BALB/c and Swiss mice are routinely used to validate the effectiveness of tuberculosis drug regimens, although these mouse strains fail to develop human-like pulmonary granulomas exhibiting caseous necrosis. Microenvironmental conditions within human granulomas may negatively impact drug efficacy, and this may not be reflected in non-necrotizing lesions found within conventional mouse models. The C3HeB/FeJ mouse model has been increasingly utilized as it develops hypoxic, caseous necrotic granulomas which may more closely mimic the pathophysiological conditions found within human pulmonary granulomas. Here, we examined the treatment response of BALB/c and C3HeB/FeJ mice to bedaquiline (BDQ) and pyrazinamide (PZA) administered singly and in combination. BALB/c mice consistently displayed a highly uniform treatment response to both drugs, while C3HeB/FeJ mice displayed a bimodal response composed of responsive and less-responsive mice. Plasma pharmacokinetic analysis of dissected lesions from BALB/c and C3HeB/FeJ mice revealed that PZA penetrated lesion types from both mouse strains with similar efficiency. However, the pH of the necrotic caseum of C3HeB/FeJ granulomas was determined to be 7.5, which is in the range where PZA is essentially ineffective under standard laboratory in vitro growth conditions. BDQ preferentially accumulated within the highly cellular regions in the lungs of both mouse strains, although it was present at reduced but still biologically relevant concentrations within the central caseum when dosed at 25 mg/kg. The differential treatment response which resulted from the heterogeneous pulmonary pathology in the C3HeB/FeJ mouse model revealed several factors which may impact treatment efficacy, and could be further evaluated in clinical trials.

BackgroundOne problem of interpreting population-based biomonitoring data is the reconstruction of corresponding external exposure in cases where no such data are available.ObjectivesWe demonstrate the use of a computational framework that integrates physiologically based pharmacokinetic (PBPK) modeling, Bayesian inference, and Markov chain Monte Carlo simulation to obtain a population estimate of environmental chloroform source concentrations consistent with human biomonitoring data. The biomonitoring data consist of chloroform blood concentrations measured as part of the Third National Health and Nutrition Examination Survey (NHANES III), and for which no corresponding exposure data were collected.MethodsWe used a combined PBPK and shower exposure model to consider several routes and sources of exposure: ingestion of tap water, inhalation of ambient household air, and inhalation and dermal absorption while showering. We determined posterior distributions for chloroform concentration in tap water and ambient household air using U.S. Environmental Protection Agency Total Exposure Assessment Methodology (TEAM) data as prior distributions for the Bayesian analysis.ResultsPosterior distributions for exposure indicate that 95% of the population represented by the NHANES III data had likely chloroform exposures ≤ 67 μg/L in tap water and ≤ 0.02 μg/L in ambient household air.ConclusionsOur results demonstrate the application of computer simulation to aid in the interpretation of human biomonitoring data in the context of the exposure–health evaluation–risk assessment continuum. These results should be considered as a demonstration of the method and can be improved with the addition of more detailed data.

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 ...

Pretomanid is a nitroimidazole antibiotic in late-phase clinical testing as a component of several novel antituberculosis (anti-TB) regimens. A population pharmacokinetic model for pretomanid was constructed using a Bayesian analysis of data from two phase 2 studies, PA-824-CL-007 and PA-824-CL-010, conducted with adult (median age, 27 years) patients in Cape Town, South Africa, with newly diagnosed pulmonary TB. Combined, these studies included 63 males and 59 females administered once-daily oral pretomanid doses of 50, 100, 150, 200, 600, 1,000, or 1,200 mg for 14 days. The observed pretomanid plasma concentration-time profiles for all tested doses were described by a one-compartment model with first-order absorption and elimination and a sigmoidal bioavailability dependent on dose, time, and the predose fed state. Allometric scaling with body weight (normalized to 70 kg) was used for volume of distribution and clearance, with the scaling exponents equal to 1 and 3/4, respectively. The posterior population geometric means for the clearance and volume of distribution allometric constants were 4.8 ± 0.2 liters/h and 130 ± 5 liters, respectively, and the posterior population geometric mean for the half-maximum-effect dose for the reduction of bioavailability was 450 ± 50 mg. Interindividual variability, described by the percent coefficient of variation, was 32% ± 3% for clearance, 17% ± 4% for the volume of distribution, and 74% ± 9% for the half-maximum-effect dose. This model provides a dose-exposure relationship for pretomanid in adult TB patients with potential applications to dose selection in individuals and to further clinical testing of novel pretomanid-containing anti-TB regimens.

The emergence of multidrug-resistant tuberculosis (MDR-TB) has led to a renewed interest in the use of second-line antibiotic agents. Unfortunately, there are currently dearths of information, data, and computational models that can be used to help design rational regimens for administration of these drugs. To help fill this knowledge gap, an exploratory physiologically based pharmacokinetic (PBPK) model, supported by targeted experimental data, was developed to predict the absorption, distribution, metabolism, and excretion (ADME) of the second-line agent capreomycin, a cyclic peptide antibiotic often grouped with the aminoglycoside antibiotics. To account for interindividual variability, Bayesian inference and Monte Carlo methods were used for model calibration, validation, and testing. Along with the predictive PBPK model, the first for an antituberculosis agent, this study provides estimates of various key pharmacokinetic parameter distributions and supports a hypothesized mechanism for capreomycin transport into the kidney.