Dataset Information

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:Shorter, more potent regimens are needed for tuberculosis. The nitroimidazole pretomanid was recently approved for extensively drug-resistant tuberculosis in combination with bedaquiline and linezolid. Pretomanid may also have benefit as a treatment-shortening agent for drug-sensitive tuberculosis. It is unclear how and whether it can be used together with rifamycins, which are key sterilizing first-line drugs. In this analysis, data were pooled from two studies: the Assessing Pretomanid for Tuberculosis (APT) trial, in which patients with drug-sensitive pulmonary TB received pretomanid, isoniazid, and pyrazinamide plus either rifampin or rifabutin versus standard of care under fed conditions, and the AIDS Clinical Trials Group 5306 (A5306) trial, a phase I study in healthy volunteers receiving pretomanid alone or in combination with rifampin under fasting conditions. In our population pharmacokinetic (PK) model, participants taking rifampin had 44.4 and 59.3% reductions in pretomanid AUC (area under the concentration-time curve) compared to those taking rifabutin or pretomanid alone (due to 80 or 146% faster clearance) in the APT and A5306 trials, respectively. Median maximum concentrations (C max) in the rifampin and rifabutin arms were 2.14 and 3.35 mg/liter, while median AUC0-24 values were 30.1 and 59.5 mg·h/liter, respectively. Though pretomanid exposure in APT was significantly reduced with rifampin, AUC0-24 values were similar to those associated with effective treatment in registrational trials, likely because APT participants were fed with dosing, enhancing pretomanid relative bioavailability and exposures. Pretomanid concentrations with rifabutin were high but in range with prior observations. While pretomanid exposures with rifampin are unlikely to impair efficacy, our data suggest that pretomanid should be taken with food if prescribed with rifampin. (This study has been registered at ClinicalTrials.gov under identifier NCT02256696.).

Project description:Bedaquiline (B), pretomanid (Pa) and linezolid (L) are key components of new regimens for treating rifampicin-resistant tuberculosis (TB). However, there is limited information on the global prevalence of resistance to these drugs and the impact of resistance on treatment outcomes. Mycobacterium tuberculosis (MTB) phenotypic drug susceptibility and whole-genome sequence (WGS) data, as well as patient profiles from 4 pretomanid-containing trials-STAND, Nix-TB, ZeNix and SimpliciTB-were used to investigate the rates of baseline resistance (BR) and acquired resistance (AR) to BPaL drugs, as well as their genetic basis, risk factors and impact on treatment outcomes. Data from >1,000 TB patients enrolled from 2015 to 2020 in 12 countries was assessed. We identified 2 (0.3%) participants with linezolid BR. Pretomanid BR was also rare, with similar rates across TB drug resistance types (0-2.1%). In contrast, bedaquiline BR was more prevalent among participants with highly resistant TB or longer prior treatment histories than those with newly diagnosed disease (5.2-6.3% vs. 0-0.3%). Bedaquiline BR was a risk factor for bacteriological failure or relapse in Nix-TB/ZeNix; 3/12 (25%, 95% CI 5-57%) participants with vs. 6/185 (3.2%, 1.2-6.9%) without bedaquiline BR. Across trials, we observed no linezolid AR, and only 3 cases of bedaquiline AR, including 2 participants with poor adherence. Overall, pretomanid AR was also rare, except in ZeNix patients with bedaquiline BR. WGS analyses revealed novel mutations in canonical resistant genes and, in 7 MTB isolates, the genetic determinants could not be identified. The overall low rates of BR to linezolid and pretomanid, and to a lesser extent to bedaquiline, observed in the pretomanid trials are in support of the worldwide implementation of BPaL-based regimens. Similarly, the overall low AR rates observed suggest BPaL drugs are better protected in the regimens trialed here than in other regimens combining bedaquiline with more, but less effective drugs.

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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