A Physiologically Based Pharmacokinetic Model of Rifampin in Mice

Abstract

One problem associated with regimen-based development of antituberculosis (anti-TB) drugs is the difficulty of a systematic and thorough in vivo evaluation of the large number of possible regimens that arise from consideration of multiple drugs tested together. A mathematical model capable of simulating the pharmacokinetics and pharmacodynamics of experimental combination chemotherapy of TB offers a way to mitigate this problem by extending the use of available data to investigate regimens that are not initially tested. In order to increase the available mathematical tools needed to support such a model for preclinical anti-TB drug development, we constructed a preliminary whole-body physiologically based pharmacokinetic (PBPK) model of rifampin in mice, using data from the literature. Interindividual variability was approximated using Monte Carlo (MC) simulation with assigned probability distributions for the model parameters. An MC sensitivity analysis was also performed to determine correlations between model parameters and plasma concentration to inform future model development. Model predictions for rifampin concentrations in plasma, liver, kidneys, and lungs, following oral administration, were generally in agreement with published experimental data from multiple studies. Sensitive model parameters included those descriptive of oral absorption, total clearance, and partitioning of rifampin between blood and muscle. This PBPK model can serve as a starting point for the integration of rifampin pharmacokinetics in mice into a larger mathematical framework, including the immune response to Mycobacterium tuberculosis infection, and pharmacokinetic models for other anti-TB drugs.T uberculosis (TB), caused by Mycobacterium tuberculosis, is an infectious disease which continues to be a major cause of death in large parts of the world (1). While the current first-line therapy for drug-susceptible TB (composed of rifampin, isoniazid, pyrazinamide, and ethambutol) has been in clinical use for nearly 30 years, the emergence and spread of drug-resistant M. tuberculosis strains have motivated the search for new, more-effective combination regimens (2). Our interest here is the development of mathematical tools to supplement the animal studies necessary for the identification and testing of such new anti-TB drug regimens.The mouse is the primary animal species used for preclinical anti-TB drug development (3). Despite the differences between mice and humans, the activities of many anti-TB drugs against disease caused by M. tuberculosis are similar in both species (4, 5). Mice also provide for a range of TB susceptibility and pathology through a variety of outbred and inbred strains; a notable example is C3HeB/FeJ mice (6), which form necrotic pulmonary lesions similar to those observed in TB patients (7). The recent Critical Path to TB Drug Regimens (CPTR) Initiative (8) includes an added emphasis on the mouse for identification of new optimized three-drug regimens as a key step in advancing novel drug combinations into ...

Computational pharmacokinetics/pharmacodynamics of rifampin in a mouse tuberculosis infection model

“…The mathematical PK/PD model was constructed by combining a physiologically based pharmacokinetic (PBPK) model for rifampin in mice [23] with a host-effect model (TB model) describing M. tuberculosis infection in the lungs of mice [24]. The PBPK model provided rifampin concentration-time profiles for the major tissues and organs, including plasma and lungs, for single and multiple oral dosing.…”

Physiologically Based Pharmacokinetic Model of Rifapentine and 25-Desacetyl Rifapentine Disposition in Humans

“…1. The model comprises a set of compartments for RPT, identical to those used previously for rifampin (19), integrated with a simpler structure for the metabolite, dRPT, which consisted of only the lung and a "lumped" peripheral compartment. The compartmental species mass balance equations are similar to those used in this prior study (see the Appendix) with the exception of the description of oral absorption fraction for the parent compound and the explicit quantitation of the metabolite concentration over time described below.…”

“…Unlike previous PBPK models for anti-TB drugs (17,19), the present model was developed to make predictions of pharmacokinetics in humans. To quantify and illustrate uncertainty in simulation outputs, model development and testing included a Bayesian approach to parameter estimation and Monte Carlo simulations.…”

“…Physiological compartment volumes and blood flow rates for human and rat were obtained from a report by Brown et al (23). Compartment volumes were scaled linearly with body weight, blood flow rates were scaled with body weight to the 0.75 power (24), and the coefficients of variation for each organ volume and the arterial blood flow rate were set at 0.2 and 0.3, respectively (19,25). The resulting physiological parameters for each compartment are summarized in Table 1.…”

“…Using targeted experimental data in mice, Reisfeld et al (17) developed a PBPK model to describe the biodistribution of the second-line TB agent capreomycin, and because capreomycin is nephrotoxic (18), PBPK modeling allowed for tissue-specific concentration predictions at both the site of action for the antibiotic effect, the lung, and the site of potential toxicity, the kidney. Subsequently, Lyons et al (19) used a rich set of literature data to create a PBPK model to describe the disposition of rifampin, which, as noted earlier, is a first-line agent in current therapies for TB. Although the above models are useful in simulating and comparing the disposition of anti-TB drugs in tissues of interest, they were developed using data from rodents and currently have limited applicability to humans.…”