The development of novel antibacterial agents is decreasing despite increasing resistance to presently available agents among common pathogens. Insights into relationships between pharmacodynamics and resistance may provide ways to optimize the use of existing agents. The evolution of resistance was examined in two ciprofloxacin-susceptible Staphylococcus aureus strains exposed to in vitro-simulated clinical and experimental ciprofloxacin pharmacokinetic profiles for 96 h. As the average steady-state concentration (C avg ss ) increased, the rate of killing approached a maximum, and the rate of regrowth decreased. The enrichment of subpopulations with mutations in grlA and low-level ciprofloxacin resistance also varied depending on the pharmacokinetic environment. A regimen producing values for C avg ss slightly above the MIC selected resistant variants with grlA mutations that did not evolve to higher levels of resistance. Clinical regimens which provided values for C avg ss intermediate to the MIC and mutant prevention concentration (MPC) resulted in the emergence of subpopulations with gyrA mutations and higher levels of resistance. A regimen producing values for C avg ss close to the MPC selected grlA mutants, but the appearance of subpopulations with higher levels of resistance was diminished. A regimen designed to maintain ciprofloxacin concentrations entirely above the MPC appeared to eradicate low-level resistant variants in the inoculum and prevent the emergence of higher levels of resistance. There was no relationship between the time that ciprofloxacin concentrations remained between the MIC and the MPC and the degree of resistance or the presence or type of ciprofloxacin-resistance mutations that appeared in grlA or gyrA. Regimens designed to eradicate low-level resistant variants in S. aureus populations may prevent the emergence of higher levels of fluoroquinolone resistance.

Three pharmacodynamic models of increasing complexity, designed for two subpopulations of bacteria with different susceptibilities, were developed to describe and predict the evolution of resistance to ciprofloxacin in Staphylococcus aureus by using pharmacokinetic, viable count, subpopulation, and resistance mechanism data obtained from in vitro system experiments. A two-population model with unique growth and killing rate constants for the ciprofloxacin-susceptible and -resistant subpopulations best described the initial killing and subsequent regrowth patterns observed. The model correctly described the enrichment of subpopulations with low-level resistance in the parent cultures but did not identify a relationship between the time ciprofloxacin concentrations were in the mutant selection window (the interval between the MIC and the mutant prevention concentration) and the enrichment of these subpopulations. The model confirmed the importance of resistant variants to the emergence of resistance by successfully predicting that resistant subpopulations would not emerge when a low-density culture, with a low probability of mutants, was exposed to a clinical dosing regimen or when a high-density culture, with a higher probability of mutants, was exposed to a transient high initial concentration designed to rapidly eradicate low-level resistant grlA mutants. The model, however, did not predict or explain the origin of variants with higher levels of resistance that appeared and became the predominant subpopulation during some experiments or the persistence of susceptible bacteria in other experiments where resistance did not emerge. Continued evaluation of the present two-population pharmacodynamic model and development of alternative models is warranted.Mathematical models that are carefully constructed by using data from in vitro and in vivo studies may provide insights into the population dynamics underlying the emergence of antimicrobial resistance. If such models accurately predict the outcome of antimicrobial therapy, they could facilitate the design of dosing regimens to prevent resistance by allowing rapid analysis of multiple dosing strategies.A number of pharmacodynamic models have been proposed to explain the population dynamics leading to antimicrobial resistance and to predict dosing regimens that may prevent the emergence of resistance. Some were derived from those modeling the effects of chemotherapeutic agents on eukaryotic cells (19). Zhi and coworkers proposed a model that successfully predicted the effects of single and multiple doses of piperacillin on Pseudomonas aeruginosa infections in neutropenic mice (36). Others expanded this one-population model by adding mathematical terms to account for the emergence of resistance (22,25), the maximum number of bacteria that can grow in a given environment (18,25,35), or the appearance of resistant mutants from susceptible bacteria by a stochastic process (23). Recently, an indirect physiological model has been proposed where the antimicrobial is assume...

Previously, we demonstrated the importance of low-level-resistant variants to the evolution of resistance in Staphylococcus aureus exposed to ciprofloxacin in an in vitro system and developed a pharmacodynamic model which predicted the emergence of resistance. Here, we examine and model the evolution of resistance to levofloxacin in S. aureus exposed to simulated levofloxacin pharmacokinetic profiles. Enrichment of subpopulations with mutations in grlA and low-level resistance varied with levofloxacin exposure. A regimen producing average steady-state concentrations (C avg ss ) just above the MIC selected grlA mutants with up to 16-fold increases in the MIC and often additional mutations in grlA/grlB and gyrA. A regimen providing C avg ss between the MIC and the mutant prevention concentration (MPC) suppressed bacterial numbers to the limit of detection and prevented the appearance of bacteria with additional mutations or high-level resistance. Regimens producing C avg ss above the MPC appeared to eradicate low-level-resistant variants in the cultures and prevent the emergence of resistance. There was no relationship between the time concentrations remained between the MIC and the MPC and the degree of resistance or the presence or type of mutations that appeared in grlA/B or gyrA. Our pharmacodynamic model described the growth and levofloxacin killing of the parent strains and the most resistant grlA mutants in the starting cultures and correctly predicted conditions that enrich subpopulations with low-level resistance. These findings suggest that the pharmacodynamic model has general applicability for describing fluoroquinolone resistance in S. aureus and further demonstrate the importance of low-level-resistant variants to the evolution of resistance.In previous work, we examined the evolution of resistance when ciprofloxacin-susceptible (S) Staphylococcus aureus strains were exposed in an in vitro hollow-fiber system to simulated clinical and experimental ciprofloxacin pharmacokinetic profiles (4). We found that with increasing average steady-state concentrations (C avg ss ), the rate of initial killing approached a maximum, and the rate of regrowth decreased. Enrichment of subpopulations with mutations in grlA and low-level resistance also varied depending on the pharmacokinetic environment. A regimen producing C avg ss slightly above the MIC selected resistant (R) variants with grlA mutations that did not evolve to higher levels of resistance. Clinical regimens which provided C avg ss intermediate between the MIC and mutant prevention concentration (MPC) resulted in the emergence of subpopulations with gyrA mutations and higher levels of resistance and a regimen producing C avg ss greater than or equal to the MPC selected grlA mutants, but the appearance of subpopulations with higher levels of resistance was delayed. A regimen designed to maintain ciprofloxacin concentrations entirely above the MPC appeared to eradicate low-level-resistant variants in the inoculum and prevent the emergence of high-level-re...

) pharmacokinetic profiles in an in vitro system indicated that the subpopulation-specific estimated maximal killing rate constants were similar for both agents, suggesting a common mechanism of action. We propose two novel pharmacodynamic models that assign mechanisms of action to fluoroquinolones (growth inhibition or death stimulation) and compare the abilities of these models and two other maximum effect models (net effect and MIC based) to describe and predict the changes in the population dynamics observed during our previous in vitro system experiments with ciprofloxacin. A high correlation between predicted and observed viable counts was observed for all models, but the best fits, as assessed by diagnostic tests, and the most precise parameter estimates were obtained with the growth inhibition and net effect models. All models, except the death stimulation model, correctly predicted that resistant subpopulations would not emerge when a high-density culture was exposed to a high initial concentration designed to rapidly eradicate low-level-resistant grlA mutants. Additional experiments are necessary to elucidate which of the proposed mechanistic models best characterizes the antibacterial effects of fluoroquinolone antimicrobial agents.Pharmacodynamic models may prove to be efficient and powerful tools for optimizing antimicrobial dosing to prevent the emergence of resistance if they can accurately predict changes in susceptible and resistant bacterial subpopulations over time as a function of antimicrobial concentration. Such models could potentially be used to narrow the range of in vitro, animal, or clinical trials required for drug development and approval.We previously evaluated the abilities of three maximum effect (E max ) models of increasing complexity, designed for two subpopulations of bacteria with different susceptibilities, to describe and predict the evolution of resistance to ciprofloxacin in Staphylococcus aureus by using pharmacokinetic, viable count, subpopulation, and resistance mechanism data obtained from in vitro system experiments (5). A two-population model with unique growth and killing rate constants for the ciprofloxacin-susceptible and -resistant subpopulations best described the initial killing and subsequent regrowth patterns observed. The model correctly characterized the enrichment of subpopulations with low-level resistance in the parent cultures and confirmed the importance of resistant variants to the emergence of resistance by successfully predicting that resistant subpopulations would not emerge when a low-density culture, with a low probability of mutants, was exposed to a clinical dosing regimen or when a high-density culture, with a higher probability of mutants, was exposed to a transient high initial concentration designed to rapidly eradicate low-levelresistant grlA mutants (5).In subsequent in vitro system experiments in which the same S. aureus strains were exposed to ciprofloxacin, gatifloxacin, and garenoxacin (J. J. Campion and M. E. Evans, Abstr. 11th Int....

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