Population pharmacokinetics of rifapentine and desacetyl rifapentine in healthy volunteers: nonlinearities in clearance and bioavailability

Abstract

Rifapentine is under active investigation as a potent drug that may help shorten the tuberculosis (TB) treatment duration. A previous rifapentine dose escalation study with daily dosing indicated a possible decrease in bioavailability as the dose increased and an increase in clearance over time for rifapentine and its active metabolite, desacetyl rifapentine. This study aimed to assess the effects of increasing doses on rifapentine absorption and bioavailability and to evaluate the clearance changes over 14 days. A population analysis was performed with nonlinear mixed-effects modeling. Absorption, time-varying clearance, bioavailability, and empirical and semimechanistic autoinduction models were investigated. A one-compartment model linked to a transit compartment absorption model best described the data. The bioavailability of rifapentine decreased linearly by 2.5% for each 100-mg increase in dose. The autoinduction model suggested a dose-independent linear increase in clearance of the parent drug and metabolite over time from 1.2 and 3.1 liters · h(-1), respectively, after a single dose to 2.2 and 5.0 liters · h(-1), respectively, after 14 once-daily doses, with no plateau being reached by day 14. In clinical trial simulations using the final model, rifapentine demonstrated less-than-dose-proportional pharmacokinetics, but there was no plateau in exposures over the dose range tested (450 to 1,800 mg), and divided dosing increased exposures significantly. Thus, the proposed compartmental model incorporating daily dosing of rifapentine over a wide range of doses and time-related changes in bioavailability and clearance provides a useful tool for estimation of drug exposure that can be used to optimize rifapentine dosing for TB treatment. (This study has been registered at ClinicalTrials.gov under registration no. NCT01162486.).

Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Figures

FIG 1

Rifapentine model structure. Abbreviations: ktr, transit rate constant; ka, absorption rate constant; n, number of transit compartments; k, rifapentine elimination rate constant; CL, rifapentine clearance; V, rifapentine volume of distribution; km, metabolite elimination rate constant; CLm, metabolite clearance; Vm, metabolite volume of distribution.

FIG 2

Observed relationship between interindividual variability in bioavailability and oral dose (left) and study arm (right). The line represents the Lowess smooth through the data.

FIG 3

Observed relationship between subject-specific Bayesian estimates of clearance (ETA) estimated at days 1, 5, 9, and 14 on treatment. If within-subject variability in clearance is truly random, there would not be a visible trend with time. White line within each box, median population value.

FIG 4

Visual predictive check for blood levels of rifapentine (left) and metabolite (right) for different days on treatment. Solid black lines, median of the observed data; dotted black lines, 5th and 95th percentiles of the observed data; middle gray shaded area, simulated median with uncertainty (for 500 repetitions of the visual predictive check); lower and upper gray shaded areas, simulated 5th and 95th percentiles with uncertainty, respectively.

FIG 5

Clinical trial simulations of once-daily (QD) versus twice-daily (BID) dosing to be tested in ACTG study A5311 as a strategy of increasing RPT exposure.

FIG 6

Predicted AUC distribution in patient study 29X. Predictions were based on the final model without (left panel) and with (right panel) the potential effect of high-fat food. Each box represents the simulated distribution of AUCs following the dosing criteria used in study 29X. White line within each box, population median; circles, outliers.