Population pharmacokinetics of rifampicin in Mexican patients with tuberculosis

State of the art of real-life concentration monitoring of rifampicin and its implementation contextualized in resource-limited settings: the Tanzanian case

The unique medical and socio-economic situation in each country affected by TB creates different epidemiological contexts, thus providing exploitable loopholes for the spread of the disease. Country-specific factors such as comorbidities, health insurance, social stigma or the rigidity of the health system complicate the management of TB and the overall outcome of each patient. First-line TB drugs are administered in a standardized manner, regardless of patient characteristics other than weight. This approach does not consider patient-specific conditions such as HIV infection, diabetes mellitus and malnutrition, which can affect the pharmacokinetics of TB drugs, their overall exposure and response to treatment. Therefore, the 'one-size-fits-all' approach is suboptimal for dealing with the underlying inter-subject variability in the pharmacokinetics of anti-TB drugs, further complicated by the recent increased dosing regimen of rifampicin strategies, calling for a patient-specific methodology. In this context, therapeutic drug monitoring (TDM), which allows personalized drug dosing based on blood drug concentrations, may be a legitimate solution to address treatment failure. This review focuses on rifampicin, a critical anti-TB drug, and examines its suitability for TDM and the socio-economic factors that may influence the implementation of TDM in clinical practice in resource-limited settings, illustrated by Tanzania, thereby contributing to the advancement of personalized TB treatment.

Assessment of body mass-related covariates for rifampicin pharmacokinetics in healthy Caucasian volunteers

PURPOSE

Currently, body weight-based dosing of rifampicin is recommended. But lately, fat-free mass (FFM) was reported to be superior to body weight (BW). The present evaluation aimed to assess the influence of body mass-related covariates on rifampicin's pharmacokinetics (PK) parameters in more detail using non-linear mixed effects modeling (NLMEM).

METHODS

Twenty-four healthy Caucasian volunteers were enrolled in a bioequivalence study, each receiving a test and a reference tablet of 600 mg of rifampicin separated by a wash-out period of at least 9 days. Monolix version 2023R1 was used for NLMEM. Monte Carlo simulations (MCS) were performed to visualize the relationship of body size descriptors to the exposure to rifampicin.

RESULTS

A one-compartment model with nonlinear (Michaelis-Menten) elimination and zero-order absorption kinetics with a lag time best described the data. The covariate model including fat-free mass (FFM) on volume of distribution (V/F) and on maximum elimination rate (Vmax/F) lowered the objective function value (OFV) by 56.4. The second-best covariate model of sex on V/F and Vmax/F and BW on V/F reduced the OFV by 51.2. The decrease in unexplained inter-individual variability on Vmax/F in both covariate models was similar. For a given dose, MCS showed lower exposure to rifampicin with higher FFM and accordingly in males compared to females with the same BW and body height.

CONCLUSION

Our results indicate that beyond BW, body composition as reflected by FFM could also be relevant for optimized dosing of rifampicin. This assumption needs to be studied further in patients treated with rifampicin.

Effect of Interindividual Variability in Metabolic Clearance and Relative Bioavailability on Rifampicin Exposure in Tuberculosis Patients with and without HIV Co-Infection: Does Formulation Quality Matter?

The present study aims to characterise the pharmacokinetics of rifampicin (RIF) in tuberculosis (TB) patients with and without HIV co-infection, considering the formation of 25-O-desacetyl-rifampicin (desRIF). It is hypothesised that the metabolite formation, HIV co-infection and drug formulation may further explain the interindividual variation in the exposure to RIF. Pharmacokinetic, clinical, and demographic data from TB patients with (TB-HIV+ group; n = 18) or without HIV (TB-HIV- group; n = 15) who were receiving RIF as part of a four-drug fixed-dose combination (FDC) regimen (RIF, isoniazid, pyrazinamide, and ethambutol) were analysed, along with the published literature data on the relative bioavailability of different formulations. A population pharmacokinetic model, including the formation of desRIF, was developed and compared to a model based solely on the parent drug. HIV co-infection does not alter the plasma exposure to RIF and the desRIF formation does not contribute to the observed variability in the RIF disposition. The relative bioavailability and RIF plasma exposure were significantly lower than previously reported for the standard regimen with FDC tablets. Furthermore, participants weighting less than 50 kg do not reach the same RIF plasma exposure as compared to those weighting >50 kg. In conclusion, as no covariate was identified other than body weight on CL/F and Vd/F, low systemic exposure to RIF is likely to be caused by the low bioavailability of the formulation.

Population pharmacokinetic model of rifampicin for personalized tuberculosis pharmacotherapy: Effects of SLCO1B1 polymorphisms on drug exposure

BACKGROUND

Rifampicin (RIF) exhibits high pharmacokinetic (PK) variability among individuals; a low plasma concentration might result in unfavorable treatment outcomes and drug resistance. This study evaluated the contributions of non- and genetic factors to the interindividual variability of RIF exposure, then suggested initial doses for patients with different weight bands.

METHODS

This multicenter prospective cohort study in Korea analyzed demographic and clinical data, the solute carrier organic anion transporter family member 1B1 (SLCO1B1) genotypes, and RIF concentrations. Population PK modeling and simulations were conducted using nonlinear mixed-effect modeling.

RESULTS

In total, 879 tuberculosis (TB) patients were divided into a training dataset (510 patients) and a test dataset (359 patients). A one-compartment model with allometric scaling for effect of body size best described the RIF PKs. The apparent clearance (CL/F) was 16.6% higher among patients in the SLCO1B1 rs4149056 wild-type group than among patients in variant group, significantly decreasing RIF exposure in the wild-type group. The developed model showed better predictive performance compared with previously reported models. We also suggested that patients with body weights of <40 kg, 40-55 kg, 55-70 kg, and >70 kg patients receive RIF doses of 450, 600, 750, and 1050 mg/day, respectively.

CONCLUSIONS

Total body weight and SLCO1B1 rs4149056 genotypes were the most significant covariates that affected RIF CL/F variability in Korean TB patients. We suggest initial doses of RIF based on World Health Organization weight-band classifications. The model may be implemented in treatment monitoring for TB patients.

Development of population pharmacokinetics model and Bayesian estimation of rifampicin exposure in Indonesian patients with tuberculosis

BACKGROUND

Interindividual variability in the pharmacokinetics (PK) of anti-tuberculosis (TB) drugs is the leading cause of treatment failure. Herein, we evaluated the influence of demographic, clinical, and genetic factors that cause variability in RIF PK parameters in Indonesian TB patients.

METHODS

In total, 210 Indonesian patients with TB (300 plasma samples) were enrolled in this study. Clinical data, solute carrier organic anion transporter family member-1B1 (SLCO1B1) haplotypes *1a, *1b, and *15, and RIF concentrations were analyzed. The population PK model was developed using a non-linear mixed effect method.

RESULTS

A one-compartment model with allometric scaling adequately described the PK of RIF. Age and SLCO1B1 haplotype *15 were significantly associated with variability in apparent clearance (CL/F). For patients in their 40s, each 10-year increase in age was associated with a 10% decrease in CL/F (7.85 L/h). Patients with the SLCO1B1 haplotype *15 had a 24% lower CL/F compared to those with the wild-type. Visual predictive checks and non-parametric bootstrap analysis indicated good model performance.

CONCLUSION

Age and SLCO1B1 haplotype *15 were significant covariates of RIF CL/F. Geriatric patients with haplotype *15 had significantly greater exposure to RIF. The model could optimize TB pharmacotherapy through its application in therapeutic drug monitoring (clinical trial no. NCT05280886).

Population Pharmacokinetics Analyses of Rifampicin in Adult and Children Populations: A Systematic Review

AIMS

Rifampicin has become an essential component as the first-line therapy for pulmonary tuberculosis (PTB). Several population pharmacokinetic (PK) studies on rifampicin in the adult and children population have been studied previously. Therefore, the aims of the systematic review were (i) to summarize the relevant published studies and significant covariates that influence the PK of rifampicin across different populations, (ii) to identify any knowledge gap that requires additional research in the future.

METHODS

A total of 121 relevant population PK articles were systematically identified using PubMed and Scopus from inception to October 2021. Review articles, in-vitro, and physiological methods, animal studies, and noncompartmental analysis were excluded.

RESULTS

19 studies which 16 involved adults, two involved children, and one involved both adults and children were included in the review. The structural model of rifampicin can be described as one compartment with a transient compartment absorption model and first-order elimination in most of the studies. Pharmaceutical formulation, body weight, gender, pregnancy status, diabetes, and nutritional supplementation were found to be the significant covariates that affect the PK parameters. External validation of the developed PK model was only conducted in two studies.

CONCLUSIONS

The source of variability for PK parameters of rifampicin remains inconsistent and poorly understood even though there were many potential covariates investigated in the selected studies. Exploring other possible factors and implementation a strict sampling strategy by considering the induction effects might unravel precise and reliable information. Furthermore, external validation should be frequently conducted to produce better predictability of model performance.

Population Pharmacokinetics and Bayesian Dose Adjustment to Advance TDM of Anti-TB Drugs

Tuberculosis (TB) is still the number one cause of death due to an infectious disease. Pharmacokinetics and pharmacodynamics of anti-TB drugs are key in the optimization of TB treatment and help to prevent slow response to treatment, acquired drug resistance, and adverse drug effects. The aim of this review was to provide an update on the pharmacokinetics and pharmacodynamics of anti-TB drugs and to show how population pharmacokinetics and Bayesian dose adjustment can be used to optimize treatment. We cover aspects on preclinical, clinical, and population pharmacokinetics of different drugs used for drug-susceptible TB and multidrug-resistant TB. Moreover, we include available data to support therapeutic drug monitoring of these drugs and known pharmacokinetic and pharmacodynamic targets that can be used for optimization of therapy. We have identified a wide range of population pharmacokinetic models for first- and second-line drugs used for TB, which included models built on NONMEM, Pmetrics, ADAPT, MWPharm, Monolix, Phoenix, and NPEM2 software. The first population models were built for isoniazid and rifampicin; however, in recent years, more data have emerged for both new anti-TB drugs, but also for defining targets of older anti-TB drugs. Since the introduction of therapeutic drug monitoring for TB over 3 decades ago, further development of therapeutic drug monitoring in TB next steps will again depend on academic and clinical initiatives. We recommend close collaboration between researchers and the World Health Organization to provide important guideline updates regarding therapeutic drug monitoring and pharmacokinetics/pharmacodynamics.

Population Pharmacokinetic Models of Antituberculosis Drugs in Patients: A Systematic Critical Review

BACKGROUND

Tuberculosis (TB) remains one of the most important infectious diseases. Population pharmacokinetic (pop-PK) models are widely used to individualize dosing regimens of several antibiotics, but their application in anti-TB drug studies is scant. The aim of this study was to provide an insight regarding the status of pop-PK for these drugs and to compare results obtained through both parametric and nonparametric approaches to design precise dosage regimens.

METHODS

First, a systematic approach was implemented, searching in PubMed and Google Scholar. Articles that did not include human patients, that lacked an explicit structural model, that analyzed drugs inactive against M. tuberculosis, or were without full-text access, were excluded. Second, the PK parameters were summarized and categorized as parametric versus nonparametric results. Third, a Monte Carlo simulation was performed in Pmetrics using the results of both groups, and an error term was built to describe the imprecision of each PK modeling approach.

RESULTS

Thirty-three articles reporting at least 1 pop-PK model of 19 anti-TB drug were found; 46 different models including PK parameter estimates and their relevant covariates were also reported. Only 9 models were based on nonparametric approaches. Rifampin was the drug most studied, but only using parametric approaches. The simulations showed that nonparametric approaches improve the error term compared with parametric approaches.

CONCLUSIONS

More and better models, ideally using nonparametric approaches linked with clear pharmacodynamic goals, are required to optimize anti-TB drug dosing, as recommended in the WHO End TB strategy.

Drug exposure of first-line anti-tuberculosis drugs in China: A prospective pharmacological cohort study

AIM

Exploring the need for optimization of drug exposure to improve tuberculosis (TB) treatment outcome is of great importance. We aimed to describe drug exposure at steady state as well as the population pharmacokinetics (PK) of rifampicin (RIF), isoniazid (INH) and pyrazinamide (PZA) in Chinese TB patients.

METHODS

A prospective multicentre PK study of RIF, INH and PZA was conducted in China between January 2015 and December 2017. Six blood samples were collected from each subject for drug concentration measurement. Nonlinear mixed effect analyses were used to develop population PK models.

RESULTS

In total, 217 patients were included. Positive correlations between body weight, clearance and volume of distribution were identified for RIF and PZA, whereas body weight only influenced clearance for INH. In addition, males had higher RIF clearance and thus lower RIF exposure than women. Acetylator status was significantly associated with INH clearance as INH exposure in intermediate and fast acetylators was significantly lower than in slow acetylators, especially in low-weight bands. Simulations also showed significantly lower drug exposures in low-weight bands for all three drugs. Patients weighing <38 kg were respectively exposed to 30.4%, 45.9% and 18.0% lower area under the concentration-time curve of RIF, INH and PZA than those weighing ≥70 kg. Higher doses by addition of one fixed-dose combination tablet or 150 mg INH were simulated and found to be effective in improving INH drug exposures, especially in low-weight bands.

CONCLUSION

PK variability of first-line anti-TB drugs is common in Chinese TB patients. The developed population PK models can be used to optimize drug exposures in Chinese patients. Moreover, standard dosing needs to be adjusted to increase target attainment.

A population approach of rifampicin pharmacogenetics and pharmacokinetics in Mexican patients with tuberculosis

The aim of this study was to develop a population pharmacokinetic model of rifampicin (RMP) in Mexican patients with tuberculosis (TB) to evaluate the influence of anthropometric and clinical covariates, as well as genotypic variants associated with MDR1 and OATP1B1 transporters. A prospective study approved by Research Ethics Committee was performed at Hospital Central in San Luis Potosí, Mexico. TB patients under DOTS scheme and who signed informed consent were consecutively included. Anthropometric and clinical information was retrieved from medical records. Single nucleotide polymorphisms in MDR1 (C3435T) and SLCO1B1 (A388G and T521C) genes were evaluated. RMP plasma concentrations and time data were assessed with NONMEM software. A total of 71 Mexican TB patients from 18 to 72 years old were included for RMP quantification from 0.3 to 12 h after dose; 329 and 97 plasma concentrations were available for model development and validation, respectively. Sequential process includes a typical lag time of 0.25 h prior to absorption start with a Ka of 1.24 h^-1 and a zero-order absorption of 0.62 h to characterize the gradual increase in RMP plasma concentrations. Final model includes total body weight in volume of distribution (0.7 L/kg, CV = 26.8%) and a total clearance of 5.96 L/h (CV = 38.5%). Bioavailability was modified according to time under treatment and generic formulation administration. In conclusion, a population pharmacokinetic model was developed to describe the variability in RMP plasma concentrations in Mexican TB patients. Genetic variants evaluated did not showed significant influence on pharmacokinetic parameters. Final model will allow therapeutic drug monitoring at early stages.

Personalized Tuberculosis Treatment Through Model-Informed Dosing of Rifampicin

BACKGROUND AND OBJECTIVE

This study proposes a model-informed approach for therapeutic drug monitoring (TDM) of rifampicin to improve tuberculosis (TB) treatment.

METHODS

Two datasets from pulmonary TB patients were used: a pharmacokinetic study (34 patients, 373 samples), and TDM data (96 patients, 391 samples) collected at Radboud University Medical Center, The Netherlands. Nine suitable population pharmacokinetic models of rifampicin were identified in the literature and evaluated on the datasets. A model developed by Svensson et al. was found to be the most suitable based on graphical goodness of fit, residual diagnostics, and predictive performance. Prediction of individual area under the concentration-time curve from time zero to 24 h (AUC₂₄) and maximum concentration (C_max) employing various sampling strategies was compared with a previously established linear regression TDM strategy, using sampling at 2, 4, and 6 h, in terms of bias and precision (mean error [ME] and root mean square error [RMSE]).

RESULTS

A sampling strategy using 2- and 4-h blood collection was selected to be the most suitable. The bias and precision of the two strategies were comparable, except that the linear regression strategy was more biased in prediction of the AUC₂₄ than the model-informed approach (ME of 9.9% and 1.5%, respectively). A comparison of resulting dose advice, using predictions on a simulated dataset, showed no significant difference in sensitivity or specificity between the two methods. The model was successfully implemented in the InsightRX precision dosing platform.

CONCLUSION

Blood sampling at 2 and 4 h, combined with model-based prediction, can be used instead of the currently used linear regression strategy, shortening the sampling by 2 h and one sampling point without performance loss while simultaneously offering flexibility in sampling times.

Perspectives from the Innovation and Quality Consortium Induction Working Group on Factors Impacting Clinical Drug-Drug Interactions Resulting from Induction: Focus on Cytochrome 3A Substrates

A recent publication from the Innovation and Quality Consortium Induction Working Group collated a large clinical data set with the goal of evaluating the accuracy of drug-drug interaction (DDI) prediction from in vitro data. Somewhat surprisingly, comparison across studies of the mean- or median-reported area under the curve ratio showed appreciable variability in the magnitude of outcome. This commentary explores the possible drivers of this range of outcomes observed in clinical induction studies. While recommendations on clinical study design are not being proposed, some key observations were informative during the aggregate analysis of clinical data. Although DDI data are often presented using median data, individual data would enable evaluation of how differences in study design, baseline expression, and the number of subjects contribute. Since variability in perpetrator pharmacokinetics (PK) could impact the overall DDI interpretation, should this be routinely captured? Maximal induction was typically observed after 5-7 days of dosing. Thus, when the half-life of the inducer is less than 30 hours, are there benefits to a more standardized study design? A large proportion of CYP3A4 inducers were also CYP3A4 inhibitors and/or inactivators based on in vitro data. In these cases, using CYP3A selective substrates has limitations. More intensive monitoring of changes in area under the curve over time is warranted. With selective CYP3A substrates, the net effect was often inhibition, whereas less selective substrates could discern induction through mechanisms not susceptible to inhibition. The latter included oral contraceptives, which raise concerns of reduced efficacy following induction. Alternative approaches for modeling induction, such as applying biomarkers and physiologically based pharmacokinetic modeling (PBPK), are also considered. SIGNIFICANCE STATEMENT: The goal of this commentary is to stimulate discussion on whether there are opportunities to optimize clinical drug-drug interaction study design. The overall aim is to reduce, understand and contextualize the variability observed in the magnitude of induction across reported clinical studies. A large clinical CYP3A induction dataset was collected and further analyzed to identify trends and gaps. Reporting individual victim PK data, characterizing perpetrator PK and including additional PK assessments for mixed-mechanism perpetrators may provide insights into how these factors impact differences observed in clinical outcomes. The potential utility of biomarkers and PBPK modeling are discussed in considering future directions.

Suboptimal Exposure to Anti-TB Drugs in a TBM/HIV+ Population Is Not Related to Antiretroviral Therapy

A placebo-controlled trial that compares the outcomes of immediate vs. deferred initiation of antiretroviral therapy in HIV +ve tuberculous meningitis (TBM) patients was conducted in Vietnam in 2011. Here, the pharmacokinetics of rifampicin, isoniazid, pyrazinamide, and ethambutol were investigated in the presence and absence of anti-HIV treatment in 85 patients. Pharmacokinetic analyses show that HIV therapy has no significant impact on the pharmacokinetics of TB drugs in this cohort. The same population, however, displayed generally low cerebrospinal fluid (CSF) and systemic exposures to rifampicin compared to previously reported HIV -ve cohorts. Elevated CSF concentrations of pyrazinamide, on the other hand, were strongly and independently correlated with increased mortality and neurological toxicity. The findings suggest that the current standard dosing regimens may put the patient at risk of treatment failure from suboptimal rifampicin exposure, and potentially increasing the risk of adverse central nervous system events that are independently correlated with pyrazinamide CSF exposure.

Population pharmacokinetics of rifampicin in adult patients with osteoarticular infections: interaction with fusidic acid

AIMS

Rifampicin represents the key antibiotic for the management of osteoarticular infections. An important pharmacokinetic variability has already been described, particularly for absorption and metabolism. All previous pharmacokinetic studies have been focused only on patients treated for tuberculosis. The objective of the present study was to describe a population pharmacokinetic model of rifampicin in patients with staphylococcal osteoarticular infections, which has not been investigated to date.

METHOD

Rifampicin concentrations were collected retrospectively from 62 patients treated with oral rifampicin 300 mg three times daily. Plasma concentration-time data were analysed using NONMEM to estimate population pharmacokinetic parameters. Demographic data, infection characteristics and antibiotics taken in addition to rifampicin antibiotics were investigated as covariates.

RESULTS

A one-compartment model, coupled to a transit absorption model, best described the rifampicin data. Fusidic acid coadministration was identified as a covariate in rifampicin pharmacokinetic parameters. The apparent clearance and apparent central volume of distribution mean values [95% confidence interval (CI)] were 5.1 1 h^-1 (1.2, 8.2 1 h^-1 )/23.8 l (8.9, 38.7 l) and 13.7 1 h^-1 (10.6, 18.0 1 h^-1 )/61.1 1 (40.8, 129.0 1) for patients with and without administration of fusidic acid, respectively. Interindividual variability (95% CI) in the apparent clearance and apparent central volume of distribution were 72.9% (49.5, 86.0%) and 59.1% (5.5, 105.4%), respectively. Residual variability was 2.3 mg l^-1 (1.6, 2.6 mg l^-1 ).

CONCLUSION

We developed the first population pharmacokinetic model of rifampicin in patients with osteoarticular infections. Our model demonstrated that fusidic acid affects rifampicin pharmacokinetics, leading to potential high drug exposure. This finding suggests that fusidic acid dosing regimens should be reconsidered.

The challenges of pharmacokinetic variability of first-line anti-TB drugs

INTRODUCTION

Inter-individual variations in the pharmacokinetics (PK) of anti-TB drugs are known to occur, which could have important therapeutic implications in patient management. Areas covered: We compiled factors responsible for PK variability of anti-TB drugs reported from different settings that would give a better understanding about the challenges of PK variability of anti-TB medications. We searched PubMed data base and Google scholar from 1976 to the present using the key words 'Pharmacokinetics', 'pharmacokinetic variability', 'first-line anti-TB therapy', 'Rifampicin', 'Isoniazid', 'Ethambutol', 'Pyrazinamide', 'food', 'nutritional status', 'HIV', 'diabetes', 'genetic polymorphisms' and 'pharmacokinetic interactions'. We also included abstracts from scientific meetings and review articles. Expert commentary: A variety of host and genetic factors can cause inter-individual variations in the PK of anti-TB drugs. PK studies conducted in various settings have adopted different designs, PK sampling time points, drug estimation methodologies. Hence comparison and interpretation of these results should be done with caution More phamacogenomic studies in different patient populations are needed for further understanding.

Validation and Application of a Dried Blood Spot Assay for Biofilm-Active Antibiotics Commonly Used for Treatment of Prosthetic Implant Infections

Dried blood spot (DBS) antibiotic assays can facilitate pharmacokinetic (PK)/pharmacodynamic (PD) studies in situations where venous blood sampling is logistically difficult. We sought to develop, validate, and apply a DBS assay for rifampin (RIF), fusidic acid (FUS), and ciprofloxacin (CIP). These antibiotics are considered active against organisms in biofilms and are therefore commonly used for the treatment of infections associated with prosthetic implants. A liquid chromatography-mass spectroscopy DBS assay was developed and validated, including red cell partitioning and thermal stability for each drug and the rifampin metabolite desacetyl rifampin (Des-RIF). Plasma and DBS concentrations in 10 healthy adults were compared, and the concentration-time profiles were incorporated into population PK models. The limits of quantification for RIF, Des-RIF, CIP, and FUS in DBS were 15 μg/liter, 14 μg/liter, 25 μg/liter, and 153 μg/liter, respectively. Adjusting for hematocrit, red cell partitioning, and relative recovery, DBS-predicted plasma concentrations were comparable to measured plasma concentrations for each antibiotic (r > 0.95; P < 0.0001), and Bland-Altman plots showed no significant bias. The final population PK estimates of clearance, volume of distribution, and time above threshold MICs for measured and DBS-predicted plasma concentrations were comparable. These drugs were stable in DBSs for at least 10 days at room temperature and 1 month at 4°C. The present DBS antibiotic assays are robust and can be used as surrogates for plasma concentrations to provide valid PK and PK/PD data in a variety of clinical situations, including therapeutic drug monitoring or studies of implant infections.

An Exposure-Response Modeling Approach to Examine the Relationship Between Potency of CYP3A Inducer and Plasma 4β-Hydroxycholesterol in Healthy Subjects

The objectives of this analysis were to establish the exposure-response relationship between plasma rifampicin and 4β-hydroxycholesterol (4βHC) concentration and to estimate the effect of weak, moderate, and potent CYP3A induction. Plasma rifampicin and 4βHC concentration-time data from a drug-drug interaction study with rifampicin 600 mg were used for model development. An indirect response model with an effect compartment described the relationship between rifampicin and 4βHC concentrations. The model predicted that the equilibration t_1/2 and 4βHC t_1/2 were 72.8 and 142 hours, respectively. EM₅₀ and E_max of rifampicin induction were 32.6 μg and 8.39-fold, respectively. The population PK-PD model was then used to simulate the effects of rifampicin 10, 20, and 100 mg on plasma 4βHC for up to 21 days, in which rifampicin 10, 20, and 100 mg were used to represent weak, moderate, and strong inducers, respectively. The model-predicted median (5th, 95th percentiles) 1.13 (1.04, 1.44)-, 1.28 (1.10, 1.71)-, and 2.10 (1.45, 3.49)-fold increases in plasma 4βHC after 14-day treatment with rifampicin 10, 20, and 100 mg, respectively. A new drug candidate can likely be classified as a weak, moderate, or strong inducer if baseline-normalized plasma 4βHC increases by <1.13-, 1.13- to 2.10-, or >2.10-fold, respectively, after 14 days of dosing.

Population Pharmacokinetics of Rifampicin in Chinese Patients With Pulmonary Tuberculosis

Rifampicin (RIF) induces cytochrome P450, which in turn catalyzes drug metabolism; however, pharmacokinetic studies on this phenomenon in the Chinese population, especially in the context of disease, are limited. Therefore, we sought to establish population-based pharmacokinetic models of RIF in a Chinese population with pulmonary tuberculosis (TB). Clinical data were retrospectively collected from 54 patients with pulmonary TB and analyzed alongside RIF blood levels from 95 samples collected prior to RIF administration and between 2 and 12 hours after treatment. HPLC was used to measure serum RIF concentrations. A nonlinear mixed model used to characterize RIF pharmacokinetics and the data generated from the present study were validated using a bootstrap method. Covariates, including demographics, as well as hematological and biological indicators were analyzed. We observed a 1-compartment model with first-order absorption. Typical population values of apparent clearance (CL/F) and apparent volume of distribution (VD /F) were 4.02 L/h and 57.8 L, respectively. No covariate significantly changed the parameters of CL/F and VD . The present study may serve as a foundation for individualized therapy and offer a basis for pharmacokinetic-pharmacodynamic (PK-PD) analysis.

Clinical Pharmacokinetics of Rifampin in Patients with Tuberculosis and Type 2 Diabetes Mellitus: Association with Biochemical and Immunological Parameters

Tuberculosis (TB) remains a major public health issue due to the increasing incidence of type 2 diabetes mellitus (T2DM), which exacerbates the clinical course of TB and increases the risk of poor long-term outcomes. The aim of this study was to characterize the pharmacokinetics of rifampin (RIF) and its relationship with biochemical and immunological parameters in patients with TB and T2DM. The biochemical and immunological parameters were assessed on the same day that the pharmacokinetic evaluation of RIF was performed. Factors related to the metabolic syndrome that is characteristic of T2DM patients were not detected in the TB-T2DM group (where predominant malnutrition was present) or in the TB group. Percentages of CD8(+) T lymphocytes and NK cells were diminished in the TB and TB-T2DM patients, who had high tumor necrosis factor alpha (TNF-α) and low interleukin-17 (IL-17) levels compared to healthy volunteers. Delayed RIF absorption was observed in the TB and TB-T2DM patients; absorption was poor and slower in the latter group due to poor glycemic control. RIF clearance was also slower in the diabetic patients, thereby prolonging the mean residence time of RIF. There was a significant association between glycemic control, increased TNF-α serum concentrations, and RIF pharmacokinetics in the TB-T2DM patients. These altered metabolic and immune conditions may be factors to be considered in anti-TB therapy management when TB and T2DM are concurrently present.

Pharmacokinetic Modeling and Optimal Sampling Strategies for Therapeutic Drug Monitoring of Rifampin in Patients with Tuberculosis

Rifampin, together with isoniazid, has been the backbone of the current first-line treatment of tuberculosis (TB). The ratio of the area under the concentration-time curve from 0 to 24 h (AUC0-24) to the MIC is the best predictive pharmacokinetic-pharmacodynamic parameter for determinations of efficacy. The objective of this study was to develop an optimal sampling procedure based on population pharmacokinetics to predict AUC0-24 values. Patients received rifampin orally once daily as part of their anti-TB treatment. A one-compartmental pharmacokinetic population model with first-order absorption and lag time was developed using observed rifampin plasma concentrations from 55 patients. The population pharmacokinetic model was developed using an iterative two-stage Bayesian procedure and was cross-validated. Optimal sampling strategies were calculated using Monte Carlo simulation (n = 1,000). The geometric mean AUC0-24 value was 41.5 (range, 13.5 to 117) mg · h/liter. The median time to maximum concentration of drug in serum (Tmax) was 2.2 h, ranging from 0.4 to 5.7 h. This wide range indicates that obtaining a concentration level at 2 h (C2) would not capture the peak concentration in a large proportion of the population. Optimal sampling using concentrations at 1, 3, and 8 h postdosing was considered clinically suitable with an r(2) value of 0.96, a root mean squared error value of 13.2%, and a prediction bias value of -0.4%. This study showed that the rifampin AUC0-24 in TB patients can be predicted with acceptable accuracy and precision using the developed population pharmacokinetic model with optimal sampling at time points 1, 3, and 8 h.

Effects of type 2 diabetes mellitus on the population pharmacokinetics of rifampin in tuberculosis patients

Diabetes mellitus (DM) is a well-known risk factor to develop tuberculosis (TB). Some reports indicate the serum concentrations of anti-TB drugs are lower in patients with TB and DM than those with TB only. Therefore, we developed a nonlinear mixed-effects model (NONMEM) to determine the population PK parameters of rifampin and assessed the effects of DM status in patients with TB. One-compartment linear modeling with first-order absorption was evaluated using the 206 plasma samples of rifampin from 54 patients with DM. Based on the final model, DM affected the absorption rate constant (ka) and the volume of distribution (Vd) of rifampin. The body mass index (BMI) of the patients affected rifampin clearance (CL). The ka of rifampin in patients with TB and DM was greater than that in patients with TB only. Further, the predicted Vd in patients with DM was greater than that in patients without DM. As Vd is inversely correlated with plasma concentrations, the rifampin concentrations were predicted to be lower in the patients with DM. The authors recommend administering the greater doses of rifampin for the treatment of TB in patients with DM compared with the doses for the patients without DM to prevent treatment failure.

Pharmacokinetics of rifampicin in Mexican patients with tuberculosis and healthy volunteers

OBJECTIVE

The aim of this study was to compare the pharmacokinetics (PK) of rifampicin (RIF) between healthy volunteers and patients with tuberculosis (TB).

METHODS

RIF was administered as a single 600-mg dose to 24 healthy volunteers and 24 TB patients, followed by serial blood sampling. Plasma concentrations were analysed using a chromatographic method, and the PK parameters were estimated using WinNonlin software.

KEY FINDINGS

Peak plasma concentration ranged from 6.4 to 19.9 mg/l, which was subtherapeutic for 15% of the study participants in both groups, mostly in men (71.4%). The mean area under the concentration-time curve (AUC0-24h ) did not show differences between these groups (P > 0.05). The absorption rate was slower in TB patients and the volume of distribution normalized by total body weight (Vd/kg) was greater than healthy volunteers (P < 0.05). A greater Vd and clearance were found in male subjects. The lag time (tlag) and the time before reach Cmax (Tmax) were longer for female TB patients (P < 0.05).

CONCLUSION

The main differences in PK parameters of RIF between Mexican TB patients and healthy volunteers were demonstrated in absorption and distribution processes. In addition, differences in PK parameters observed by sex should be considered for further dosing recommendations.

Serum drug concentrations predictive of pulmonary tuberculosis outcomes

BACKGROUND

Based on a hollow-fiber system model of tuberculosis, we hypothesize that microbiologic failure and acquired drug resistance are primarily driven by low drug concentrations that result from pharmacokinetic variability.

METHODS

Clinical and pharmacokinetic data were prospectively collected from 142 tuberculosis patients in Western Cape, South Africa. Compartmental pharmacokinetic parameters of isoniazid, rifampin, and pyrazinamide were identified for each patient. Patients were then followed for up to 2 years. Classification and regression tree analysis was used to identify and rank clinical predictors of poor long-term outcome such as microbiologic failure or death, or relapse.

RESULTS

Drug concentrations and pharmacokinetics varied widely between patients. Poor long-term outcomes were encountered in 35 (25%) patients. The 3 top predictors of poor long-term outcome, by rank of importance, were a pyrazinamide 24-hour area under the concentration-time curve (AUC) ≤ 363 mg·h/L, rifampin AUC ≤ 13 mg·h/L, and isoniazid AUC ≤ 52 mg·h/L. Poor outcomes were encountered in 32/78 patients with the AUC of at least 1 drug below the identified threshold vs 3/64 without (odds ratio = 14.14; 95% confidence interval, 4.08-49.08). Low rifampin and isoniazid peak and AUC concentrations preceded all cases of acquired drug resistance.

CONCLUSIONS

Low drug AUCs are predictive of clinical outcomes in tuberculosis patients.