| Literature DB >> 34339275 |
Sarah Kim1, Walter M Yamada2, Brandon Duncanson3, Jocelyn Nole3, Stephanie Rogers3, Sarah Parker3, Meredith Bacci3, Nino Mtchedlidze3, Charles A Peloquin4, Arnold Louie3, Stephan Schmidt1, George L Drusano3, Michael N Neely2.
Abstract
Mycobacterium tuberculosis metabolic state affects the response to therapy. Quantifying the effect of antimicrobials in the acid and nonreplicating metabolic phases of M. tuberculosis growth will help to optimize therapy for tuberculosis. As a brute-force approach to all possible drug combinations against M. tuberculosis in all different metabolic states is impossible, we have adopted a model-informed strategy to accelerate the discovery. Using multiple concentrations of each drug in time-kill studies, we examined single drugs and two- and three-drug combinations of pretomanid, moxifloxacin, and bedaquiline plus its active metabolite against M. tuberculosis in its acid-phase metabolic state. We used a nonparametric modeling approach to generate full distributions of interaction terms between pretomanid and moxifloxacin for susceptible and less susceptible populations. From the model, we could predict the 95% confidence interval of the simulated total bacterial population decline due to the 2-drug combination regimen of pretomanid and moxifloxacin and compare this to observed declines with 3-drug regimens. We found that the combination of pretomanid and moxifloxacin at concentrations equivalent to average or peak human concentrations effectively eradicated M. tuberculosis in its acid growth phase and prevented emergence of less susceptible isolates. The addition of bedaquiline as a third drug shortened time to total and less susceptible bacterial suppression by 8 days compared to the 2-drug regimen, which was significantly faster than the 2-drug kill.Entities:
Keywords: Monte Carlo simulation; combination therapy; mathematical modeling
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Year: 2021 PMID: 34339275 PMCID: PMC8451274 DOI: 10.1128/AAC.00693-21
Source DB: PubMed Journal: Antimicrob Agents Chemother ISSN: 0066-4804 Impact factor: 5.191