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Use of Monte Carlo Simulation to Design an Optimized Pharmacodynamic Dosing Strategy for Meropenem

From the Center for Anti-Infective Research and Development (Dr. Kuti, Dr. Dandekar, Dr. Nightingale, Dr. Nicolau), Research Administration (Dr. Nightingale), and Department of Medicine, Division of Infectious Diseases (Dr. Nicolau), Hartford Hospital, Hartford, Connecticut.

Address for reprints: David P. Nicolau, PharmD, FCCP, Center for Anti-Infective Research and Development, Hartford Hospital, 80 Seymour Street, Hartford, CT 06112.

	ABSTRACT

TOP ABSTRACT METHOD RESULTS DISCUSSION CONCLUSION REFERENCES

 
Prolonging the infusion of meropenem over 3 hours increases the percentage of the dosing interval that drug concentrations remain above the minimum inhibitory concentration (MIC), thereby maximizing the pharmacodynamics of this agent and adhering to drug stability constraints. Monte Carlo simulation was employed to determine pharmacodynamic target attainment rates for several prolonged infusion (PI) meropenem dosage regimens as compared with the traditional 30-minute infusion (TI) against Enterobacteriaceae, Acinetobacter species, and Pseudomonas aeruginosa populations. Percent time above the MIC (%T>MIC) exposures for 1000 mg TI q8h, 2000 mg TI q8h, 500 mg PI q8h, 1000 mg PI q12h, 1000 mg PI q8h, 2000 mg PI q12h, and 2000 mg PI q8h were simulated for 10,000 subjects. Variability in pharmacokinetic parameters and MIC distributions were derived from studies in healthy volunteers and the MYSTIC surveillance program, respectively. The probabilities of attaining bacteriostatic (30% T>MIC) and bactericidal (50% T>MIC) exposures were high for all dosage regimens against populations of Enterobacteriaceae. Against Acinetobacter species and Pseudomonas aeruginosa, the 2000-mg PI q8h dosage regimen provided the highest target attainment rates. For mild to moderate infections caused by Enterobacteriaceae, prolonged infusion regimens of 500 mg PI q8h and 1000 mg PI q12h would provide equivalent target attainment rates to the traditional 30-minute infusion while requiring less drug over 24 hours. For more serious infections presumably caused by Acinetobacter species or Pseudomonas aeruginosa, a dose of 2000 mg PI q8h is recommended because of its high bactericidal target attainment rate against these pathogens. Further study of these dosage recommendations in clinical trials is suggested.

Key Words: Meropenem • Monte Carlo simulation • pharmacodynamics • dosage regimens • antimicrobial drug development

Monte Carlo simulation has been proposed as an acceptable method to evaluate the probability of experimental dosage regimens in attaining prespecified pharmacodynamic targets against specific pathogens.^8-10 By using a probability density function to generate random concentration values, thousands of single-point estimates can be made and their probabilities plotted to examine the entire range of possible drug exposures. The results of these simulations provide investigators with reasonable confidence of which dosage regimens have the highest probabilities of positive outcomes and thus which substantiate further development in larger clinical trials.

Meropenem, an intravenous carbapenem with microbiological activity against both Gram-positive and Gram-negative bacteria, including Pseudomonas aeruginosa, was approved in the United States in 1996 as a 1000-mg dose infused over 5 or 30 minutes every 8 hours.¹¹ Like other ß-lactam antibiotics (i.e., penicillins and cephalosporins), meropenem displays time-dependent or concentration-independent killing, whereby bactericidal killing best correlates with the duration of time that drug concentrations remain above the minimum inhibitory concentration (MIC) for the organism. The pharmacodynamic parameter used to measure this endpoint is the percentage of the dosing interval that drug concentrations remain above the MIC (%T>MIC).¹² For the carbapenems, bacteriostatic and bactericidal responses were observed when drug concentrations remained above their MIC for approximately 20% to 30% and 40% to 50% of the dosing interval, respectively.¹³ Thus, a pharmacodynamic target is now available when designing dosage regimens.

Selection of dosing regimens that have a high target attainment rate, and thus maximize pharmacodynamic exposure, may provide increasing benefits in the form of quicker rates of response, especially in the immunocompromised host.^7,14 Ideally, administration by continuous infusion should be considered to maximize the %T>MIC for ß-lactam antibiotics. However, carbapenem antibiotics, such as meropenem, imipenem-cilastatin sodium, and ertapenem, are only stable for approximately 4 to 6 hours at room temperature and are thus inappropriate candidates for continuous infusion unless administered in a cold pouch.^15,16 Recently, another pharmacodynamically influenced dosing strategy has been suggested for meropenem, prolonging the infusion of the drug to 3 hours. As compared with a 30-minute infusion, this methodology increases the %T>MIC while adhering to the confines of room-temperature stability (Figure 1).^17,18

View larger version (12K): [in this window] [in a new window]   Figure 1. Simulated concentration-time profiles of meropenem 2000 mg administered as the traditional 30-minute infusion and as a prolonged 3-hour infusion. Administration as a prolonged infusion will increase the %T>MIC (percent time minimum inhibitory concentration).

The objective of this study was to compare pharmacodynamic target attainment rates of several dosage regimens when the infusion is prolonged over 3 hours as compared with the traditional 30-minute infusion against populations of Enterobacteriaceae, Pseudomonas aeruginosa, and Acinetobacter species. These results will assist in determining which prolonged infusion regimens may be candidates for further development in clinical trials.

	METHOD

TOP ABSTRACT METHOD RESULTS DISCUSSION CONCLUSION REFERENCES

 
Pharmacokinetics
Steady-state pharmacokinetic data for prolonged infusion (PI) meropenem regimens of 500 mg and 2000 mg over 3 hours every 8 hours were derived from 6 healthy volunteers (Table I).¹⁷ These data indicated that when administered as a 3-hour infusion, meropenem displayed linear pharmacokinetics and dose proportionality over the range of doses studied. Thus, different doses and dosing intervals could be evaluated using the same results for half-life (t_1/2), volume of distribution (Vd), and clearance (CL). Comparative pharmacokinetic data for the 30-minute traditional infusion (TI), specifically t_1/2 and Vd, were collected from a previously published study in 12 healthy volunteers and are also listed in Table I.¹⁹ The values of these parameters were similar to those found in patients receiving the prolonged infusion.

Probability distributions for t_1/2, CL, and Vd were developed using Crystal Ball 2000 (Decisioneering, Inc., Denver, CO). All pharmacokinetic parameters displayed normal distributions.

Microbiology
MIC values and their frequencies were derived from the Meropenem Yearly Susceptibility Test Information Collection (MYSTIC) surveillance study, a multicenter, longitudinal program that compares the activity of meropenem and five other antimicrobial agents against Gram-positive and Gram-negative aerobic clinical isolates from intensive care units, neutropenia units, cystic fibrosis units, or nonspecialist centers.²⁰ MIC data from the Americas (10 centers in the United States, 3 in Brazil, and 1 in Mexico) for the years 1997 to 1998 were collected for the following bacteria: Escherichia coli, Klebsiella pneumoniae, Enterobacter cloacae, Serratia spp., Acinetobacter spp., and Pseudomonas aeruginosa. MIC frequency values are listed in Table II. Custom MIC distributions were built for each population of bacteria based on the MIC frequencies in the MYSTIC study using Crystal Ball.

Pharmacodynamics
Pharmacodynamic analysis was made using Monte Carlo methodology for the following dosage regimens: 1000 mg TI q8h, 2000 mg TI q8h, 500 mg PI q8h, 1000 mg PI q12h, 1000 mg PI q8h, 2000 mg PI q12h, and 2000 mg PI q8h. The %T>MIC for the TI dosage regimens was calculated using a one-compartment IV-bolus equation:

where ln is the natural logarithm, Dose is the intermittent dose in milligrams, Vd is the volume of distribution in liters, MIC is the minimum inhibitory concentration in micrograms per milliliter, t_1/2 is the half-life in hours, and DI is the dosing interval in hours. Although the traditional infusion duration is commonly 30 minutes, the added time above the MIC from this infusion extension would be insignificant, and thus an IV-bolus model is used for simplicity.

Because the PI regimens were infused over 3 hours, a one-compartment equation that combined an IV-continuous infusion during the distribution (i.e., infusion) phase of the concentration-time curve and an IV-bolus during the elimination phase was required to calculate the %T>MIC:

where Ro is the infusion rate in mg/h (i.e., 166.67 mg/h, 333.33 mg/h, and 666.67 mg/h for the 500-mg, 1000-mg, and 2000-mg PI doses, respectively), t is the infusion time (i.e., 3 h), CL is the clearance in liters per hour, ln is the natural logarithm, MIC is the minimum inhibitory concentration in micrograms per milliliter, t_1/2 is the half-life in hours, and DI is the dosing interval in hours. This equation assumes that the peak concentration at the end of the 3-hour infusion is the steady-state concentration, as calculated by Ro/CL.

A 10,000-subject Monte Carlo simulation was conducted for each dosing regimen against each population of bacteria. During each iteration, a different value for the pharmacokinetic parameters as well as the MIC was substituted into the equation based on the probability distributions for each. For PI regimens, t_1/2 estimates were negatively correlated to CL (r = -0.90 for the 500-mg dose and -0.83 for the 2000-mg dose) estimates using the correlation application in Crystal Ball and the individual healthy volunteer t_1/2 and CL values. Because specific pharmacokinetic values for a 1000-mg PI dose were not reported in the healthy volunteer study, probability distributions for the 500-mg PI dose were extrapolated to simulate 1000-mg dosages.¹⁷

The resulting %T>MIC exposures were plotted according to their frequencies. The target attainment rates (i.e., probabilities) of achieving bacteriostatic (30% T>MIC) and bactericidal (50% T>MIC) exposures were calculated for each regimen against each bacteria population.

	RESULTS

TOP ABSTRACT METHOD RESULTS DISCUSSION CONCLUSION REFERENCES

 
Target attainment rates for achieving 30% and 50% T>MIC are listed in Tables III and IV. All dosage regimens had a high probability of attaining bacteriostatic and bactericidal responses against E. coli, K. pneumoniae, E. cloacae, and Serratia species. Furthermore, these exposures could be obtained with 500 mg PI q8h and 1000 mg PI q12h, doses lower than regimens approved by the Food and Drug Administration (FDA).

Against Acinetobacter species, all doses, regardless of infusion length and dosing interval, obtained high target attainment rates for bacteriostatic exposure; however, target attainment rates declined for bactericidal exposure, with 2000-mg PI q8h, 2000-mg TI q8h, and 1000-mg PI q8h regimens retaining the highest probabilities (Table IV).

Prolonged infusion regimens of 1000 mg and 2000 mg q8h had high bacteriostatic target attainment rates against P. aeruginosa and were similar to the same dosage regimens administered by traditional infusion. The 2000-mg PI q12h regimen also obtained high probability of bacteriostatic exposure (Table III). Similar to Acinetobacter species, bactericidal target attainment rates declined for P. aeruginosa, with the 2000-mg PI q8h regimen having the highest probability followed by 2000 mg TI q8h and 1000 mg PI q8h (Table IV).

Figures 2 and 3 display bacteriostatic and bactericidal target attainment rates for each dosage regimen specific to each MIC dilution, respectively. Considering that the susceptibility breakpoint for Enterobacteriaceae, Acinetobacter species, and P. aeruginosa is 4 µg/mL, all regimens had 100% certainty of achieving bacteriostatic (30% T>MIC) exposure against susceptible isolates (Figure 2). However, for bactericidal (50% T>MIC) exposure, doses of 1000 mg PI q8h, 2000 mg TI q8h, and 2000 mg PI q8h achieve the highest attainment for all susceptible isolates (Figure 3). Furthermore, the regimen of 2000 mg PI q8h will achieve adequate bactericidal exposure against organisms considered to be meropenem intermediate resistant (MIC = 8 µg/mL).

View larger version (16K): [in this window] [in a new window]   Figure 2. Target attainment rate for 30% time above the minimum inhibitory concentration (MIC) for each meropenem dosage regimen at each MIC.

View larger version (18K): [in this window] [in a new window]   Figure 3. Target attainment rate for 50% time above the minimum inhibitory concentration (MIC) for each meropenem dosage regimen at each MIC.

	DISCUSSION

TOP ABSTRACT METHOD RESULTS DISCUSSION CONCLUSION REFERENCES

 
In this analysis, we performed Monte Carlo simulation to compare pharmacodynamic target attainment rates of a newly proposed dosing strategy for meropenem against various bacteria populations. Historically, investigators have used single-point estimates of pharmacokinetic parameters (e.g., average values of half-life, volume of distribution, or area under the curve) and pathogen MIC (e.g., MIC₅₀ or MIC₉₀) to calculate the predicted exposure of a specified dosing regimen.^21,22 While not incorrect, simply applying single-point estimates to compare different antibiotics or dosing regimens does not adequately determine the likelihood of achieving therapeutic pharmacodynamic exposure. Monte Carlo simulation allows incorporation of variability in pharmacokinetic parameters among potential patients when predicting exposure. In addition, the range of possible MIC values in a given bacterial population are considered, thereby providing results that would be applicable to the empiric treatment of an infection, before the susceptibility of the pathogen is known.

ß-Lactam antibiotics, such as the carbapenems, are known to display concentration-independent or time-dependent bactericidal killing once drug concentrations are greater than two to four times the MIC.^1,12 Thus, the most efficient dosing regimens for these agents would be to maintain drug concentrations above the MIC throughout the dosing interval, which is best accomplished by a continuous infusion.^5,7 However, as stated previously, carbapenem antibiotics are not stable for more than 4 to 6 hours at room temperature.^15,16 Therefore, keeping in line with meropenem's time-dependent killing and the goal of prolonging concentrations above the MIC to maximize pharmacodynamics, investigators have proposed extending the meropenem infusion to 3 hours instead of the traditional 30 minutes.^17,18 As demonstrated in Figure 1, this strategy lowers the maximum concentration (C_max), delays the time to maximum concentration (t_max), and has no effect on the elimination of meropenem, thus prolonging the T>MIC as compared with the traditional infusion duration. Moreover, this is accomplished while adhering to the confinements of room-temperature stability.

The results of our Monte Carlo simulations revealed that prolonging the infusion had little benefit against Enterobacteriaceae when the same dose was simulated (i.e., 1000 mg TI q8h vs. 1000 mg PI q8h). This was due to the low MIC values for susceptible isolates and exceedingly high MIC values for resistant isolates within these bacterial populations. However, prolonging the infusion does allow the possibility of using a lower dose (500 mg PI q8h) or increasing the dosing interval (1000 mg PI q12h). Both regimens had high target attainment rates for bactericidal exposure while using less drug over a 24-hour period, thereby lowering drug-associated acquisition cost, a positive attribute in today's cost-conscious health care economy.

In contrast, Acinetobacter and P. aeruginosa, which are commonly associated with more severe infections, had greater numbers of isolates with elevated MIC values. As such, higher doses were needed to maintain a high probability of bacteriostatic and bactericidal exposure. This was most apparent for the population of P. aeruginosa used in the analysis. Against this organism, the 2000-mg PI q8h regimen attained bactericidal exposure with 84% certainty compared with 79.9% for 2000 mg q8h by 30-minute infusion. In addition, attainment rates for bacteriostatic exposures were less than 90% for all regimens. These observations are due to a higher prevalence of multidrug-resistant P. aeruginosa in the MYSTIC surveillance program and further justify the empiric use of a second agent such as an aminoglycoside when treating suspected P. aeruginosa infections, thus effectively lowering the MIC and preventing the emergence of resistance.¹⁸

While all regimens achieved 100% certainty of bacteriostatic exposure at the National Committee for Clinical Laboratory Standards (NCCLS) susceptibility breakpoint of 4 µg/mL, dosage regimens of 1000 mg PI q8h, 2000 mg PI q8h, and 2000 mg TI q8h obtained the highest attainment rates for bactericidal exposure against all meropenem-susceptible organisms (Figures 2 and 3).²³ These target attainment rates were generated with a conservative estimate for bactericidal exposure (50% T>MIC). Other investigators have employed 40% T>MIC as the target for bactericidal killing and demonstrated that 1000 mg TI q8h also achieves high attainment rates against all susceptible organisms.¹⁸ Since pathogens such as Acinetobacter species and P. aeruginosa have more isolates with meropenem MIC values near the susceptibility breakpoint, these observations support the empiric use of larger doses when these bacteria are suspected. Last, when considering target attainment rate for these dosage regimens by MIC, 2000 mg PI q8h will provide high probability of bactericidal exposure at an MIC of 8 µg/mL, which is considered intermediate resistant, and 37% certainty at an MIC of 16 µg/mL (Figure 2). Since a deletion of the oprD2 porin in P. aeruginosa results in a fourfold increase in the meropenem MIC (i.e., from 4 µg/mL to 16 µg/mL), these elevated exposures may have additional benefits by preventing the emergence of resistance in susceptible isolates.

Because we are advocating higher doses for the empiric treatment of Acinetobacter species and P. aeruginosa infections, clinicians may have some trepidation about an increase in dose-related toxicity—specifically, central nervous system toxicity. Dosage regimens up to 2000 mg q8h by traditional infusion have been studied in both pediatrics and adults with cystic fibrosis and shown to be safe.^11,24 Furthermore, meropenem is approved for use in pediatrics in the United States up to a dose of 2000 mg q8h, with no observed increase in toxicity. Administration by prolonged infusion should have a similar if not better toxicity profile, as peak concentrations are lower than that of the traditional infusion. Increasing dosages, specifically against these organisms, will also result in higher drug-related acquisition costs. This seems justifiable, however, if higher doses in fact result in better outcomes and earlier discharges from the hospital, thus leading to overall lower medical costs. These endpoints require further study in clinical trials involving these dosage regimens.

Proper interpretation of these results requires discussion of certain assumptions made by our model. First, our pharmacokinetic parameter distributions were derived from data in 6 healthy volunteers. This results in a more conservative estimate of meropenem exposure, as healthy volunteers will have the shortest half-life and eliminate meropenem the quickest. More important, while the pharmacokinetics of meropenem in severely ill patients would be different from healthy volunteers, we have observed that these differences often have little effect on %T>MIC exposure. When compared with healthy volunteers, infected patients commonly have both a larger Vd and t_1/2, which cancel each other out to provide similar pharmacodynamic exposure for time-dependent antibiotics (authors' observation).²⁵

In addition, variability in a controlled study, especially among 6 healthy volunteers, is small. In infected patients, we would predict that although the total exposure would be similar, greater variability in the model would be apparent. Monte Carlo simulation alleviates some of this concern as it randomly picks point estimates from the distribution of half-life and volume. As a result, longer as well as shorter half-lives, along with larger volumes of distribution, were sampled and are represented in the final distribution. Ideally, Monte Carlo simulation should be conducted with patient pharmacokinetic data; however, larger studies than are currently available in the literature are needed to capture pharmacokinetic estimates for patients in the upper and lower 5% of the population distribution.

We employed a one-compartment model to calculate meropenem exposure in our analyses. Other studies have suggested that meropenem serum concentration-time profiles are best fitted with a two-compartment pharmacokinetic model.^19,26 However, studies on meropenem pharmacokinetics have been published using both one- and two-compartment models as well as noncompartmental analysis.^17,19,25-27 The Vd of meropenem is low, indicating predominantly extracellular distribution; therefore, incorporating estimates of the rate constants between the central and peripheral compartments should have little effect on the overall probability of achieving targeted pharmacodynamic exposure.

Last, we used bacterial populations from the MYSTIC surveillance program. While MIC results for Enterobacteriaceae and Acinetobacter species are similar to other large surveillance programs, they may not be representative of the MIC distributions in other institutions.^28,29 Arguably, the MYSTIC program acquires samples from those institutions that use carbapenems frequently because of a higher prevalence of resistance among certain bacteria species. This explains the difference in Pseudomonas susceptibility to meropenem when compared with other national surveillance programs; meropenem resistance rates are higher in the MYSTIC hospitals.^30,31 Therefore, it is probable that our exposure estimates are again a "worst-case" scenario, specifically for this organism.

	CONCLUSION

TOP ABSTRACT METHOD RESULTS DISCUSSION CONCLUSION REFERENCES

 
Monte Carlo simulation is a valuable technique to discriminate potential differences in the pharmacodynamic profile of various antibiotic dosing regimens among populations of bacteria. For mild infections caused by Enterobacteriaceae, prolonging the meropenem infusion to 3 hours allows use of a lower meropenem dose (500 mg PI q8h) or increased dosing interval (1000 mg PI q12h). For more serious infections presumably caused by Acinetobacter species or Pseudomonas aeruginosa, a dose of 2000 mg PI q8h is recommended because of its high bactericidal target attainment rate against these pathogens and ability to provide adequate exposure against intermediate-resistant isolates. Further study of these dosage recommendations in clinical trials is suggested to determine if benefits in the clinical success rate, prevention of the emergence of resistance, and cost savings are achievable.

	FOOTNOTES

 
Presented in part at the 42nd Interscience Conference on Antimicrobial Agents and Chemotherapy, San Diego, California, September 27-30, 2002. Supported by a grant from AstraZeneca L.P., Wilmington, Delaware. Dr. Nicolau acts as a consultant to and has received research grants from AstraZeneca L.P.

DOI: 10.1177/0091270003257225

Submitted for publication March 15, 2003; Revised version accepted July 3, 2003.

	REFERENCES

TOP ABSTRACT METHOD RESULTS DISCUSSION CONCLUSION REFERENCES

 

1. Craig WA: Pharmacokinetic/pharmacodynamic parameters: rationale for antibacterial dosing of mice and men. Clin Infect Dis 1998; 26:1- 12.

2. Kuti JL, Capitano BC, Nicolau DP: Cost-effective approaches to the treatment of community acquired pneumonia in the era of resistance. Pharmacoeconomics 2002;20: 513-528.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]

3. Kuti JL, Maglio D, Nightingale CH, Nicolau DP: Economic benefit of a pharmacodynamic influenced meropenem dosing strategy. Am J Health-Syst Pharm; 2003;60: 565-568.[Abstract/Free Full Text]

4. Freeman CD, Nicolau DP, Belliveau PP, Nightingale CH: Once-daily dosing of aminoglycosides: review and recommendations for clinical practice. J Antimicrob Chemother 1997;39: 677-686.[Abstract/Free Full Text]

5. Craig WA, Ebert SC: Continuous infusion of ß-lactam antibiotics. Antimicrob Agents Chemother 1992;36: 2577-2583.[Free Full Text]

6. Nicolau DP, Freeman CD, Belliveau PP, Nightingale CH, Ross JW, Quintiliani R: Experience with a once-daily aminoglycoside program administered to 2,184 adult patients. Antimicrob Agents Chemother 1995;39: 650-655.[Abstract]

7. Grant EM, Kuti JL, Nicolau DP, Nightingale CH, Quintiliani R: Clinical efficacy and pharmacoeconomics of a continuous infusion piperacillin/tazobactam program in a large, community, teaching hospital. Pharmacotherapy 2002;22: 471-483.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]

8. Ambrose PG, Grasela DM: The use of Monte Carlo simulation to examine pharmacodynamic variance of drugs: fluoroquinolone pharmacodynamics against Streptococcus pneumoniae. Diagn Micro Infect Dis 2000;38: 151-157.

9. Drusano GL, Preston SL, Corrado M, Reichl V, Freitag S, Kahn JB, et al: Target attainment analysis for levofloxacin 750mg IV daily for nosocomial pneumonia using Monte Carlo simulation for common Gram-negative pathogens [abstract], in: Program and Abstracts of the 42nd Interscience Conference on Antimicrobial Agents and Chemotherapy (San Diego). Washington, DC: American Society for Microbiology, 2002; 8.

10. Paterson DL, Clarke L, Ndirangu MW, Kuznetsov D: Use of pharmacodynamic principles and stochastic modeling to choose an optimal empiric cefepime dose for suspected Pseudomonas aeruginosa infections within a single institution [abstract], in: Program and Abstracts of the 42nd Interscience Conference on Antimicrobial Agents and Chemotherapy (San Diego). Washington, DC: American Society for Microbiology, 2002; 9.

11. Merrem package insert. Wilmington, DE: AstraZeneca Pharmaceuticals L.P., 2001.

12. Turnidge JD: The pharmacodynamics of ß-lactams. Clin Infect Dis 1998;27: 10-22.[Web of Science][Medline] [Order article via Infotrieve]

13. Walker R, Andes D, Conklin J, Ebert SC, Craig WA: Pharmacodynamic activities of meropenem in an animal infection model [abstract], in: Program and Abstracts of the 34th Interscience Conference on Antimicrobial Agents and Chemotherapy (Orlando). Washington, DC: American Society for Microbiology, 1994; 147.

14. Bodey GP, Ketchel SJ, Rodriguez V: A randomized study of carbenicillin plus cefamandole or tobramycin in the treatment of febrile episodes in cancer patients. Am J Med 1979;67: 608-616.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]

15. Patel RP, Cook SE: Stability of meropenem in intravenous solutions. Am J Health-Syst Pharm 1997;54: 412-421.[Abstract/Free Full Text]

16. Grant EM, Zhong MK, Ambrose PG, Nicolau DP, Nightingale CH, Quintiliani R: Stability of meropenem in a portable infusion device in a cold pouch. Am J Health-Syst Pharm 2000;57: 992-995.[Free Full Text]

17. Dandekar PK, Maglio D, Sutherland CA, Nightingale CH, Nicolau DP: Pharmacokinetics of meropenem 0.5g and 2g every 8h administered as a 3h infusion. Pharmacotherapy 2003;23: 988-991.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]

18. Drusano GL, Louie A, Miller MH, Melnick D: Prevention of emergence of resistance in Pseudomonas aeruginosa infections through pharmacodynamic dosing and combination chemotherapy [abstract]. Paper presented at the 98th International Conference of the American Thoracic Society, Atlanta, GA, May 2002.

19. Dreetz M, Hamacher J, Eller J, Borner K, Koeppe P, Schaberg T, et al: Serum bactericidal activities and comparative pharmacokinetics of meropenem and imipenem-cilastatin. Antimicrob Agents Chemother 1996;40: 105-109.[Abstract]

20. Turner PJ: MYSTIC (Meropenem Yearly Susceptibility Test Information Collection): a global overview. J Antimicrob Chemother 2000; 46:9- 23.[Abstract/Free Full Text]

21. Kays MB: Comparison of five ß-lactam antibiotics against common nosocomial pathogens using the time above the MIC at different creatinine clearances. Pharmacotherapy 1999;19: 1392-1399.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]

22. Kays MB, Denys GA: In vitro activity and pharmacodynamics of azithromycin and clarithromycin against Streptococcus pneumoniae based on serum and intrapulmonary pharmacokinetics. Clin Ther 2001;23: 413-424.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]

23. National Committee for Clinical Laboratory Standards (NCCLS): Performance Standards for Antimicrobial Susceptibility Testing: Twelfth Informational Supplement. NCCLS document M100-S12. Wayne, PA: NCCLS, 2002.

24. Bui KQ, Ambrose PG, Nicolau DP, Lapin CD, Nightingale CH, Quintiliani R: Pharmacokinetics of high-dose meropenem in adult cystic fibrosis patients. Chemother 2001;47: 153-156.

25. Thalhammer F, Traunmuller F, El Menyawi I, Frass M, Hollenstein UM, Locker GJ, et al: Continuous infusion versus intermittent administration of meropenem in critically ill patients. J Antimicrob Chemother 1999;43: 523-527.[Abstract/Free Full Text]

26. Mouton JW, van den Anker JN: Meropenem clinical pharmacokinetics. Clin Pharmacokin 1995;28: 275-286.[Web of Science][Medline] [Order article via Infotrieve]

27. Bax RP, Bastain W, Featherstone A, Wilkinson DM, Hutchinson M, Haworth SJ: The pharmacokinetics of meropenem in volunteers. J Antimicrob Chemother 1989;24(Suppl. A): 311-320.[Abstract/Free Full Text]

28. Diekema DJ, Pfaller MA, Jones RN, Doern GV, Winokur PL, Gales AC, et al: Survey of bloodstream infections due to Gram-negative bacilli: frequency of occurrence and antimicrobial susceptibility of isolates collected in the United States, Canada, and Latin America for the SENTRY antimicrobial surveillance program, 1997. Clin Infect Dis 1999;29: 595-607.[Web of Science][Medline] [Order article via Infotrieve]

29. Gales AC, Jones RN, Forward KR, Linares J, Sader HS, Verhoef J: Emerging importance of multidrug-resistant Acinetobacter species and Stenotrophomonas maltophilia as pathogens in seriously ill patients: geographic patterns, epidemiological features, and trends in the SENTRY antimicrobial surveillance program (1997-1999). Clin Infect Dis 2001;32(Suppl. 2): S104-S113.

30. Gales AC, Jones RN, Turnidge J, Rennie R, Ramphal R: Characterization of Pseudomonas aeruginosa isolates: occurrence rates, antimicrobial susceptibility patterns, and molecular typing in the global SENTRY antimicrobial surveillance program, 1997-1999. Clin Infect Dis 2001;32(Suppl. 2): S146-S155.

31. Jones RN, Kirby JT, Beach ML, Biedenbach DJ, Pfaller MA: Geographic variations in activity of broad-spectrum ß-lactams against Pseudomonas aeruginosa: summary of the worldwide SENTRY antimicrobial surveillance program (1997-2000). Diagn Micro Infect Dis 2002;43: 239-243.
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