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Modeling and Simulation of Pretomanid Pharmacodynamics in Pulmonary Tuberculosis Patients.

ABSTRACT: Pretomanid (PA-824) is a nitroimidazole in clinical testing for the treatment of tuberculosis. A population pharmacodynamic model for pretomanid was developed using a Bayesian analysis of efficacy data from two early bactericidal activity (EBA) studies, PA-824-CL-007 and PA-824-CL-010, conducted in Cape Town, South Africa. The two studies included 122 adult male and female participants with newly diagnosed pulmonary tuberculosis who received once daily oral pretomanid doses of either 50, 100, 150, 200, 600, 1,000, or 1,200 mg for 14 days. The structural model described capacity-limited growth and saturable drug-induced bacterial killing with separate rate equations for sputum solid culture colony forming unit (CFU) counts and liquid culture time to positivity (TTP) that were linked through a time constant. The posterior population geometric means and interindividual variability percent coefficients of variation were, respectively; 0.152±0.013 log10 CFU/mL sputum/day and 54%±6% for the maximum kill rate constant, 20.4±1.0 h and 20.8%±0.1% for the time constant of proportionality between the CFU and TTP rate equations, and 770±140 ng/mL and 48%±17% for the pretomanid half-maximum effect plasma concentration. Model simulations showed once daily pretomanid at 100 mg, 200 mg, and 300 mg, attained 58%, 73%, and 80%, respectively, of an expected maximum 14-day EBA of 0.136 log10CFU/mL sputum/day. These results establish a pretomanid exposure-efficacy relationship with dual outcomes for CFU counts and TTP, and with potential applications to dose optimization of pretomanid-containing regimens.

SUBMITTER: Lyons MA

PROVIDER: S-EPMC6879235 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Modeling and Simulation of Pretomanid Pharmacodynamics in Pulmonary Tuberculosis Patients.

Lyons Michael A MA

Antimicrobial agents and chemotherapy 20190930 12

Pretomanid (PA-824) is a nitroimidazole in clinical testing for the treatment of tuberculosis. A population pharmacodynamic model for pretomanid was developed using a Bayesian analysis of efficacy data from two early bactericidal activity (EBA) studies, PA-824-CL-007 and PA-824-CL-010, conducted in Cape Town, South Africa. The two studies included 122 adult male and female participants with newly diagnosed pulmonary tuberculosis who received once daily oral pretomanid doses of either 50, 100, 15 ...[more]

PMID: 31570404

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Project description:BackgroundTuberculosis (TB) incidence in India continues to be high due, in large part, to long delays experienced by patients before successful diagnosis and treatment initiation, especially in the private sector. This diagnostic delay is driven by patients' inclination to switch between different types of providers and providers' inclination to delay ordering of accurate diagnostic tests relevant to TB. Our objective is to quantify the impact of changes in these behavioral characteristics of providers and patients on diagnostic delay experienced by pulmonary TB patients.Methods and findingsWe developed a discrete event simulation model of patients' diagnostic pathways that captures key behavioral characteristics of providers (time to order a test) and patients (time to switch to another provider). We used an expectation-maximization algorithm to estimate the parameters underlying these behavioral characteristics, with quantitative data encoded from detailed interviews of 76 and 64 pulmonary TB patients in the 2 Indian cities of Mumbai and Patna, respectively, which were conducted between April and August 2014. We employed the estimated model to simulate different counterfactual scenarios of diagnostic pathways under altered behavioral characteristics of providers and patients to predict their potential impact on the diagnostic delay. Private healthcare providers including chemists were the first point of contact for the majority of TB patients in Mumbai (70%) and Patna (94%). In Mumbai, 45% of TB patients first approached less-than-fully-qualified providers (LTFQs), who take 28.71 days on average for diagnosis. About 61% of these patients switched to other providers without a diagnosis. Our model estimates that immediate testing for TB by LTFQs at the first visit (at the current level of diagnostic accuracy) could reduce the average diagnostic delay from 35.53 days (95% CI: 34.60, 36.46) to 18.72 days (95% CI: 18.01, 19.43). In Patna, 61% of TB patients first approached fully qualified providers (FQs), who take 9.74 days on average for diagnosis. Similarly, immediate testing by FQs at the first visit (at the current level of diagnostic accuracy) could reduce the average diagnostic delay from 23.39 days (95% CI: 22.77, 24.02) to 11.16 days (95% CI: 10.52, 11.81). Improving the diagnostic accuracy of providers per se, without reducing the time to testing, was not predicted to lead to any reduction in diagnostic delay. Our study was limited because of its restricted geographic scope, small sample size, and possible recall bias, which are typically associated with studies of patient pathways using patient interviews.ConclusionsIn this study, we found that encouraging private providers to order definitive TB diagnostic tests earlier during patient consultation may have substantial impact on reducing diagnostic delay in these urban Indian settings. These results should be combined with disease transmission models to predict the impact of changes in provider behavior on TB incidence.

Project description:BackgroundThe bedaquiline-pretomanid-linezolid regimen has been reported to have 90% efficacy against highly drug-resistant tuberculosis, but the incidence of adverse events with 1200 mg of linezolid daily has been high. The appropriate dose of linezolid and duration of treatment with this agent to minimize toxic effects while maintaining efficacy against highly drug-resistant tuberculosis are unclear.MethodsWe enrolled participants with extensively drug-resistant (XDR) tuberculosis (i.e., resistant to rifampin, a fluoroquinolone, and an aminoglycoside), pre-XDR tuberculosis (i.e., resistant to rifampin and to either a fluoroquinolone or an aminoglycoside), or rifampin-resistant tuberculosis that was not responsive to treatment or for which a second-line regimen had been discontinued because of side effects. We randomly assigned the participants to receive bedaquiline for 26 weeks (200 mg daily for 8 weeks, then 100 mg daily for 18 weeks), pretomanid (200 mg daily for 26 weeks), and daily linezolid at a dose of 1200 mg for 26 weeks or 9 weeks or 600 mg for 26 weeks or 9 weeks. The primary end point in the modified intention-to-treat population was the incidence of an unfavorable outcome, defined as treatment failure or disease relapse (clinical or bacteriologic) at 26 weeks after completion of treatment. Safety was also evaluated.ResultsA total of 181 participants were enrolled, 88% of whom had XDR or pre-XDR tuberculosis. Among participants who received bedaquiline-pretomanid-linezolid with linezolid at a dose of 1200 mg for 26 weeks or 9 weeks or 600 mg for 26 weeks or 9 weeks, 93%, 89%, 91%, and 84%, respectively, had a favorable outcome; peripheral neuropathy occurred in 38%, 24%, 24%, and 13%, respectively; myelosuppression occurred in 22%, 15%, 2%, and 7%, respectively; and the linezolid dose was modified (i.e., interrupted, reduced, or discontinued) in 51%, 30%, 13%, and 13%, respectively. Optic neuropathy developed in 4 participants (9%) who had received linezolid at a dose of 1200 mg for 26 weeks; all the cases resolved. Six of the seven unfavorable microbiologic outcomes through 78 weeks of follow-up occurred in participants assigned to the 9-week linezolid groups.ConclusionsA total of 84 to 93% of the participants across all four bedaquiline-pretomanid-linezolid treatment groups had a favorable outcome. The overall risk-benefit ratio favored the group that received the three-drug regimen with linezolid at a dose of 600 mg for 26 weeks, with a lower incidence of adverse events reported and fewer linezolid dose modifications. (Funded by the TB Alliance and others; ZeNix ClinicalTrials.gov number, NCT03086486.).

Dataset Information

Modeling and Simulation of Pretomanid Pharmacodynamics in Pulmonary Tuberculosis Patients.

Publications

Modeling and Simulation of Pretomanid Pharmacodynamics in Pulmonary Tuberculosis Patients.

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