title: Predicting bacterial resistance using the time inside the mutant selection window: possibilities and limitations.
abstract: The time inside the mutant selection window (TMSW) has been shown to be less predictive of selection of fluoroquinolone-resistant bacteria than the ratio of the area under the concentration-time curve to minimum inhibitory concentration (AUC/MIC). To explore the different predictive powers of TMSW and AUC/MIC, enrichment of ciprofloxacin-resistant mutants of four Escherichia coli strains was studied in an in vitro dynamic model at widely ranging TMSW values. Each organism was exposed to twice-daily ciprofloxacin for 3 days. Peak antibiotic concentrations were simulated to be close to the MIC, between the MIC and the mutant prevention concentration (MPC), and above the MPC, with TMSW varying from 0% to 100% of the dosing interval. Amplification of resistant mutants was monitored by plating on medium with 8× MIC of the antibiotic. For each organism, TMSW plots of the area under the bacterial mutant concentration-time curve (AUBCM) exhibited a hysteresis loop: at a given TMSW that corresponds to the points on the ascending portion of the bell-shaped AUBCM-AUC/MIC curve [when the time above the MPC (T>MPC) was zero], the AUBCM was greater than at the same TMSW related to the descending portion (T>MPC>0). A sigmoid function fits these separate data sets well for combined data with the four organisms (r(2)=0.81 and 0.92, respectively), in contrast to fitting the whole data pool while ignoring the AUC/MIC-resistance relationship (r(2)=0.61). These data allow the appropriate use of TMSW as a predictor of bacterial resistance.
authors.affiliation: Department of Pharmacokinetics & Pharmacodynamics, Gause Institute of New Antibiotics, Russian Academy of Medical Sciences, 11 Bolshaya Pirogovskaya Street, Moscow 119021, Russia; Department of Pharmaceutical and Toxicological Chemistry, I.M. Sechenov First Moscow State Medical University, Moscow, Russia. Electronic address: firsov@dol.ru.
authors.forename: Alexander A
authors.initials: AA
authors.lastname: Firsov
authors.affiliation: Department of Pharmacokinetics & Pharmacodynamics, Gause Institute of New Antibiotics, Russian Academy of Medical Sciences, 11 Bolshaya Pirogovskaya Street, Moscow 119021, Russia.
authors.forename: Yury A
authors.initials: YA
authors.lastname: Portnoy
authors.affiliation: Department of Pharmacokinetics & Pharmacodynamics, Gause Institute of New Antibiotics, Russian Academy of Medical Sciences, 11 Bolshaya Pirogovskaya Street, Moscow 119021, Russia.
authors.forename: Elena N
authors.initials: EN
authors.lastname: Strukova
authors.affiliation: Department of Pharmacokinetics & Pharmacodynamics, Gause Institute of New Antibiotics, Russian Academy of Medical Sciences, 11 Bolshaya Pirogovskaya Street, Moscow 119021, Russia.
authors.forename: Darya S
authors.initials: DS
authors.lastname: Shlykova
authors.affiliation: Department of Medicine, Mount Auburn Hospital, Harvard Medical School, Cambridge, MA, USA.
authors.forename: Stephen H
authors.initials: SH
authors.lastname: Zinner
mesh_terms: D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D002939:Ciprofloxacin / Q000494:pharmacology*; D024881:Drug Resistance, Bacterial; D004926:Escherichia coli / Q000187:drug effects* / Q000235:genetics; D008826:Microbial Sensitivity Tests; D015233:Models, Statistical; D008962:Models, Theoretical; D009154:Mutation; D012641:Selection, Genetic; D013997:Time Factors
chemical_list: D000900:Anti-Bacterial Agents; D002939:Ciprofloxacin
keywords: Fluoroquinolones; In vitro model; Resistant mutant enrichment