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bioRxivPharmacology & ToxicologyPreprint

Concentration-dependent suppression of macrolide resistance in Mycobacterium avium by combination therapy: an improved in vitro time-kill assay and PK/PD modelling study

Fumiya WatanabeiD, Yuta MorishigeiD, Akio AonoiD, Yuji MoritaiD, Kozo MorimotoiD, Satoshi MitaraiiD, Kazuhiko Hanada

PDFDOI

Abstract

ObjectivesMacrolides are key drugs in the treatment for Mycobacterium avium pulmonary disease, and combination chemotherapy is essential to preventing macrolide resistance. However, the concentrations of concomitant agents required to suppress resistance emergence remain undefined. This study aimed to quantify the concentration-dependent effects of companion drugs on macrolide resistance using an improved time-kill assay and pharmacokinetic/pharmacodynamic (PK/PD) modelling approach. MethodsTime-kill assays were performed on M. avium ATCC 700898 using azithromycin alone or in combination with ethambutol, rifampicin, amikacin, or clofazimine. Total and resistant bacterial populations were quantified over 28 days. A pharmacodynamic (PD) model describing the dynamics of susceptible and resistant subpopulations was linked to a pharmacokinetic (PK) model incorporating alveolar macrophage concentrations to simulate resistance and bactericidal rates under various dosing regimens. ResultsMacrolide resistance most frequently emerged at 2-4x the minimum inhibitory concentration (MIC) of azithromycin, whereas resistance was less frequent at 8-16x MIC or sub-MIC levels. The addition of companion drugs suppressed resistance emergence even at sub-MIC levels. PK/PD simulations demonstrated that standard-dose ethambutol effectively prevented macrolide resistance, whereas rifampicin provided minimal protection. More frequent dosing schedules enhanced resistance suppression compared with once-daily regimens. ConclusionThis study defines the concentration-dependent contributions of concomitant agents to macrolide resistance suppression in M. avium and establishes a quantitative PK/PD framework for evaluating resistance emergence. These findings provide mechanistic insights to support the optimization of combination dosing strategies for M. avium pulmonary disease.

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