Pharmacodynamics of Vancomycin at Simulated Epithelial LiningFluid Concentrations against Methicillin-ResistantStaphylococcus aureus (MRSA): Implications for
Dosing in MRSA Pneumonia�
Yoriko Harigaya,1† Jurgen B. Bulitta,1,2 Alan Forrest,1,2 George Sakoulas,4Alan J. Lesse,3,5 Joseph M. Mylotte,3 and Brian T. Tsuji1,6*
Laboratory for Antimicrobial Pharmacodynamics, School of Pharmacy and Pharmaceutical Sciences and The New York State Center ofExcellence in Bioinformatics & Life Sciences, University at Buffalo, State University of New York, Buffalo, New York1;
Ordway Research Institute, Albany, New York2; School of Medicine and Biomedical Sciences, University at Buffalo,State University of New York, Buffalo, New York3; Department of Medicine, Division of Infectious Diseases,
New York Medical College, Valhalla, New York4; VA Western New York Healthcare System, Buffalo,New York5; and Roswell Park Cancer Institute, Department of Medicine, Buffalo, New York6
Received 30 November 2008/Returned for modification 24 March 2009/Accepted 3 June 2009
Little is known regarding killing activity of vancomycin against methicillin (meticillin)-resistant Staphylo-coccus aureus (MRSA) in pneumonia since the extent of vancomycin penetration into epithelial lining fluid(ELF) has not been definitively established. We evaluated the impact of the extent of ELF penetration onbacterial killing and resistance by simulating a range of vancomycin exposures (24-h free drug area under theconcentration-time curve [ƒAUC24]/MIC) using an in vitro pharmacodynamic model and population-basedmathematical modeling. A high-dose, 1.5-g-every-12-h vancomycin regimen according to American ThoracicSociety/Infectious Diseases Society of America guidelines (trough concentration, 15 mg/liter) with simulatedELF/plasma penetration of 0, 20, 40, 60, 80, or 100% (ƒAUC24/MIC of 0, 70, 140, 210, 280, or 350) was evaluatedagainst two agr-functional, group II MRSA clinical isolates obtained from patients with a bloodstream infection(MIC � 1.0 mg/liter) at a high inoculum of 108 CFU/ml. Despite high vancomycin exposures and 100% penetration,all regimens up to a ƒAUC24/MIC of 350 did not achieve bactericidal activity. At regimens of <60% penetration(ƒAUC24/MIC < 210), stasis and regrowth occurred, amplifying the development of intermediately resistantsubpopulations. Regimens simulating >80% penetration (ƒAUC24/MIC > 280) suppressed development of resis-tance. Resistant mutants amplified by suboptimal vancomycin exposure displayed reduced rates of autolysis (TritonX-100) at 72 h. Bacterial growth and death were well characterized by a Hill-type model (r2 > 0.984) and apopulation pharmacodynamic model with a resistant and susceptible subpopulation (r2 > 0.965). Due to theemergence of vancomycin-intermediate resistance at a ƒAUC24/MIC of <210, exceeding this exposure breakpoint inELF may help to guide optimal dosage regimens in the treatment of MRSA pneumonia.
Nosocomial pneumonia remains a significant cause of mor-bidity and mortality. Recently the American Thoracic Societyand the Infectious Diseases Society of America (ATS/IDSA)(1) proposed vancomycin trough concentrations of 15 to 20mg/liter for health care- and ventilator-associated (HAP andVAP) methicillin (meticillin)-resistant Staphylococcus aureus(MRSA) pneumonia. This recommendation is derived fromevidence suggesting that the vancomycin 24-h area-under-the-concentration-time-curve-to-MIC (AUC/MIC) ratio of �350is predictive of cure in patients with S. aureus pneumonia andrecent concerns regarding vancomycin’s antistaphylococcal ac-tivity, such as the MIC “creep,” low rate of killing, and increas-ing reports of treatment failure (14, 26, 31, 32). However, therehas been significant debate as to whether high-dose vancomy-
cin is beneficial, since some studies have shown that greaterexposure is not correlated with a more favorable hospital out-come and is associated with increased nephrotoxicity in pa-tients receiving high-dose vancomycin regimens (9, 11, 22).
Additionally, little is known regarding the degree of penetra-tion of vancomycin into epithelial lining fluid (ELF) from plasma.Although an earlier study by Lamer et al. (19) provided evidencethat vancomycin penetrates poorly into ELF (free vancomycin inELF/plasma was less than 30%), a recent study by G. L. Drusanoet al. (7a) suggests that ELF penetration may be higher (freevancomycin in ELF/plasma was approximately 100%). Adding tothis discrepancy is the lack of information regarding vancomycin’skilling activity and ability to suppress resistance at clinicallyachievable concentrations at the site of infection and the relation-ship between the early physiologic changes in S. aureus that occurdue to suboptimal exposure.
The objective of this investigation was to simulate humanconcentration-time profiles of vancomycin in ELF and deter-mine the proclivity toward developing reduced glycopeptidesusceptibility, tolerance, and phenotypic alterations using an invitro pharmacodynamic model of MRSA infection and math-ematical modeling.
* Corresponding author. Mailing address: Laboratory for Antimi-crobial Pharmacodynamics, University at Buffalo, School of Pharmacyand Pharmaceutical Sciences, State University of New York, Buffalo,NY 14260. Phone: (716) 881-7543. Fax: (716) 849-6890. E-mail: [email protected].
† Present address: Food and Drug Administration, Center for DrugEvaluation and Research, Silver Spring, MD.
� Published ahead of print on 13 July 2009.
3894
(This work was presented in part at the 47th Annual Meet-ing of the Interscience Conference on Antimicrobial Agentsand Chemotherapy, Chicago, IL, September 2007.)
MATERIALS AND METHODS
Bacterial isolates. Two clinical MRSA isolates (S203 and S204) obtained frompatients with bloodstream infections at the Buffalo VA Health System of West-ern New York in 2003 were evaluated. All studies were conducted in accordancewith the institutional review board at the University at Buffalo and the VAWestern New York Healthcare System. Patient isolates were exempt from en-rollment. Both isolates belonged to accessory gene regulator (agr) group II andwere delta-hemolysin positive. Delta-hemolysin production was used as a surro-gate marker of agr function using methodology described previously (30, 39).
Antibiotics and medium. Vancomycin analytical-grade powder was commer-cially purchased (Sigma Chemical Company, St. Louis, MO). Fresh solutionswere prepared in the morning prior to each experimental run. Mueller-Hintonbroth (Difco Laboratories, Detroit, MI) supplemented with calcium (25 mg/liter)and magnesium (12.5 mg/liter) was utilized for susceptibility testing. Brain heartinfusion (BHI) agar and BHI broth (Difco Laboratories, Detroit, MI) were usedfor all in vitro model experiments. Trypticase soy agar with 5% sheep blood agar(TSA II; Becton-Dickinson Diagnostics, Sparks, MD) was utilized for quantifi-cation of bacteria.
Determining alterations in MIC. Vancomycin MICs were determined by brothmicrodilution according to the Clinical and Laboratory Standards Institute inquadruplicate prior to all in vitro model experiments. Quantitative cultures weredetermined on BHI agar plates to allow detection of the susceptible populationand on BHI agar containing 2, 4, or 6 mg/liter vancomycin to quantify theresistant subpopulations at 0, 24, 48, and 72 h. Colonies were enumerated after48 h of incubation at 37°C and plotted as a function of time for both isolates anddrug regimens tested using the SigmaPlot 9 software program. Changes in MICswere determined using the vancomycin Etest strip, which were placed on BHIplates inoculated with suspensions adjusted to a 0.5 McFarland standard toconfirm the emergence of resistance. The intersection of the elliptical inhibitionzone and the E-strip was read according to the Etest manufacturer’s instructions.
IVPM. An in vitro pharmacodynamic model (IVPM) consisting of a one-compartment 500-ml glass chamber (working model volume, 250 ml broth) withmultiple ports for the removal of BHI broth, delivery of antibiotic, and collectionof bacterial and antimicrobial samples was utilized (39). Briefly, overnight cul-tures of MRSA isolates were diluted in fresh BHI broth and adjusted to a 1.0McFarland turbidity. The suspension was added to BHI broth in the IVPM,yielding a final volume of 250 ml and a starting inoculum over 108 CFU/ml. Serialsamples were taken at 0 (predose), 0.5, 1, 2, 4, 6, 8, 24, 28, 32, 48, 52, 56, and 72 hto assess viable counts. Antimicrobial carryover was minimized by centrifugingthe bacterial samples at 10,000 � g for 5 min and then reconstituting them withsterile normal saline to their original volumes, followed by subsequent serialdilution (10- to 100,000-fold). Viable bacterial counts were determined by plating100-�l samples of each diluted sample on BHI agar, using an automated spiraldispenser (Automatic Spiral Plater; Microbiology International, Rockville, MD).Plated samples were incubated at 37°C for 24 h, and colony counts (log10
CFU/ml) were determined by using an automated bacterial colony counter(aCOLyte; Synbiosis, Frederick, MD). Colony count (log10 CFU/ml) data wereplotted as a function of time for all tested drug regimens for each isolate.Bactericidal activity at 72 h was defined as a 99.9% reduction in colony countscompared to the starting inoculum.
Simulated regimens. A vancomycin high-dose regimen of 1.5 g every 12 h(q12h) was selected based on a trough concentration of 15 mg/liter (total van-comycin concentration in plasma) as recommended by ATS/IDSA guidelines forHAP/VAP and the IDSA/American Society of Health-System Pharmacists/So-ciety of Infectious Diseases Pharmacists vancomycin therapeutic monitoringguidelines (1, 28) with the following pharmacokinetic values: total plasma max-imum drug concentration (Cmax)/MIC of 60 mg/liter, total plasma minimum drugconcentration (Cmin)/MIC of 15 mg/liter, and total plasma AUC/MIC from 1 to24 h (MIC0-24) of 778 based on a half-life of 6 h. Using a protein binding levelof 55% for vancomcyin in plasma, this yields the following values for this regi-men: free drug Cmax (ƒCmax)/MIC of 27, free drug Cmin (fCmin)/MIC of 6.8, andfree drug AUC (ƒAUC)/MIC0-24 of 350 using the linear trapezoidal rule. Thisregimen was then divided according to percent penetration into ELF fromplasma according to the following studies characterizing vancomycin pharmaco-kinetics.
Recent data by Drusano et al. (47th ICAAC, A-2151, 2007) show a high extentof penetration of approximately 100% for vancomycin into ELF (total drug AUCin ELF divided by ƒAUC in plasma), whereas a low penetration of 20% (based
on concentration ratios) was reported by Lamer et al. (19). Therefore, to con-sider a wide range of ELF/plasma penetration ratios, which may also be affectedby the disease state, we simulated penetration into ELF (ƒAUC24/MIC in pa-rentheses) of 20% (70), 40% (140), 60% (210), 80% (280), or 100% (350) of the1.5-g q12h regimen, which is shown in Table 1. All simulated exposure profileswere administered q12h throughout the 72-h period of the study. All experimentswere performed in duplicate.
Autolysis. Autolysis profiles using Triton X-100 were determined spectropho-tometrically, as described previously (30). Briefly, MRSA isolates after a 72-hvancomycin exposure in the IVPM were evaluated for autolysis. Samples werepelleted using a centrifuge and washed with ice-cold Tris-EDTA (4°C). Pelletswere resuspended in Tris-HCl buffer at pH 7.2 (0.05 M) with 0.05% TritonX-100. Suspensions were adjusted to 0.5 optical density at 620 nm (OD620) andincubated at 37°C for 8 h. Samples were obtained every 2 h to measure OD620sup to 8 h. The ratio of the area under the absorbance curve over 8 h for thedrug-exposed isolates (AUCdrug absorbance) compared to the AUC for no change(100%) in absorbance over 8 h (AUCstasis absorbance � OD620 � 8 h) was calcu-lated. To quantify the effect of various vancomycin dosage regimens on the extentof autolysis, the “extent of autolysis” was calculated as AUCdrug absorbance/AUCstasis absorbance.
Pharmacokinetic analysis. Samples for pharmacokinetic analysis were ob-tained at 0, 0.5, 1, 2, 4, 6, 8, 24, 28, 32, 48, 52, 56, and 72 h. Vancomycinconcentrations were determined by standard agar diffusion bioassay proceduresusing Mueller-Hinton agar with Micrococcus luteus ATCC 9341 as an indicatororganism (38). Standards and samples were tested in quadruplicate using blank1⁄4-in. disks saturated with 20 �l of the solution. Concentrations of 0.5 to 30mg/liter were used as standard curves for vancomycin. The limit of detection forvancomycin was 0.75 mg/liter. The peak concentration (Cmax), trough concen-tration (Cmin), and elimination half-life (t1/2) were calculated from the concen-tration-time profiles. The AUC0–24 was calculated using the linear trapezoidalmethod in the WinNonlin software program (version 5.0.1; Pharsight, Cary, NC).
Pharmacokinetic/pharmacodynamic (PK/PD) analysis. (i) Area-based method.An integrated PK/PD area measure (log ratio area) was applied to all CFUdata to quantify the drug effect as shown in equation 1, as described previ-ously (40):
Log ratio area � log10� AUCFUdrug
AUCFUgrowthcontrol� (1)
AUCFU (area under the CFU-versus-time curve) was calculated on a linearscale from 0 to 72 h using the linear trapezoidal rule in WinNonlin. Usingnonlinear regression, a four-parameter concentration-effect Hill-type model wasfit to the effect parameter in the Systat (Richmond, VA) software program(version 11) as described previously (40):
E � E0 �Emax � �fAUC:MIC�H
�EC50�H � �fAUC:MIC�H (2)
where the dependent variable (E) is the log ratio area, E0 is the effect measuredat a drug concentration of zero, Emax is the maximal effect, EC50 is the fAUC/MIC ratio for which there is 50% maximal effect, and H is the Hill or sigmoidicityconstant. The parameters of this Hill equation were estimated using maximum-likelihood methods.
(ii) Population PK/PD modeling. Candidate models were simultaneously fit toall CFU-versus-time data of both strains in the NONMEM VI software program
TABLE 1. Pharmacokinetic profiles of vancomycin in ELFsimulated in an in vitro pharmacodynamic modela
a A vancomycin regimen of 1,500 mg q12h was simulated, based on a totaltrough concentration in plasma of 15 mg/liter (assuming a protein binding levelof 55%) according to ATS/IDSA and IDSA/ASHP/SIDP guidelines (1, 28).
b The extent of penetration is based on the simulated vancomycin AUC in ELFdivided by the AUC in plasma.
c All simulated regimens were administered q12h.
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(level 1.2; NONMEM Project Group, Icon Development Solutions, Ellicott City,MD) with the first-order conditional-estimation methods and an additive errormodel on a logarithmic scale. Model discrimination was based on the individualcurve fits, NONMEM’s objective function, and the model stability during esti-mation.
The drug effect was modeled as either inhibition of growth or stimulation ofbacterial killing. Models with one, two, or three subpopulations of differentsusceptibilities for each strain were considered.
Bacterial growth was described by a saturable growth function as described pre-viously (24). We reparameterized this growth model and estimated the shortestgrowth t1/2 at low bacterial concentrations (t1/2,low CFU/ml) and the maximum popu-lation size (POPmax). The maximum growth rate constant (kg) at low CFU/ml, themaximum velocity of bacterial growth (VGmax; unit, CFU/ml/h), and the bacterialconcentration (CFUm) associated with 50% of VGmax can be calculated fromt1/2,low CFU/ml, POPmax, and first-order natural death rate constant, kd:
kg �ln�2
t1/2,low CFU/ml(3)
CFUm �POPmax
kg
kd� 1
(4)
VGmax � CFUm � kg (5)
These equations were derived from the steady-state solution of the model fromMeagher et al. (24) in the absence of an antibiotic. To describe a lower rate ofgrowth of the resistant subpopulation than of the susceptible subpopulation, theratio of VGmax for the resistant subpopulation divided by VGmax for the suscep-tible subpopulation was described by frVGmax,R. A transit compartment approachwas used to describe a slower initial rate of bacterial growth. The mean transittime for the lag process was described by MTTlag. This approach is comparableto previous implementations of lag time (37).
In the final model, inhibition of bacterial growth for the susceptible(INHgrowth,S) and resistant (INHgrowth,R) subpopulation by the vancomycin con-centration (CDrug) was described by different drug concentrations causing 50% ofmaximal inhibition for the susceptible (IC50,S) and resistant (IC50,R) subpopula-tions as described previously (4, 7, 8):
INHgrowth,S/R � 1 �CDrug
IC50,S/R � CDrug(6)
This yields the following set of (differential) equations for a model with twosubpopulations (ADrug, concentration of vancomycin in the system; CFUS,lag
[CFUR,lag], concentration of susceptible [resistant] bacteria in the lag compart-ment; CFUS [CFUR], concentration of replicating susceptible [replicating resis-tant] bacteria; CFUall, bacterial concentration of all subpopulations):
The total initial inoculum and the initial inoculum of the resistant population(CFUoR) were estimated, and the initial inoculum of the susceptible population(CFUoS) was calculated as the difference in the former two estimates. Initialconditions for equations 7, 10, and 11 were zero. A clearance (CL) of 0.5 ml/minand volume of distribution (V) of 250 ml yield an elimination half-life (rate
constant, kel) of approximately 6 h. Loss of bacteria due to washout from theunfiltered system was described by kel.
RESULTS
Impact of escalating vancomycin exposure on total and re-sistant bacterial populations. The vancomycin MICs ofMRSA S203 and S204 were 1.0 mg/liter. Vancomycin dis-played bacteriostatic activity against both isolates in alltested regimens, with maximal reductions of 1.7 log10
CFU/ml from the baseline at all exposures up to a ƒAUC24/MIC of 350 (100% penetration) at 72 h (Fig. 1A and B).Regrowth was present at low exposures, ƒAUC24/MIC of 70(20% penetration), for both clinical isolates. Bacterialcounts from nadir to 72 h increased for regimens withƒAUC24/MIC of 70 by 2.73 log10 CFU/ml for S203 and by1.53 log10 CFU/ml for S204 (Fig. 1A and B). Increasingnumbers of resistant mutants appeared at lower simulatedexposures of vancomycin in ELF, since significant growthwas present on vancomycin plates containing 2 mg/liter inagar (Fig. 1C and D). Amplification of resistant mutants wasobserved at a ƒAUC24/MIC as high as 210 (60% penetra-tion). Resistant mutants exceeded 60% of the total popula-tion at 72 h, with growth up to 6.5 log10 CFU/ml on vanco-mycin plates with 2 mg/liter after vancomycin exposure. Allexposures amplified resistant mutants growing on agar with2 mg/liter vancomycin, while only lower exposures ofƒAUC24/MIC of �140 amplified intermediately resistantmutants displaying growth on 4 and 6 mg/liter of vancomycincontaining agar.
Interestingly, for both MRSA isolates, exposure to aƒAUC24/MIC of �280 (80% penetration) suppressed the de-velopment of resistance throughout the 72-h experiment, andno growth was present on 4 and 6 mg/liter of vancomycin-containing agar. Postexposure MICs at 72 h for the ƒAUC 0,70, 140, 210, 280, and 350 regimens were 1.0, 6.0, 6.0, 6.0, 6.0,and 2.0 mg/liter for S203 and 1.0, 6.0, 6.0, 4.0, 2.0, and 2.0mg/liter for S204, respectively. Therefore, under selective drugpressure, all exposure profiles (except after exposure to aƒAUC/MIC of 350 and a ƒAUC/MIC of 280 for S204) dem-onstrated the occurrence of vancomycin-intermediate resis-tance by 72 h.
Modeling drug effect on bacterial growth and death andpharmacokinetics. Analysis of pharmacodynamics revealed ex-cellent model fits (r2 0.98) of the data to the Hill-type model,since vancomycin killing occurred in an exposure-dependentmanner against both strains (Fig. 1E and F).
The population PK/PD analysis showed that models whichimplemented the drug effect as inhibition of growth performedbetter than models that specified the drug effect as stimulationof death. A model with three bacterial subpopulations pro-vided better curve fits for one of the six dosage regimens forone of the two strains. The three-subpopulation model pro-vided in part physiologically unreasonable parameter estimates(extremely low IC50,S), and this model was less robust than amodel with two subpopulations. Since the simpler model pro-vided excellent curve fits (Fig. 2) for both strains, we selectedthe model with two subpopulations as the final model. A linearregression of the observed versus the individual [population]
3896 HARIGAYA ET AL. ANTIMICROB. AGENTS CHEMOTHER.
fitted log10 (CFU/ml) yielded a slope of 1.004 [0.996], interceptof �0.031 [�0.014], and r2 value of 0.965 [0.923] for the modelwith two subpopulations.
Figure 3 shows the structure of the final model. For strain S204,both the susceptible and resistant subpopulations were estimatedto have higher IC50 values than the respective population of strainS203 (Table 2). However, the growth half-life of the resistantpopulation was longer for strain S204 (133 min) than for strainS203 (100 min). Parameter estimates were reasonably precise(Table 2). Since the lowest studied trough concentration wasapproximately fourfold higher than the IC50,S values and since theIC50,R values were (notably) higher than the highest studied peakconcentration, standard errors for the IC50 terms were larger.Standard curves for vancomycin bioassays were linear over the
FIG. 1. The killing activities of simulated vancomycin regimens in an in vitro infection model profiling the total population over timeversus S203 or S204 (A and B) or a resistant population growing on vancomycin 2-mg/liter BHI agar (C and D). The pharmacodynamicrelationship between the log ratio area and the ƒAUC/MIC (R2 represents the coefficient of determination) is shown in the bottom panels(E and F).
FIG. 2. Observed and fitted bacterial counts for simulated vanco-mycin exposures in ELF against S203 (A) or S204 (B).
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concentration between 2 and 25 mg/liter (r2 � 0.882) when thestandards were prepared in BHI medium. The lower limit ofdetection for vancomycin was 0.75 mg/liter. Observed pharmaco-kinetic parameters were within 20% of targeted values.
Alterations in autolysis secondary to vancomycin exposure.Resistant mutants displayed defective autolysis profiles aftersuboptimal exposure to vancomycin (Fig. 4A and B). The mu-tant strains (MIC � 2 mg/liter) showed marked autolysis inhi-
bition. At the 2-h time point, subsequent differences of reduc-tion in initial absorbance between a ƒAUC/MIC of 350 and aƒAUC/MIC of 70 for S203 and S204 were 46.95 and 10.24,respectively. Interestingly, a linear relationship between van-comycin exposure (ƒAUC/MIC) and the extent of autolysis ofS. aureus was found (Fig. 4C and D).
DISCUSSION
Despite more than 50 years of clinical use of vancomycin,knowledge regarding the degree of penetration into ELF hasbeen lacking, with only two studies, limited by a small numberof patients and single-time-point pharmacokinetic compari-sons, addressing this issue (5, 19, 35). Recently publishedguidelines (1, 28, 38) support the notion of poor vancomycinpenetration into ELF, citing that vancomycin is to be dosed toachieve high trough levels of 15 to 20 mg/liter for MRSApneumonia, which has been adopted by some clinicians for allinfection sources, with some institutions utilizing vancomycindoses of 4 g/day (22, 25). Although increased exposure ofvancomycin is driven by the perceived poor penetration ofvancomycin in pneumonia and the necessity of achieving agreater drug exposure in ELF, nephrotoxicity has been re-ported at these high exposures (9, 12, 16, 22). A recent phar-macokinetic study by Drusano et al. (47th ICAAC, A-2151,2007) suggests that vancomycin penetration into ELF com-pared to that into plasma may indeed be higher than onceanticipated, at approximately 100% of the free drug AUC inplasma. Therefore, much still remains unknown regarding the
FIG. 3. Structure of the final model with a susceptible and a resistantsubpopulation describing the effect of vancomycin as inhibition (IC50,Sand IC50,R) of the saturable growth function for each subpopulation. Thelag compartments are linked to the compartments for replicating cells viaa first-order rate constant (klag � 1/MTTlag). Arrows for loss of bacteriadue to washout from the unfiltered in vitro model are not shown. SeeMaterials and Methods for further explanation of parameters.
FIG. 4. Postexposure isolates of MRSA S203 (A) or MRSA S204 (B) for each vancomycin regimen simulated (as shown in the key to thesymbols) in the IVPM were obtained at 72 h and subsequently evaluated for differences in autolysis profiles over 8 h. The pharmacodynamicrelationship between the extent of autolysis and the ƒAUC/MIC for S203 (C) or for S204 (D) is shown.
3898 HARIGAYA ET AL. ANTIMICROB. AGENTS CHEMOTHER.
impact of escalating dose intensity and the selection of optimaldosage regimens in MRSA pneumonia.
The findings of the present study suggest that guideline-recommended dosing regimens of vancomycin with high-doseintensity (1, 28), even under situations of 100% penetrationinto ELF, may not provide the optimal exposure necessary toachieve bactericidal activity. Even more importantly, undersituations of low penetration against a high bacterial inoculumof MRSA, the propensity to develop resistant mutants of S.aureus may be amplified. A high bacterial density of 108
CFU/ml was employed in this study to simulate MRSA infec-tion in pneumonia given that the inoculum size influencesvancomycin pharmacodynamics (20, 20a, 38). While decreasedkilling of a higher density of organisms is perhaps intuitive, thelack of activity at high inocula may also be explained by apropensity for a heterogeneous inoculum to harbor resistantmutants which are amplified secondary to drug exposure (36).This is particularly important if the initial inoculum exceedsthe inverse of the mutation frequency. (15) We determinedthat there was amplification of resistant subpopulations sec-ondary to low vancomycin penetration and exposure in ELFagainst this inoculum. The time course of bacterial killing andregrowth of resistant bacteria was well characterized by the pro-posed population PK/PD model. Importantly, the IC50 of theresistant subpopulation was estimated to be notably above thehighest simulated unbound peak concentration. These findingsmay potentially explain the high rate of failure of vancomycinmonotherapy in infections associated with high bacterial density,such as pneumonia and endocarditis (11, 21, 26, 32).
The current study also highlights the recent discussion sur-rounding AUC/MIC targets and breakpoints for vancomycin.The ATS/IDSA and recent American Society of Health-Sys-tem Pharmacists/IDSA/Society of Infectious Diseases Pharma-cists vancomycin therapeutic monitoring guidelines recom-mend trough levels for vancomycin of 15 to 20 mg/ml and an
AUC/MIC ratio of �400 as the optimal serum concentrationtarget (1, 28). Therefore, to achieve these targets in vitro, wesimulated a 1.5 g q12h regimen and the following pharmaco-kinetic parameters in plasma: ƒAUC/MIC ratio of 350, anƒCmax/MIC ratio of 27 mg/liter, and an ƒCmin/MIC ratio of 6.8mg/liter. Accounting for vancomycin protein binding (55%),we simulated free-drug concentrations, which can be extrapo-lated to a total AUC/MIC ratio of approximately 778, a totalCmax/MIC ratio of 60 mg/liter, and a total Cmin/MIC ratio of 15mg/liter, in following the recommendations of the IDSA. In-terestingly, although the current study utilized two MRSA iso-lates with a MIC of 1 mg/liter, if the MRSA strain selecteddisplayed a MIC of 2 mg/liter, this exposure would decrease toan AUC/MIC of 389, which is below the recommended expo-sure breakpoint of 400. Furthermore, in situations of poorpenetration (20%) into ELF, the IDSA/ATS-recommendedregimen of a plasma trough concentration of 15 mg/liter wouldyield a free ELF trough concentration of 1.4 mg/liter, whichmay explain the rapid development of heterogeneous resis-tance in our in vitro model at this extent of penetration. Ad-ditionally, these data are supported by clinical data by Hidayatet al. (9), who determined that even when vancomycin troughconcentrations of 15 to 20 mg/liter were obtained, a signifi-cantly higher mortality rate was observed with patients infectedwith MRSA pneumonia or bacteremia with MICs of 1.5 to 2mg/liter than with patients infected with low-MIC strains (�1mg/liter). Taken together with vancomycin’s association withnephrotoxicity at high doses (22), the development of resis-tance in situations of poor ELF penetration as shown in thepresent study suggests that the use of combination therapy orantibiotics other than vancomycin may be warranted in MRSApneumonia.
Although the precise mechanism in S. aureus leading tovancomycin-intermediate resistance still remains unclear, al-terations in cell morphology and autolysis and global transcrip-
TABLE 2. Estimates for final population PK/PD model for vancomycin against MRSA strains S203 and S204
Parameter Symbol and/or unitEstimate (SE �%�)
MRSA S203 MRSA S204
Initial inoculum of total population Log10 CFUo 8.34 (0.8)a,b 8.34 (0.8)a,b
Initial inoculum of resistant population Log10 CFUoR 5.91 (5)a 5.55 (9)a
Maximum population size Log10 POPmax 9.98 (0.9)a 9.98 (0.9)a
Mean transit time for growth lag MTTlag (h) 0.01 (fixed)c 1.96 (45)Shortest growth half-life at low bacterial concentrations
for susceptible populationt1/2,low CFU/ml (min) 77.5 (17)d 61.4 (32)d
Shortest growth half-life at low bacterial concentrationsfor resistant population
t1/2,low CFU/ml,R (min) 100e 133e
Relative maximum velocity of growth for resistantcompared to susceptible populations
frVGmax,R 0.773 (16) 0.460 (36)
Natural death rate constant kd (h�1) 0.161 (27) 0.119 (32)Concn causing 50% of inhibition of growth for the
Concn causing 50% of inhibition of growth for theresistant population
IC50,R (mg/liter) 39.3 (32) 200 (89)
SD of additive residual error on log10 scale SDerr 0.208 (13)f 0.208 (13)f
a Population mean was shared between the two strains.b The standard deviation for the variability of log10 (CFUo) between runs was estimated to be 0.15 (69% standard error).c The MTTlag was estimated to be very small and was eventually fixed to 0.01 h for strain S203.d The coefficient of variation for the variability of growth half-life between runs was estimated to be 4.0% (63% standard error).e Calculated based on t1/2,low CFU/ml and frVGmax,R. The t1/2,low CFU/ml,R was not an estimated model parameter.f Estimate for residual error was shared between the two strains.
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tional changes involving the accessory gene regulator (agr)system have been proposed (6, 10, 13, 30, 33). Specifically,alterations in the autolytic pathway have been associated withthe development of vancomycin-intermediate resistance: inhi-bition of the autolytic pathway through the blockage of mureinhydrolases and mutations in the vraR operon, a two-compo-nent system which impacts cell wall synthesis, have been pro-posed as potential mechanisms (2, 17, 18, 27, 34). Buildingupon these findings, our results are the first to demonstrate aPK/PD, dose-response relationship for vancomycin dose inten-sity and autolysis: lower vancomycin exposures (ƒAUC/MIC)resulted in a lesser extent of autolysis in S. aureus from blood-stream infection. These findings reveal that suboptimal vanco-mycin dosing or penetration in ELF may be associated withearly phenotypic alterations correlated with the developmentof vancomycin-intermediate resistance. This is especially im-portant in situations of poor antimicrobial penetration againsta heterogeneous high bacterial inoculum, where bacterialgrowth, colonization, and quorum-sensing mechanisms maygreatly impact optimal antimicrobial therapy (29, 39, 41).
The current study utilized both Hill-type and populationpharmacodynamic models to characterize the pharmacody-namics of vancomycin against MRSA. A sigmoidal Hill-typemodel using an area-based method has been utilized previouslyin our laboratory and by other groups to characterize the effectof vancomycin killing against MRSA (23, 40). The drug effectin this model is described as the log ratio of the area under theCFU/ml curve for the treated regimen versus the respectivearea for the growth control. Therefore, this area-based methodhas the advantage that it accounts for the entire time course ofCFU counts as opposed to the change in viable counts relativeto the initial inoculum at a single time point (for example, at72 h). The Hill-type model showed that the maximal reductionof the area under the CFU-versus-time curve by vancomycinagainst MRSA was approximately �2 log10, which correspondsto a 99% reduction in the area of organisms. This is in agree-ment with vancomycin’s bacteriostatic pharmacodynamics.
The area-based method provided a robust and readily ac-cessible measure for the time-averaged drug effect in this in-vestigation and is recommended over point-based methods.However, this empirical method cannot predict the time courseof bacteria and does not account for the mechanism of bacte-rial killing, and we are not aware of a rational approach toextend the area ratio method to optimize combination antibi-otic regimens. Additionally, the area-based approach takes noaccount of “shape”: for example, two regimens with similarAUCs of CFU are counted as equivalent even if one drops toa nadir and is returning toward the control level by the end ofthe experiment and the other drops more slowly but continuesthroughout the study period. Therefore, the employed popu-lation PK/PD modeling approach can simulate the time courseof susceptible and resistant bacteria for other than the studieddosage regimens and can implement the mechanism(s) of drugaction. Additionally, such mathematical models present thefirst step toward building models that can describe and simu-late the time course of bacterial counts for rational develop-ment of antibiotic combination regimens.
The final mathematical model described vancomycin killingas inhibition of growth and contained two subpopulations withdifferent susceptibilities, which is in agreement with the mech-
anisms of action and resistance for vancomcyin. Of particularinterest, the two-subpopulation mathematical model appropri-ately characterized vancomycin’s bacterial killing and mecha-nisms involved as heterogeneous vancomycin-intermediate re-sistance. For example, since a high fraction of sensitivesubpopulations and a low fraction of resistant subpopulationsare contained within the initial inoculum of MRSA, it is onlyuntil low-level selective drug pressure causes the amplificationof resistant subpopulations, which is made evident by the shiftin MIC from susceptible to intermediate resistance. VanA-mediated resistance would require a third subpopulation in themathematical model; however, this rarely develops in thecourse of vancomycin therapy (3). More-complex mathemati-cal models will need to be developed to describe the pheno-typic and genotypic changes that are more likely to occurduring longer durations of vancomycin therapy.
The present study had potential limitations, including theuse of two clinical isolates, since more geographically diverseclinical isolates are needed in future studies. In addition, sincethe temporal profile of vancomycin pharmacokinetics in ELFhas not been fully elucidated for healthy volunteers or infectedpatients, the dynamic nature of concentrations in ELF toplasma could be only partly taken into account in the simulatedpharmacokinetics in the in vitro models. Although we at-tempted to account for this by simulating a range of penetra-tion levels from 20 to 100%, between-patient variability in drugdisposition may be particularly important for infected patientswith lung inflammation, where drug penetration may be higherand the rate of equilibration may be different. Additional stud-ies of animal models of pneumonia are needed to provideadditional data to assess the impact of vancomycin penetrationinto ELF on bacterial killing in vivo, since numerous factors,such as host defense mechanisms and bacterial toxins, maygreatly influence antimicrobial pharmacodynamics in vivo.
In conclusion, this study highlights the potential problemsassociated with suboptimal vancomycin exposures in pneumo-nia and ultimately may impact vancomycin susceptibility inMRSA. Our data suggest that the use of higher vancomycinexposure profiles, combination therapy, or alternative agentsmay be necessary to maintain optimal exposures in ELF tosuppress the amplification of resistance in MRSA pneumonia.Further in vivo studies are necessary to strengthen the trans-lation of these in vitro findings to humans before our resultsare applied to clinical practice to guide selection of optimalantimicrobial regimens against MRSA pneumonia.
ACKNOWLEDGMENTS
This study was funded by the University at Buffalo, State Universityof New York, Interdisciplinary Research Fund. J.B.B. was supportedby a postdoctoral fellowship from Johnson & Johnson.
We thank George Drusano for excellent insight into the pharmaco-kinetic design of this study. We thank Dung Ngo, Michael Ma, andChristina Hall for excellent technical assistance. We thank CorneliaLandersdorfer for critical comments in reviewing this manuscript.
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