Population Pharmacokinetics of Rifampicin in Chinese Patients With Pulmonary Tuberculosis

Population pharmacokinetics/pharmacodynamics of minocycline plus rifampicin in patients with complicated skin and skin structure infections caused by MRSA

BACKGROUND

The population pharmacokinetics/pharmacodynamics (PK/PD) of minocycline, rifampicin and linezolid in patients with complicated skin and soft tissue infections (cSSTIs) caused by MRSA are described.

METHODS

Samples were collected in a Phase 4 study of oral minocycline plus rifampicin versus linezolid showing minocycline plus rifampicin to be non-inferior to linezolid. Antibiotics were assayed by HPLC or LC-MS, and a population PK model was developed using Pmetrics. The association between PK/PD indices and patient outcomes was explored.

RESULTS

A three-compartment model (with an absorption compartment) with first-order input and elimination best described the data for the three drugs. No covariates were included in the final model. The population median values (95% credibility limits) of the clearance and volume of distribution were 7.412 L/h (5.121-8.361) and 14.155 L (6.799-33.901) for minocycline, 5.683 L/h (3.703-7.726) and 7.736 L (6.031-8.948) for rifampicin, and 1.970 L/h (1.326-2.499) and 20.169 L (12.857-32.629) for linezolid, respectively. Maximum a posteriori probability-Bayesian estimation plots of observed versus predicted had a slope of 0.999 r20.967 for minocycline, slope 0.998 r20.769 for rifampicin and slope 0.998 r20.895 for linezolid. PK/PD indices were not related to clinical outcome. Taking a translational minocycline fAUC24h/MIC target of >0.5 for minocycline in the presence of rifampicin, 96% (49/51) of patients reached the target.

CONCLUSIONS

Population PK models of minocycline, rifampicin and linezolid were developed in patients with MRSA cSSTI and almost all patients reached the predefined PD index targets. As a result, neither AUC, MIC nor the AUC/MIC ratio could be related to clinical outcome.

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.

Mathematical Model for Growth and Rifampicin-Dependent Killing Kinetics of Escherichia coli Cells

Antibiotic resistance is a global health threat. We urgently need better strategies to improve antibiotic use to combat antibiotic resistance. Currently, there are a limited number of antibiotics in the treatment repertoire of existing bacterial infections. Among them, rifampicin is a broad-spectrum antibiotic against various bacterial pathogens. However, during rifampicin exposure, the appearance of persisters or resisters decreases its efficacy. Hence, to benefit more from rifampicin, its current standard dosage might be reconsidered and explored using both computational tools and experimental or clinical studies. In this study, we present the mathematical relationship between the concentration of rifampicin and the growth and killing kinetics of Escherichia coli cells. We generated time-killing curves of E. coli cells in the presence of 4, 16, and 32 μg/mL rifampicin exposures. We specifically focused on the oscillations with decreasing amplitude over time in the growth and killing kinetics of rifampicin-exposed E. coli cells. We propose the solution form of a second-order linear differential equation for a damped oscillator to represent the mathematical relationship. We applied a nonlinear curve fitting solver to time-killing curve data to obtain the model parameters. The results show a high fitting accuracy.

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.

Impact of rifampicin dose in bone and joint prosthetic device infections due to Staphylococcus spp: a retrospective single-center study in France

BACKGROUND

Prosthetic joint infections (PJI) are a major cause of morbidity and mortality burden worldwide. While surgical management is well defined, rifampicin (RIF) dose remains controversial. The aim of our study was to determine whether Rifampicin dose impact infection outcomes in PJI due to Staphylococcus spp.

METHODS

single-center retrospective study including 411 patients with PJI due to Rifampicin-sensitive Staphylococcus spp. Rifampicine dose was categorized as follow: < 10 mg/kg/day, 10-20 mg/kg/day or > 20 mg/kg/day. The primary endpoint was patient recovery, defined as being free of infection during 12 months after the end of the initial antibiotic course.

RESULTS

321 (78%) received RIF for the full antibiotic course. RIF dose didn't affect patients recovery rate with 67, 76 and 69% in the < 10, 10-20 and > 20 mg/kg/day groups, respectively (p = 0.083). In univariate analysis, recovery rate was significantly associated with gender (p = 0.012) but not to RIF dose, or Staphylococcus phenotype (aureus or coagulase-negative). In multivariate analysis, age (p = 0.01) and treatment duration (p <  0.01) were significantly associated with recovery rate.

CONCLUSION

These data suggest that lower doses of RIF are as efficient and safe as the recommended high-dose French regimen in the treatment of PJI.

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.

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.

Global Urine Metabolomics in Patients Treated with First-Line Tuberculosis Drugs and Identification of a Novel Metabolite of Ethambutol

Population level variation of drug metabolism phenotype (DMP) has great implications in treatment outcome, drug-related side effects, and resistance development. In this study, we used a gas chromatography-time of flight-mass spectrometry (GC-TOF-MS)-based untargeted urine metabolomics approach to understand the DMP of a tuberculosis (TB) patient cohort (n= 20) from Tripura, a state in the northeastern part of India. Urine samples collected at different postdose time points (2 h, 6 h, 12 h, 24 h, 36 h, and 48 h) from these newly diagnosed TB patients receiving first-line anti-TB drugs were analyzed, and we have successfully detected three of the four first-line drugs,viz, isoniazid (INH), ethambutol (ETB), and pyrazinamide (PZA). The majority of their known metabolites, acetyl-isoniazid (AcINH), isonicotinic acid (INA), isonicotinuric acid (INTA), 2,2'-(ethylenediimino)-dibutyric acid (EDBA), 5-hydroxypyrazinamide (5OH-PZA), pyrazinoic acid (POA), and 5-hydroxypyrazinoic acid (5OH-POA), were also detected. Analyzing the variation in abundances of drugs and their known metabolites and calculating the metabolic ratios in these samples, we offer comprehensive DMP information on this small patient cohort that represents Tripura, India. The majority (75%) of these patients are found to be slow acetylators of INH. The average metabolic ratios of POA/PZA and 5OH-POA/POA are 3.16 ± 3.03 and 6.09 ± 6.15, respectively. Employing correlation analysis of the metabolomics metadata and a manual prediction of drug catabolism, we have proposed 2-aminobutyric acid (AABA) as a novel metabolite of ETB. These observations indicate the usefulness of GC-MS-based metabolomics to characterize the DMP at a population level and also to identify novel drug metabolites.