Standards for model-based early bactericidal activity analysis and sample size determination in tuberculosis drug development - Mockeliunas, Laurynas; Faraj, Alan; van Wijk, Rob C.; Upton, Caryn M.; van den Hoogen, Gerben; Diacon, Andreas H.; Simonsson, Ulrika S. H. (Frontiers in Pharmacology, 2023)
Background: A critical step in tuberculosis (TB) drug development is the Phase 2a early bactericidal activity (EBA) study which informs if a new drug or treatment has short-term activity in humans. The aim of this work was to present a standardized pharmacometric model-based EBA analysis workflow and determine sample sizes needed to detect EBA or a difference between treatment arms. Methods: Seven different steps were identified and developed for a standardized pharmacometric model-based EBA analysis approach. Non-linear mixed effects modeling was applied and different scenarios were explored for the sample size calculations. The sample sizes needed to detect EBA given different TTP slopes and associated variability was assessed. In addition, the sample sizes needed to detect effect differences between two treatments given the impact of different TTP slopes, variability in TTP slope and effect differences were evaluated. Results: The presented EBA analysis approach incorporates estimate of EBA with uncertainty through the model-based estimate of TTP slope, variability in TTP slope, impact of covariates and pharmacokinetics on drug efficacy. Further it allows for treatment comparison or dose optimization in Phase 2a. To detect EBA with 80% power and at a 5% significance level, 13 and 8 participants/arm were required for a treatment with a TTP-EBA0-14 as low as 11 hours when accounting for variability in pharmacokinetics and when variability in TTP slope was 104% (coefficient of variation [CV]) and 22%, respectively. Higher sample sizes are required for smaller EBA and when pharmacokinetics is not accounted for. Based on sample size determinations to detect a difference between two groups, TTP slope, variability in TTP slope and effect difference between two treatment arms needs to be considered. Conclusions: In conclusion, a robust standardized pharmacometric model-based EBA analysis approach was established in close collaboration between microbiologists, clinicians and pharmacometricians. The work illustrates the importance of accounting for covariates and drug exposure in EBA analysis in order to increase the power of detecting EBA for a single treatment arm as well as differences in EBA between treatments arms in Phase 2a trials of TB drug development.