The use of Monte Carlo simulation to examine pharmacodynamic variance of drugs: fluoroquinolone pharmacodynamics against Streptococcus pneumoniae

Abstract

Background: For fluoroquinolones, AUC:MIC ratios correlate with maximal bacterial eradication in in vitro models of infection and favorable cure rates in humans with respiratory tract infection. Inter-subject pharmacokinetic and MIC variability may impact the probability of attaining optimal AUC:MIC ratios and hence favorable clinical outcome. Methods: Monte Carlo simulation was utilized to estimate the probability of attaining AUC:MIC ratios of 30, 40, 50, 60, 70, 80, 90, 100, 110 and 120 using AUC values from patients treated with either gatifloxacin or levofloxacin and microbiologic activity against S. pneumoniae observed in 1997 SENTRY Antimicrobial Surveillance Program. Results: The probability curves for 5000 patient simulations were plotted. The median AUC:MIC ratios were 120 for gatifloxacin and 50.5 for levofloxacin. The probability of attaining AUC:MIC ratios of 30, 50, 70 and 100 for gatifloxacin were 94%, 86%, 78% and 62%, and for levofloxacin were 80%, 51%, 31% and 17%, respectively. Conclusion: Gatifloxacin has a higher probability of achieving target AUC:MIC ratios than levofloxacin. Monte Carlo simulation, using patient-based AUC and MIC distributions, may have implications for selection of optimal antibiotics for the empiric treatment of infections. Moreover, Monte Carlo simulation may have utility in the determination of MIC breakpoints.