Background: Translation of experimental data on antibiotic activity typically relies on pharmacokinetic/pharmacodynamic (PK/PD) indices. Model-based approaches, considering the full antibiotic killing time course, could be an alternative.

Objectives: To develop a mechanism-based modelling framework to assess the in vitro and in vivo activity of the FabI inhibitor antibiotic afabicin, and explore the ability of a model built on in vitro data to predict in vivo outcome.

Methods: A PK/PD model was built to describe bacterial counts from 162 static in vitro time-kill curves evaluating the effect of afabicin desphosphono, the active moiety of the prodrug afabicin, against 21 Staphylococcus aureus strains. Combined with a mouse PK model, outcomes of afabicin doses of 0.011-190 mg/kg q6h against nine S. aureus strains in a murine thigh infection model were predicted, and thereafter refined by estimating PD parameters.

Results: A sigmoid Emax model, with EC50 scaled by the MIC described the afabicin desphosphono killing in vitro. This model predicted, without parameter re-estimation, the in vivo bacterial counts at 24 h within a ±1 log margin for most dosing groups. When parameters were allowed to be estimated, EC50 was 38%-45% lower in vivo, compared with in vitro, within the studied MIC range.

Conclusions: The developed PK/PD model described the time course of afabicin activity across experimental conditions and bacterial strains. This model showed translational capacity as parameters estimated on in vitro time-kill data could well predict the in vivo outcome for a wide variety of doses in a mouse thigh infection model.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11638087PMC
http://dx.doi.org/10.1093/jac/dkae334DOI Listing

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