Literature DB >> 26349518

A mechanism-based pharmacokinetic/pharmacodynamic model allows prediction of antibiotic killing from MIC values for WT and mutants.

David D Khan1, Pernilla Lagerbäck2, Sha Cao3, Ulrika Lustig3, Elisabet I Nielsen4, Otto Cars2, Diarmaid Hughes3, Dan I Andersson3, Lena E Friberg4.   

Abstract

OBJECTIVES: In silico pharmacokinetic/pharmacodynamic (PK/PD) models can be developed based on data from in vitro time-kill experiments and can provide valuable information to guide dosing of antibiotics. The aim was to develop a mechanism-based in silico model that can describe in vitro time-kill experiments of Escherichia coli MG1655 WT and six isogenic mutants exposed to ciprofloxacin and to identify relationships that may be used to simplify future characterizations in a similar setting.
METHODS: In this study, we developed a mechanism-based PK/PD model describing killing kinetics for E. coli following exposure to ciprofloxacin. WT and six well-characterized mutants, with one to four clinically relevant resistance mutations each, were exposed to a wide range of static ciprofloxacin concentrations.
RESULTS: The developed model includes susceptible growing bacteria, less susceptible (pre-existing resistant) growing bacteria, non-susceptible non-growing bacteria and non-colony-forming non-growing bacteria. The non-colony-forming state was likely due to formation of filaments and was needed to describe data close to the MIC. A common model structure with different potency for bacterial killing (EC50) for each strain successfully characterized the time-kill curves for both WT and the six E. coli mutants.
CONCLUSIONS: The model-derived mutant-specific EC50 estimates were highly correlated (r(2) = 0.99) with the experimentally determined MICs, implying that the in vitro time-kill profile of a mutant strain is reasonably well predictable by the MIC alone based on the model.
© The Author 2015. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Year:  2015        PMID: 26349518     DOI: 10.1093/jac/dkv233

Source DB:  PubMed          Journal:  J Antimicrob Chemother        ISSN: 0305-7453            Impact factor:   5.790


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