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 CFU counts and liquid culture time to positivity (TTP) that were linked through a time constant. The posterior population geometric means and interindividual variability coefficients of variation were, respectively, 0.152 ± 0.013 log10 CFU/ml sputum/day and 54% ± 6% for the maximum kill rate constant, 770 ± 140 ng/ml and 48% ± 17% for the pretomanid half-maximum effect plasma concentration, and 20.4 ± 1.0 h and 20.8% ± 0.1% for the time constant of proportionality between the CFU and TTP rate equations. Model simulations showed once-daily pretomanid at 100, 200, and 300 mg attained 58, 73, and 80%, respectively, of an expected maximum 14-day EBA of 0.136 log10 CFU/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.

Pretomanid dose selection for pulmonary tuberculosis: An application of multi‐objective optimization to dosage regimen design

“…The pretomanid dose‐response model was based on the plasma drug concentrations, sputum CFU counts, and drug‐related AE counts observed in the CL‐007 and CL‐010 studies 23,24 . The dose‐efficacy relationship was described previously as a population PK‐PD model that included sputum CFU kinetics as a function of plasma concentration, with the latter being a function of time and the dosage 28,29 . The model included PK‐PD parameter sets for the study population, the male and female subpopulations, and for the individual participants.…”

“…23,24 The dose-efficacy relationship was described previously as a population PK-PD model that included sputum CFU kinetics as a function of plasma concentration, with the latter being a function of time and the dosage. 28,29 The model included PK-PD parameter sets for the study population, the male and female subpopulations, and for the individual participants. The dose-safety relationship was modeled as a pretomanid concentration-dependent probability of a drug-related AE;…”

“…Optimized once-daily pretomanid doses, as a variabledose and fixed-frequency problem, were determined for population-typical, male-typical, and female-typical doseresponse profiles; and for the first 3 participants randomized to the CL-007 200 mg dose group as examples of individualized dosing. Figure 1 shows the Pareto fronts, BR profiles, dose-response model MC simulations using previously described model parameter distributions, 28,29 and the individual dose-exposure-response outcomes. The differences between male and female dosing can be accounted for as a PK effect.…”

Combined quantitative tuberculosis biomarker model for time-to-positivity and colony forming unit to support tuberculosis drug development

“… Gausi et al (2021) used both biomarkers to describe isoniazid efficacy on a single bacterial population for CFU and TTP in patients with drug-sensitive and drug-resistant TB. Lyons used CFU and TTP to establish pretomanid and bedaquiline exposure-response relationships ( Lyons, 2019 ; Lyons, 2022 ). This work builds upon the previous work by using both CFU and TTP data simultaneously combined to a rifampicin PK model to evaluate the exposure-response relationship of rifampicin on three bacterial subpopulations using the MTP model, which presents a more mechanistic approach of assessing the exposure-response relationship.…”

Model‐based dose optimization framework for bedaquiline, pretomanid and linezolid for the treatment of drug‐resistant tuberculosis

“…Thus, predictions of BPaL treat- To date, quantitative pharmacology approaches have exploited some relationships between patient-and disease-related covariates, PK and response for bedaquiline, pretomanid and linezolid individually. [11][12][13][14] These models, however, did not include several key mechanistic components, such as Mtb susceptibility, target site drug exposures and PD interactions between the BPaL combination regimen. In this work, we aimed to combine the relevant mechanistic components to develop a quantitative framework for BPaL…”