Application of a mathematical model to prevent in vivo amplification of antibiotic-resistant bacterial populations during therapy
Abstract
Nonstandard abbreviations used: minimum inhibitory concentration (MIC); Mueller-Hinton II broth (MHB); minimum bactericidal concentration (MBC); area under the concentration time curve (AUC); nonparametric expectation maximization 2 (NPEM2); maximum a posteriori probability (MAP); quinolone resistance-determining region (QRDR).caused by antibiotic-resistant bacteria are more difficult to treat, resulting in excess morbidity and mortality as well as higher health care costs.Therefore, it is imperative to identify ways of suppressing the emergence of antibiotic-resistant mutants.Current preclinical methods for assessing the efficacy of an antimicrobial agent most often evaluate the effect of selected dosages of the compound on the reduction in the total bacterial population at an infection site.The impact of drug pressure on the amplification of the drug-resistant subpopulation is ignored (1-3).For some antibiotic dosages, the drug-susceptible population may be completely replaced with resistant mutants over time.Clinically, this may manifest as the failure of an infection to respond to therapy or a relapse of infection with drug-resistant mutants shortly after a prescribed course of antibiotic therapy is completed.The probability that a resistant subpopulation exists within a predominantly drug-susceptible wildtype population is dependent on the number of organisms at the infection site (total population burden) and the mutational frequency to resistance to Application of a…
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