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• W4387639542 abstract "Efflux pump inhibitors (EPIs) offer an attractive therapeutic option when combined with existing classes. However, their optimal dosing strategies are unknown.MICs of ciprofloxacin (CIP)+/-chlorpromazine, phenylalanine-arginine β naphthylamide (PAβN) and a developmental molecule MBX-4191 were determined and the pharmacodynamics (PD) was studied in an in vitro model employing Escherichia coli MG1655 and its isogenic MarR mutant (I1147). Exposure ranging experiments were performed initially then fractionation. Changes in bacterial load and population profiles were assessed. Strains recovered after EPI simulations were studied by WGS.The CIPMICs for E. coli MG1655 and I1147 were 0.08 and 0.03 mg/L. Chlorpromazine at a concentration of 60 mg/L, PAβN concentrations of 30 mg/L and MBX-4191 concentrations of 0.5-1.0 mg/L reduced CIP MICs for I1147 and enhanced bacterial killing. Using CIP at an AUC of 1.2 mg·h/L, chlorpromazine AUC was best related to reduction in bacterial load at 24 h, however, when the time drug concentration was greater than 25 mg/L (T > 25 mg/L) chlorpromazine was also strongly related to the effect. For PaβN with CIP AUC, 0.6 mg·h/L PaβN AUC was best related to a reduction in bacterial load. MBX-4191T > 0.5-0.75 mg·h/L was best related to reduction in bacterial load. Changes in population profiles were not seen in experiments of ciprofloxacin + EPIs. WGS of recovered strains from simulations with all three EPIs showed mutations in gyrA, gyrB or marR.AUC was the pharmacodynamic driver for chlorpromazine and PAβN while T > threshold was the driver for MBX-4191 and important in the activity of chlorpromazine and PAβN. Changes in population profiles did not occur with combinations of ciprofloxacin + EPIs, however, mutations in gyrA, gyrB and marR were detected." @default.
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• W4387639542 date "2023-10-14" @default.
• W4387639542 modified "2023-10-16" @default.
• W4387639542 title "Exposure of <i>Escherichia coli</i> to antibiotic-efflux pump inhibitor combinations in a pharmacokinetic model: impact on bacterial clearance and drug resistance" @default.
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• W4387639542 doi "https://doi.org/10.1093/jac/dkad320" @default.
• W4387639542 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37837411" @default.
• W4387639542 hasPublicationYear "2023" @default.
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