomycin-resistant subpopulations occurred such that the latter completely replaced the total population. They obtained similar results against the same strain in dose-fractionation studies (discussed below) in which emergence of resistant subpopulations, often completely dominating the total population, occurred with lower-dose regimens but was suppressed or even eliminated completely with higher-dose regimens. The relationship between fosfomycin dose and the emergence of resistant subpopulations matched an inverted-U-shaped function, described previously with other antibiotics, including against P. aeruginosa.42,43 Using single reference strains of E. coli and P. aeruginosa (ATCC 27853), Pan et al.38 reported selective enrichment of resistant subpopulations (growing on agar containing fosfomycin at 4, 8 and 16× MIC) for both isolates across a specific concentration range, but no development of fosfomycin resistance at a higher concentration. For P. aeruginosa, enrichment occurred with concentrations of 16–64 mg/L for time–kill studies, with resistance suppression occurring at 128 mg/L; a similar result was achieved with in vivo tissue-cage experiments (24 h dosing with a maximum achieved concentration of ∼300 mg/L). To the best of our knowledge this is the only report indicating suppression of resistance against P. aeruginosa with fosfomycin monotherapy. This is an interesting and unexplained result given the extremely high initial inoculum (∼109 cfu/mL). We have previously shown in static time–kill studies a pronounced inoculum effect for fosfomycin against three strains of P. aeruginosa, including ATCC 27853, with bacterial killing essentially eliminated at an inoculum of ∼108 cfu/mL across a concentration range of 1–1024 mg/L; highly resistant subpopulations were enriched with all but the lowest concentrations used.23 Given our previous observations of a near-complete lack of activity with monotherapy at a high inoculum, we chose a lower inoculum (∼106 cfu/mL) for the present study. However, extremely high exposures in the present study (up to an fCmax of 3000 mg/L) with a lower starting inoculum were similarly unable to suppress amplification of resistant subpopulations, even with the loss of some bacteria from the system; bacterial loss is a limitation of one-compartment models. This situation would only be made worse if a shorter half-life, which would reduce bacterial killing even further, were to be used; half-lives of 2–3 h have been reported in some critically ill patients.44,45 Regardless of resistance emergence, absolute bacterial numbers in the study by Pan et al.38 never dropped below ∼5–6 log10 cfu/mL. That study notwithstanding, although increasing fosfomycin exposures may prevent or limit the emergence of resistance against other organisms such as E. coli, such a relationship does not appear to exist against P. aeruginosa. Indeed, we previously found that all of the 14 P. aeruginosa isolates examined (MIC range: 1–64 mg/L) contained resistant subpopulations,23 and that only moderate bacterial killing is achievable even with supra-therapeutic exposures (maximum killing of ∼3 log10 cfu/mL). Therefore, against P. aeruginosa, treatment failure with fosfomycin monotherapy would appear likely even considering the potential added effect of the immune system,46 with monotherapy regimens serving only to amplify pre-existing and highly resistant subpopulations. This situation is compounded by the fact that resistance to fosfomycin in P. aeruginosa appears to come with no apparent fitness cost.14,47,48 The difference in resistance suppression between P. aeruginosa and E. coli may be due to differences in the transport systems required for fosfomycin entry into the cells. E. coli contains two transport systems, the glycerol-3-phosphate (GlpT) and a hexose phosphate (UhpT), whereas P. aeruginosa contains only GlpT.49,50 Thus only a single mutation is required in P. aeruginosa to prevent fosfomycin entry and render the organism resistant, whereas in E. coli two mutations would be required.47,48,51–53 Only two previous studies have purported to examine the exposure–response relationships for bacterial killing of fosfomycin against any organisms. VanScoy et al.41 used a one-compartment PK/PD model similar to ours to examine bacterial killing and resistance emergence against one reference strain and two clinical isolates of E. coli. Experiments were conducted over 24 h (starting inoculum ∼1 × 106 cfu/mL) and simulated a fosfomycin half-life of 2 h. Three regimens with intermittent administration every 6, 8 and 12 h, as well as a continuous-infusion regimen, were examined, with each providing the same total daily fosfomycin exposure (as measured by the AUC0–24). The authors concluded that fosfomycin activity was most likely linked to fAUC/MIC (R2 = 0.76), although there was also a strong correlation with fCmax/MIC (R2 = 0.62); there was a poor relationship between bacterial killing and fT>MIC (R2 = 0.42). However, it was noted that given the majority of fT>MIC values were 100%, the PK/PD relationship based on this index could not be adequately explored. Lepak et al.54 used the neutropenic murine thigh infection model to examine the PK/PD activity of fosfomycin against five strains of E. coli, three of Klebsiella pneumoniae and two of P. aeruginosa. Although they determined that the PK/PD index best correlated with activity against these organisms was the AUC/MIC (R2 = 0.70; protein binding was not stated), dose-fractionation was only conducted on a single strain of E. coli; for K. pneumoniae and P. aeruginosa, only increasing doses administered every 3 h were used, with the index determined for E. coli assumed to also apply to these organisms. Our dose-fractionation study employed the largest range of fosfomycin concentrations (fCmax range: 6.25–3000 mg/L) and dosing regimens (30 different regimens) used against any organism and is the first to specifically use a dose-fractionation design to examine the PK/PD index driving bacterial activity and the emergence of resistance for fosfomycin against P. aeruginosa. In agreement with the E. coli studies of VanScoy et al.41 and Lepak et al.,54 bacterial killing was most closely correlated with fAUC/MIC. Although we have previously shown using both MDR and non-MDR isolates of P. aeruginosa that bacterial killing by fosfomycin against this organism is time dependent,23 we were unable to find a relationship between activity and fT>1×MIC. This may be explained by a large number of the dosing regimens having a fT>1×MIC of 100%. To account for this we also analysed each index at 10× MIC. Although a relationship was present between activity and fT>10×MIC (Figure 4f), the fAUC/MIC nevertheless remained the index most closely associated with activity. This is the first study to utilize a dose-fractionation design to investigate the relationship between PK/PD indices and bacterial killing for fosfomycin against P. aeruginosa. The fAUC/MIC was most closely correlated with bacterial killing. No fosfomycin exposures, including exposures well above those that are clinically achievable in plasma following intravenous administration, were able to suppress the emergence of resistant subpopulations. Our results suggest that for systemic infections involving P. aeruginosa, fosfomycin monotherapy will be ineffective. Funding This study was supported by a Ramaciotti Establishment Grant provided by the Ramaciotti Foundations and an Australian Society for Antimicrobials Research Grant provided by the Australian Society for Antimicrobials. C. B. L. is the recipient of an Australian National Health and Medical Research Council Career Development Fellowship (APP1062509). A. Y. P was supported by an Australian National Health and Medical Research Council Practitioner Fellowship. Transparency declarations None to declare. References 1 Harris P , Paterson D , Rogers B. Facing the challenge of multidrug-resistant gram-negative bacilli in Australia . Med J Aust 2015 ; 202 : 243 – 7 . Google Scholar CrossRef Search ADS 2 Wilson R , Aksamit T , Aliberti S et al. Challenges in managing Pseudomonas aeruginosa in non-cystic fibrosis bronchiectasis . Respir Med 2016 ; 117 : 179 – 89 . Google Scholar CrossRef Search ADS 3 Berdy J. Thoughts and facts about antibiotics: where we are now and where we are heading . J Antibiot 2012 ; 65 : 385 – 95 . Google Scholar CrossRef Search ADS 4 Boucher HW , Talbot GH , Bradley JS et al. Bad bugs, no drugs: no ESKAPE! An update from the Infectious Diseases Society of America . Clin Infect Dis 2009 ; 48 : 1 – 12 . Google Scholar CrossRef Search ADS 5 Talbot GH , Bradley J , Edwards JE et al. Bad bugs need drugs: an update on the development pipeline from the Antimicrobial Availability Task Force of the Infectious Diseases Society of America . Clin Infect Dis 2006 ; 42 : 657 – 68 . Google Scholar CrossRef Search ADS 6 CDC . Antibiotic/Antimicrobial Resistance: Antimicrobial Resistance Threats in the United States . Atlanta, GA, USA : CDC , 2013 . 7 Driscoll JA , Brody SL , Kollef MH. The epidemiology, pathogenesis and treatment of Pseudomonas aeruginosa infections . Drugs 2007 ; 67 : 351 – 68 . Google Scholar CrossRef Search ADS 8 Carmeli Y , Troillet N , Karchmer AW et al. Health and economic outcomes of antibiotic resistance in Pseudomonas aeruginosa . Arch Intern Med 1999 ; 159 : 1127 – 32 . Google Scholar CrossRef Search ADS 9 Milatovic D , Braveny I. Development of resistance during antibiotic therapy . Eur J Clin Microbiol 1987 ; 6 : 234 – 44 . Google Scholar CrossRef Search ADS 10 Boucher HW , Talbot GH , Benjamin DK Jr et al. 10×'20 Progress—development of new drugs active against Gram-negative bacilli: an update from the Infectious Diseases Society of America . Clin Infect Dis 2013 ; 56 : 1685 – 94 . Google Scholar CrossRef Search ADS 11 Zayyad H , Eliakim-Raz N , Leibovici L et al. Revival of old antibiotics: needs, the state of evidence and expectations . Int J Antimicrob Agents 2017 ; 49 : 536 – 41 . Google Scholar CrossRef Search ADS 12 Taneja N , Kaur H. Insights into newer antimicrobial agents against Gram-negative bacteria . Microbiol Insights 2016 ; 9 : 9 – 19 . 13 Reffert JL , Smith WJ. Fosfomycin for the treatment of resistant gram-negative bacterial infections. Insights from the Society of Infectious Diseases Pharmacists . Pharmacotherapy 2014 ; 34 : 845 – 57 . Google Scholar CrossRef Search ADS 14 Karageorgopoulos DE , Wang R , Yu X-H et al. Fosfomycin: evaluation of the published evidence on the emergence of antimicrobial resistance in Gram-negative pathogens . J Antimicrob Chemother 2012 ; 67 : 255 – 68 . Google Scholar CrossRef Search ADS 15 Hirsch EB , Raux BR , Zucchi PC et al. Activity of fosfomycin and comparison of several susceptibility testing methods against contemporary urine isolates . Int J Antimicrob Agents 2015 ; 46 : 642 – 7 . Google Scholar CrossRef Search ADS 16 Falagas ME , Vouloumanou EK , Samonis G et al. Fosfomycin . Clin Microbiol Rev 2016 ; 29 : 321 – 47 . Google Scholar CrossRef Search ADS 17 Pulcini C , Bush K , Craig WA et al. Forgotten antibiotics: an inventory in Europe, the United States, Canada, and Australia . Clin Infect Dis 2012 ; 54 : 268 – 74 . Google Scholar CrossRef Search ADS 18 Hendlin D , Stapley EO , Jackson M et al. Phosphonomycin, a new antibiotic produced by strains of streptomyces . Science 1969 ; 166 : 122 – 3 . Google Scholar CrossRef Search ADS 19 Podolsky SH. Antibiotics and the social history of the controlled clinical trial, 1950-1970 . J Hist Med Allied Sci 2010 ; 65 : 327 – 67 . Google Scholar CrossRef Search ADS 20 Mouton JW , Ambrose PG , Canton R et al. Conserving antibiotics for the future: new ways to use old and new drugs from a pharmacokinetic and pharmacodynamic perspective . Drug Resist Updat 2011 ; 14 : 107 – 17 . Google Scholar CrossRef Search ADS 21 Theuretzbacher U , Van Bambeke F , Canton R et al. Reviving old antibiotics . J Antimicrob Chemother 2015 ; 70 : 2177 – 81 . Google Scholar CrossRef Search ADS 22 Clinical and Laboratory Standards Institute . Performance Standards for Antimicrobial Susceptibility Testing: Twenty-Fifth Informational Supplement M100-S26 . CLSI, Wayne, PA, USA , 2016 . 23 Walsh CC , McIntosh MP , Peleg AY et al. In vitro pharmacodynamics of fosfomycin against clinical isolates of Pseudomonas aeruginosa . J Antimicrob Chemother 2015 ; 70 : 3042 – 50 . Google Scholar CrossRef Search ADS 24 Magiorakos AP , Srinivasan A , Carey RB et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance . Clin Microbiol Infect 2012 ; 18 : 268 – 81 . Google Scholar CrossRef Search ADS 25 Bergen PJ , Bulitta JB , Forrest A et al. Pharmacokinetic/pharmacodynamic investigation of colistin against Pseudomonas aeruginosa using an in vitro model . Antimicrob Agents Chemother 2010 ; 54 : 3783 . Google Scholar CrossRef Search ADS 26 Pfausler B , Spiss H , Dittrich P et al. Concentrations of fosfomycin in the cerebrospinal fluid of neurointensive care patients with ventriculostomy-associated ventriculitis . J Antimicrob Chemother 2004 ; 53 : 848 – 52 . Google Scholar CrossRef Search ADS 27 Joukhadar C , Klein N , Dittrich P et al. Target site penetration of fosfomycin in critically ill patients . J Antimicrob Chemother 2003 ; 51 : 1247 – 52 . Google Scholar CrossRef Search ADS 28 Schintler MV , Traunmüller F , Metzler J et al. High fosfomycin concentrations in bone and peripheral soft tissue in diabetic patients presenting with bacterial foot infection . J Antimicrob Chemother 2009 ; 64 : 574 – 8 . Google Scholar CrossRef Search ADS 29 Sauermann R , Karch R , Langenberger H et al. Antibiotic abscess penetration: fosfomycin levels measured in pus and simulated concentration-time profiles . Antimicrob Agents Chemother 2005 ; 49 : 4448 – 54 . Google Scholar CrossRef Search ADS 30 Gonzalez D , Schmidt S , Derendorf H. Importance of relating efficacy measures to unbound drug concentrations for anti-infective agents . Clin Microbiol Rev 2013 ; 26 : 274 – 88 . Google Scholar CrossRef Search ADS 31 Roussos N , Karageorgopoulos DE , Samonis G et al. Clinical significance of the pharmacokinetic and pharmacodynamic characteristics of fosfomycin for the treatment of patients with systemic infections . Int J Antimicrob Agents 2009 ; 34 : 506 – 15 . Google Scholar CrossRef Search ADS 32 Parker SL , Frantzeskaki F , Wallis SC et al. Population pharmacokinetics of fosfomycin in critically ill patients . Antimicrob Agents Chemother 2015 ; 59 : 6471 – 6 . Google Scholar CrossRef Search ADS 33 Harigaya Y , Bulitta JB , Forrest A et al. Pharmacodynamics of vancomycin at simulated epithelial lining fluid concentrations against methicillin-resistant Staphylococcus aureus (MRSA): implications for dosing in MRSA pneumonia . Antimicrob Agents Chemother 2009 ; 53 : 3894 – 901 . Google Scholar CrossRef Search ADS 34 Forest Pharmaceuticals Inc . Monurol (Fosfomycin) Package Insert . St Louis, MO, USA : Forest Pharmaceuticals Inc ., 2014 . PubMed PubMed 35 Falagas ME , Roussos N , Gkegkes LD et al. Fosfomycin for the treatment of infections caused by Gram-positive cocci with advanced antimicrobial drug resistance: a review of microbiological, animal and clinical studies . Expert Opin Investig Drugs 2009 ; 18 : 921 – 44 . Google Scholar CrossRef Search ADS 36 Falagas ME , Giannopoulou KP , Kokolakis GN et al. Fosfomycin: use beyond urinary tract and gastrointestinal infections . Clin Infect Dis 2008 ; 46 : 1069 – 77 . Google Scholar CrossRef Search ADS 37 Michalopoulos AS , Livaditis IG , Gougoutas V. The revival of fosfomycin . Int J Infect Dis 2011 ; 15 : e732 – 9 . Google Scholar CrossRef Search ADS 38 Pan A-J , Mei Q , Ye Y et al. Validation of the mutant selection window hypothesis with fosfomycin against Escherichia coli and Pseudomonas aeruginosa: an in vitro and in vivo comparative study . J Antibiot 2017 ; 70 : 166 – 73 . Google Scholar CrossRef Search ADS 39 Traunmuller F , Popovic M , Konz KH et al. A reappraisal of current dosing strategies for intravenous fosfomycin in children and neonates . Clin Pharmacokinet 2011 ; 50 : 493 – 503 . Google Scholar CrossRef Search ADS 40 Docobo-Pérez F , Drusano GL , Johnson A et al. Pharmacodynamics of fosfomycin: insights into clinical use for antimicrobial resistance . Antimicrob Agents Chemother 2015 ; 59 : 5602 – 10 . Google Scholar CrossRef Search ADS 41 VanScoy BD , McCauley J , Ellis-Grosse EJ et al. Exploration of the pharmacokinetic-pharmacodynamic relationships for fosfomycin efficacy using an in vitro infection model . Antimicrob Agents Chemother 2015 ; 59 : 7170 – 7 . Google Scholar CrossRef Search ADS 42 Tam VH , Schilling AN , Neshat S et al. Optimization of meropenem minimum concentration/MIC ratio to suppress in vitro resistance of Pseudomonas aeruginosa . Antimicrob Agents Chemother 2005 ; 49 : 4920 – 7 . Google Scholar CrossRef Search ADS 43 Tam VH , Louie A , Deziel MR et al. The relationship between quinolone exposures and resistance amplification is characterized by an inverted U: a new paradigm for optimizing pharmacodynamics to counterselect resistance . Antimicrob Agents Chemother 2007 ; 51 : 744 – 7 . Google Scholar CrossRef Search ADS 44 Bergan T , Thorsteinsson SB , Albini E. Pharmacokinetic profile of fosfomycin trometamol . Chemotherapy 1993 ; 39 : 297 – 301 . Google Scholar CrossRef Search ADS 45 Matzi V , Lindenmann J , Porubsky C et al. Extracellular concentrations of fosfomycin in lung tissue of septic patients . J Antimicrob Chemother 2010 ; 65 : 995 – 8 . Google Scholar CrossRef Search ADS 46 Drusano GL , Liu W , Fikes S et al. Interaction of drug- and granulocyte-mediated killing of Pseudomonas aeruginosa in a murine pneumonia model . J Infect Dis 2014 ; 210 : 1319 – 24 . Google Scholar CrossRef Search ADS 47 Rodriguez-Rojas A , Couce A , Blazquez J. Frequency of spontaneous resistance to fosfomycin combined with different antibiotics in Pseudomonas aeruginosa . Antimicrob Agents Chemother 2010 ; 54 : 4948 – 9 . Google Scholar CrossRef Search ADS 48 Rodriguez-Rojas A , Macia MD , Couce A et al. Assessing the emergence of resistance: the absence of biological cost in vivo may compromise fosfomycin treatments for P. aeruginosa infections . PLoS One 2010 ; 5 : e10193 . Google Scholar CrossRef Search ADS 49 Castañeda-García A , Rodríguez-Rojas A , Guelfo JR et al. The glycerol-3-phosphate permease GlpT is the only fosfomycin transporter in Pseudomonas aeruginosa . J Bacteriol 2009 ; 191 : 6968 – 74 . Google Scholar CrossRef Search ADS 50 Kahan FM , Kahan JS , Cassidy PJ et al. The mechanism of action of fosfomycin (phosphonomycin) . Ann N Y Acad Sci 1974 ; 235 : 364 – 86 . Google Scholar CrossRef Search ADS 51 MacLeod DL , Velayudhan J , Kenney TF et al. Fosfomycin enhances the active transport of tobramycin in Pseudomonas aeruginosa . Antimicrob Agents Chemother 2012 ; 56 : 1529 – 38 . Google Scholar CrossRef Search ADS 52 MacLeod DL , Barker LM , Sutherland JL et al. Antibacterial activities of a fosfomycin/tobramycin combination: a novel inhaled antibiotic for bronchiectasis . J Antimicrob Chemother 2009 ; 64 : 829 – 36 . Google Scholar CrossRef Search ADS 53 Kunakonvichaya B , Thirapanmethee K , Khuntayaporn P et al. Synergistic effects of fosfomycin and carbapenems against carbapenem-resistant Pseudomonas aeruginosa clinical isolates . Int J Antimicrob Agents 2015 ; 45 : 556 – 7 . Google Scholar CrossRef Search ADS 54 Lepak AJ , Zhao M , VanScoy B et al. In vivo pharmacokinetics and pharmacodynamics of ZTI-01 (fosfomycin for injection) in the neutropenic murine thigh infection model against Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa . Antimicrob Agents Chemother 2017 ; 61 . © The Author(s) 2018. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please email: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

Journal

Journal of Antimicrobial ChemotherapyOxford University Press

Published: Mar 1, 2018

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off