Concentration-dependent suppression of macrolide resistance in Mycobacterium avium by combination therapy: An improved in vitro time-kill assay and alveolar macrophage exposure-based pharmacokinetic/pharmacodynamic modeling study.

INTRODUCTION

Macrolides are key drugs for treating 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. Therefore, we aimed to quantify the concentration-dependent effects of companion drugs on macrolide resistance using an improved time-kill assay and pharmacokinetic/pharmacodynamic (PK/PD) modeling approach.

METHODS

Time-kill assays were performed using M. avium ATCC 700898 exposed to azithromycin alone or in combination with ethambutol, rifampicin, amikacin, or clofazimine. Total and resistant bacterial populations were quantified over 28 days. A pharmacodynamic model describing the dynamics of susceptible and resistant subpopulations was linked to a pharmacokinetic model incorporating alveolar macrophage exposure to simulate resistance emergence and bactericidal activity under various dosing regimens.

RESULTS

Macrolide resistance most frequently emerged at 2-4× the minimum inhibitory concentration (MIC) of azithromycin, whereas resistance was less frequent at 8-16× MIC or sub-MIC levels. The addition of companion drugs suppressed resistance emergence even at sub-MIC levels. PK/PD simulations (excluding clofazimine) demonstrated that standard-dose ethambutol prevented macrolide resistance regardless of whether the regimen was administered daily or three times weekly. In contrast, the addition of rifampicin or amikacin further reduced bacterial burden compared with the macrolide-plus-ethambutol regimen.

CONCLUSION

This 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. The findings provide mechanistic insights that may help optimize combination dosing strategies for M. avium pulmonary disease.