Tuberculosis (TB) remains one of the most important infectious diseases. Population pharmacokinetic (pop-PK) models are widely used to individualize dosing regimens of several antibiotics, but their application in anti-TB drug studies is scant. The aim of this study was to provide an insight regarding the status of pop-PK for these drugs and to compare results obtained through both parametric and nonparametric approaches to design precise dosage regimens.
First, a systematic approach was implemented, searching in PubMed and Google Scholar. Articles that did not include human patients, that lacked an explicit structural model, that analyzed drugs inactive against M. tuberculosis, or were without full-text access, were excluded. Second, the PK parameters were summarized and categorized as parametric versus nonparametric results. Third, a Monte Carlo simulation was performed in Pmetrics using the results of both groups, and an error term was built to describe the imprecision of each PK modeling approach.
Thirty-three articles reporting at least 1 pop-PK model of 19 anti-TB drug were found; 46 different models including PK parameter estimates and their relevant covariates were also reported. Only 9 models were based on nonparametric approaches. Rifampin was the drug most studied, but only using parametric approaches. The simulations showed that nonparametric approaches improve the error term compared with parametric approaches.
More and better models, ideally using nonparametric approaches linked with clear pharmacodynamic goals, are required to optimize anti-TB drug dosing, as recommended in the WHO End TB strategy.