title: Bacterial resistance studies using in vitro dynamic models: the predictive power of the mutant prevention and minimum inhibitory antibiotic concentrations.
abstract: In light of the concept of the mutant selection window, i.e., the range between the MIC and the mutant prevention concentration (MPC), MPC-related pharmacokinetic indices should be more predictive of bacterial resistance than the respective MIC-related indices. However, experimental evidence of this hypothesis remains limited and contradictory. To examine the predictive power of the ratios of the area under the curve (AUC24) to the MPC and the MIC, the selection of ciprofloxacin-resistant mutants of four Escherichia coli strains with different MPC/MIC ratios was studied. Each organism was exposed to twice-daily ciprofloxacin for 3 days at AUC24/MIC ratios that provide peak antibiotic concentrations close to the MIC, between the MIC and the MPC, and above the MPC. Resistant E. coli was intensively enriched at AUC24/MPCs from 1 to 10 h (AUC24/MIC from 60 to 360 h) but not at the lower or higher AUC24/MPC and AUC24/MIC ratios. AUC24/MPC and AUC24/MIC relationships of the areas under the time courses of ciprofloxacin-resistant E. coli (AUBCM) were bell-shaped. A Gaussian-like function fits the AUBCM-AUC24/MPC and AUBCM-AUC24/MIC data combined for all organisms (r(2) = 0.69 and 0.86, respectively). The predicted anti-mutant AUC24/MPC ratio was 58 ± 35 h, and the respective AUC24/MIC ratio was 1,080 ± 416 h. Although AUC24/MPC was less predictive of strain-independent E. coli resistance than AUC24/MIC, the established anti-mutant AUC24/MPC ratio was closer to values reported for Staphylococcus aureus (60 to 69 h) than the respective AUC24/MIC ratio (1,080 versus 200 to 240 h). This implies that AUC24/MPC might be a better interspecies predictor of bacterial resistance than AUC24/MIC.
authors.affiliation: Department of Pharmacokinetics and Pharmacodynamics, Gause Institute of New Antibiotics, Russian Academy of Medical Sciences, Moscow, Russia.
authors.forename: Alexander A
authors.initials: AA
authors.lastname: Firsov
authors.forename: Elena N
authors.initials: EN
authors.lastname: Strukova
authors.forename: Darya S
authors.initials: DS
authors.lastname: Shlykova
authors.forename: Yury A
authors.initials: YA
authors.lastname: Portnoy
authors.forename: Varvara K
authors.initials: VK
authors.lastname: Kozyreva
authors.forename: Mikhail V
authors.initials: MV
authors.lastname: Edelstein
authors.forename: Svetlana A
authors.initials: SA
authors.lastname: Dovzhenko
authors.forename: Mikhail B
authors.initials: MB
authors.lastname: Kobrin
authors.forename: Stephen H
authors.initials: SH
authors.lastname: Zinner
mesh_terms: D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D019540:Area Under Curve; D002939:Ciprofloxacin / Q000494:pharmacology; D004926:Escherichia coli / Q000187:drug effects* / Q000235:genetics; D008826:Microbial Sensitivity Tests; D009154:Mutation; D015363:Quinolones / Q000494:pharmacology
chemical_list: D000900:Anti-Bacterial Agents; D015363:Quinolones; D002939:Ciprofloxacin
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