The repurposed agent moxifloxacin has become an important addition to the physician's armamentarium for the therapy of Mycobacterium tuberculosis When a drug is administered, we need to have metrics for success. As for most antimicrobial chemotherapy, we contend that for Mycobacterium tuberculosis therapy, these metrics should be a decline in the susceptible bacterial burden and the suppression of amplification of less-susceptible populations. To achieve optimal outcomes relative to these metrics, a dose and schedule of administration need to be chosen. For large populations of patients, there are true between-patient differences in important pharmacokinetic parameters. These distributions of parameter values may have an impact on these metrics, depending on what measure of drug exposure drives the metrics. To optimize dose and schedule choice of moxifloxacin, we performed a dose fractionation experiment in the hollow fiber infection model. We examined 12-, 24-, and 48-h dosing intervals with doses of 200, 400, and 800 mg for each interval, respectively. Within each interval, we had an arm where half-lives of 12, 8, and 4 h were simulated. We attempted to keep the average concentration (Cavg) or area under the concentration-time curve (AUC) constant across arms. We found that susceptible bacterial load decline was linked to Cavg, as we had indicated previously. Resistance suppression, a nonmonotonic function, had minimum concentration (Cmin) as the linked index. The 48-h interval with the 4-h half-life had the largest less-susceptible population. Balancing bacterial kill, resistance suppression, toxicity (linked to peak concentration [Cpeak]), and adherence, we conclude that the dose of 400 mg daily is optimal for moxifloxacin.
Keywords: Mycobacterium tuberculosis; dose fractionation; mathematical modeling; pharmacodynamics; resistance suppression.
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