 Information from this PK study is needed to fill this knowledge gap, and to model the population PK model parameters without bias and with satisfactory precision relative standard error 20. Reiterated simulations and re-estimations sse of rifapentine data in Study 29-29X were performed to assess the optimal Study 31 PKPD design for: 1 between-subject variability BSV and precision of the population PK parameters, and 2 the longitudinal component of rifapentine clearance by autoinduction. Uncertainty in parameter estimates RSE of 10 was considered acceptable for the population PK parameters and 20 for the parameter describing autoinduction. These simulations indicated that for the parameter describing rifapentine auto-induction, it is important that multiple PK samplings are obtained, and that PK sampling occasions be time-balanced. If this is not performed, the uncertainty of the longitudinal change in clearance substantially increases, i.e. a protocol design with only one initial PK sampling is not able to identify longitudinal change in clearance with satisfactory precision, and leads to high uncertainty in parameter estimates. A parsimonious design that efficiently assesses longitudinal changes in clearance with adequate certainty and limited costs, will include the following features: i a minimum of 60 participants; ii intensive PK sampling 6 optimal samplesparticipant times 0.5, 3, 6, 9, 12, 24 hours on at least one occasion; and iii late sampling with 2 to 3 PK samples at another, later occasion separated by a minimum of 14 days. In summary, this PKPD Study is valuable because, it will allow a robust development of population PK model parameters for rifapentine and for moxifloxacin in presence of high-dose rifapentine, and evaluate the PKPD relationships of study drugs with efficacy outcomes. 