Effects of genetic variability on rifampicin and isoniazid pharmacokinetics in South African patients with recurrent 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.

The impact of alcohol and illicit substance use on the pharmacokinetics of first-line TB drugs

BACKGROUND

In South Africa, an estimated 11% of the population have high alcohol use, a major risk factor for TB. Alcohol and other substance use are also associated with poor treatment response, with a potential mechanism being altered TB drug pharmacokinetics.

OBJECTIVES

To investigate the impact of alcohol and illicit substance use on the pharmacokinetics of first-line TB drugs in participants with pulmonary TB.

METHODS

We prospectively enrolled participants ≥15 years old, without HIV, and initiating drug-susceptible TB treatment in Worcester, South Africa. Alcohol use was measured via self-report and blood biomarkers. Other illicit substances were captured through a urine drug test. Plasma samples were drawn 1 month into treatment pre-dose, and 1.5, 3, 5 and 8 h post-dose. Non-linear mixed-effects modelling was used to describe the pharmacokinetics of rifampicin, isoniazid, pyrazinamide and ethambutol. Alcohol and drug use were tested as covariates.

RESULTS

The study included 104 participants, of whom 70% were male, with a median age of 37 years (IQR 27-48). Alcohol use was high, with 42% and 28% of participants having moderate and high alcohol use, respectively. Rifampicin and isoniazid had slightly lower pharmacokinetics compared with previous reports, whereas pyrazinamide and ethambutol were consistent. No significant alcohol use effect was detected, other than 13% higher ethambutol clearance in participants with high alcohol use. Methaqualone use reduced rifampicin bioavailability by 19%.

CONCLUSION

No clinically relevant effect of alcohol use was observed on the pharmacokinetics of first-line TB drugs, suggesting that poor treatment outcome is unlikely due to pharmacokinetic alterations. That methaqualone reduced rifampicin means dose adjustment may be beneficial.

Machine Learning Approach in Dosage Individualization of Isoniazid for Tuberculosis

INTRODUCTION

Isoniazid is a first-line antituberculosis agent with high variability, which would profit from individualized dosing. Concentrations of isoniazid at 2 h (C2h), as an indicator of safety and efficacy, are important for optimizing therapy.

OBJECTIVE

The objective of this study was to establish machine learning (ML) models to predict the C2h, that can be used for establishing an individualized dosing regimen in clinical practice.

METHODS

Published population pharmacokinetic (PopPK) models for adults were searched based on PubMed and ultimately four reliable models were selected for simulating individual C2h datasets under different conditions (demographics, genotype, ethnicity, etc.). Machine learning models were trained on simulated C2h obtained from the four PopPK models. Five different algorithms were used for ML model building to predict C2h. Real-world data were used for predictive performance evaluations. Virtual trials were used to compare ML-optimized doses with PopPK model-optimized doses.

RESULTS

Categorical boosting (CatBoost) exhibited the highest prediction ability. Target C2h can be predicted using the ML model combined with the dosing regimen and three covariates (N-acetyltransferase 2 [NAT2] genotypes, weight and race [Asians and Africans]). Real-world data validation results showed that the ML model can achieve an overall prediction accuracy of 93.4%. Using the final ML model, the mean absolute prediction error value decreased by 45.7% relative to the average of PopPK models. Using the ML-optimized dosing regimen, the probability of target attainment increased by 43.7% relative to the PopPK model-optimized dosing regimens.

CONCLUSION

Machine learning models were developed with great predictive performance, which can be used to determine the individualized initial dose of isoniazid in adult patients.

Variability in plasma rifampicin concentrations and role of SLCO1B1, ABCB1, AADAC2 and CES2 genotypes in Ethiopian patients with tuberculosis

BACKGROUND

Rifampicin, a key drug against tuberculosis (TB), displays wide between-patient pharmacokinetics variability and concentration-dependent antimicrobial effect. We investigated variability in plasma rifampicin concentrations and the role of SLCO1B1, ABCB1, arylacetamide deacetylase (AADAC) and carboxylesterase 2 (CES-2) genotypes in Ethiopian patients with TB.

METHODS

We enrolled adult patients with newly diagnosed TB (n = 119) who had received 2 weeks of rifampicin-based anti-TB therapy. Venous blood samples were obtained at three time points post-dose. Genotypes for SLCO1B1 (c.388A > G, c.521T > C), ABCB1 (c.3435C > T, c.4036A > G), AADACc.841G > A and CES-2 (c.269-965A > G) were determined. Rifampicin plasma concentration was quantified using LC-MS/MS. Predictors of rifampicin Cmax and AUC0-7 h were analysed.

RESULTS

The median rifampicin Cmax and AUC0-7 were 6.76 µg/mL (IQR 5.37-8.48) and 17.05 µg·h/mL (IQR 13.87-22.26), respectively. Only 30.3% of patients achieved the therapeutic efficacy threshold (Cmax>8 µg/mL). The allele frequency for SLCO1B1*1B (c.388A > G), SLCO1B1*5 (c.521T > C), ABCB1 c.3435C > T, ABCB1c.4036A > G, AADAC c.841G > A and CES-2 c.269-965A > G were 2.2%, 20.2%, 24.4%, 14.6%, 86.1% and 30.6%, respectively. Sex, rifampicin dose and ABCB1c.4036A > G, genotypes were significant predictors of rifampicin Cmax and AUC0-7. AADACc.841G > A genotypes were significant predictors of rifampicin Cmax. There was no significant influence of SLCO1B1 (c.388A > G, c.521T > C), ABCB1c.3435C > T and CES-2 c.269-965A > G on rifampicin plasma exposure variability.

CONCLUSIONS

Subtherapeutic rifampicin plasma concentrations occurred in two-thirds of Ethiopian TB patients. Rifampicin exposure varied with sex, dose and genotypes. AADACc.841G/G and ABCB1c.4036A/A genotypes and male patients are at higher risk of lower rifampicin plasma exposure. The impact on TB treatment outcomes and whether high-dose rifampicin is required to improve therapeutic efficacy requires further investigation.

Model-Informed Precision Dosing of Isoniazid: Parametric Population Pharmacokinetics Model Repository

Introduction

Isoniazid (INH) is a crucial first-line anti tuberculosis (TB) drug used in adults and children. However, various factors can alter its pharmacokinetics (PK). This article aims to establish a population pharmacokinetic (popPK) models repository of INH to facilitate clinical use.

Methods

A literature search was conducted until August 23, 2022, using PubMed, Embase, and Web of Science databases. We excluded published popPK studies that did not provide full model parameters or used a non-parametric method. Monte Carlo simulation works was based on RxODE. The popPK models repository was established using R. Non-compartment analysis was based on IQnca.

Results

Fourteen studies included in the repository, with eleven studies conducted in adults, three studies in children, one in pregnant women. Two-compartment with allometric scaling models were commonly used as structural models. NAT2 acetylator phenotype significantly affecting the apparent clearance (CL). Moreover, postmenstrual age (PMA) influenced the CL in pediatric patients. Monte Carlo simulation results showed that the geometric mean ratio (95% Confidence Interval, CI) of PK parameters in most studies were within the acceptable range (50.00-200.00%), pregnant patients showed a lower exposure. After a standard treatment strategy, there was a notable exposure reduction in the patients with the NAT2 RA or nonSA (IA/RA) phenotype, resulting in a 59.5% decrease in AUC0-24 and 83.2% decrease in Cmax (Infants), and a 49.3% reduction in AUC0-24 and 73.5% reduction in Cmax (Adults).

Discussion

Body weight and NAT2 acetylator phenotype are the most significant factors affecting the exposure of INH. PMA is a crucial factor in the pediatric population. Clinicians should consider these factors when implementing model-informed precision dosing of INH. The popPK model repository for INH will aid in optimizing treatment and enhancing patient outcomes.

Molecular determinants of multidrug-resistant tuberculosis in Sierra Leone

Multidrug-resistant tuberculosis (MDR-TB) management has become a serious global health challenge. Understanding its epidemic determinants on the regional level is crucial for developing effective control measures. We used whole genome sequencing data of 238 of Mycobacterium tuberculosis complex (MTBC) strains to determine drug resistance profiles, phylogeny, and transmission dynamics of MDR/rifampicin-resistant (RR) MTBC strains from Sierra Leone. Forty-two strains were classified as RR, 196 as MDR, 5 were resistant to bedaquiline (BDQ) and clofazimine (CFZ), but none was found to be resistant to fluoroquinolones. Sixty-one (26%) strains were resistant to all first-line drugs, three of which had additional resistance to BDQ/CFZ. The strains were classified into six major MTBC lineages (L), with strains of L4 being the most prevalent, 62% (n = 147), followed by L6 (Mycobacterium africanum) strains, (21%, n = 50). The overall clustering rate (using ≤d12 single-nucleotide polymorphism threshold) was 44%, stratified into 31 clusters ranging from 2 to 16 strains. The largest cluster (n = 16) was formed by sublineage 2.2.1 Beijing Ancestral 3 strains, which developed MDR several times. Meanwhile, 10 of the L6 strains had a primary MDR transmission. We observed a high diversity of drug resistance mutations, including borderline resistance mutations to isoniazid and rifampicin, and mutations were not detected by commercial assays. In conclusion, one in five strains investigated was resistant to all first-line drugs, three of which had evidence of BDQ/CFZ resistance. Implementation of interventions such as rapid diagnostics that prevent further resistance development and stop MDR-TB transmission chains in the country is urgently needed.

IMPORTANCE

A substantial proportion of MDR-TB strains in Sierra Leone were resistant against all first line drugs; however this makes the all-oral-six-month BPaLM regimen or other 6-9 months all oral regimens still viable, mainly because there was no FQ resistance.Resistance to BDQ was detected, as well as RR, due to mutations outside of the hotspot region. While the prevalence of those resistances was low, it is still cause for concern and needs to be closely monitored.

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.

Parametric population pharmacokinetics of isoniazid: a systematic review

INTRODUCTION

Isoniazid (INH) plays an important role in prevention and treatment of tuberculosis (TB). However, large pharmacokinetic (PK) variations are observed in patients receiving standard INH dosages. Considering the influence of PK variations on INH efficacy or adverse reactions, we reviewed the population PK studies of INH and explored significant covariates that influence INH PK.

METHODS

The PubMed and Embase databases were systematically searched from their inception to 30 January 2023. PPK studies on INH using a parametric nonlinear mixed-effect approach were included in this review. The characteristics and identified significant covariates of the included studies were summarized.

RESULTS

Twenty-one studies conducted in adults, and seven in pediatrics were included. A two-compartment model with first-order absorption and elimination was the frequently used structural model for INH. NAT2 genotype, body size, and age were identified as significant covariates affecting INH PK variation. The median clearance (CL) value in the fast metabolizers was 2.55-fold higher than that in the slow metabolizers. Infants and children had higher CL per weight values than adults with the same metabolic phenotype. In pediatric patients, CL value increased with postnatal age.

CONCLUSIONS

Compared with slow metabolizers, the daily dose of INH should be increased by 200-600 mg in fast metabolizers. To achieve effective treatment, pediatric patients need a higher dose per kilogram than adults. Further PPK studies of anti-tuberculosis drugs are needed to comprehensively understand the covariates that affect their PK characteristics and to achieve accurate dose adjustments.

High Isoniazid Exposures When Administered with Rifapentine Once Weekly for Latent Tuberculosis in Individuals with Human Immunodeficiency Virus

Isoniazid pharmacokinetics are not yet well-described during once weekly, high-dose administrations with rifapentine (3HP) for latent tuberculosis infection (LTBI). Fewer data describe 3HP with dolutegravir-based antiretroviral therapy for the treatment of human immunodeficiency virus (HIV). The only prior report of 3HP with dolutegravir reported elevated isoniazid exposures. We measured the plasma isoniazid levels in 30 adults receiving 3HP and dolutegravir for the treatment of LTBI and HIV. The patients were genotyped to determine NAT2 acetylator status, and a population PK model was estimated by nonlinear mixed-effects modeling. The results were compared to previously reported data describing 3HP with dolutegravir, 3HP alone, and isoniazid with neither dolutegravir nor rifapentine. The isoniazid concentrations were adequately described by a one compartment model with a transit compartment absorption process. The isoniazid clearance for slow (8.33 L/h) and intermediate (12 L/h) acetylators were similar to previously reported values. Rapid acetylators (N = 4) had clearance similar to those of intermediate acetylators and much slower than typically reported, but the small sample size was limiting. The absorption rate was lower than usual, likely due to the coadministration with food, and it was faster among individuals with a low body weight. Low-body weight participants were also observed to have greater oral bioavailability. The isoniazid exposures were consistent with, or greater than, the previously reported "elevated" concentrations among individuals receiving 3HP and dolutegravir. The concentrations were substantially greater than those presented in previous reports among individuals receiving 3HP or isoniazid without rifapentine or dolutegravir. We discuss the implications of these findings and the possibility of a drug-drug interaction that is mediated by cellular transport. (This study has been registered at ClinicalTrials.gov under identifier NCT03435146 and has South African National Clinical Trial Registration no. DOH-27-1217-5770.).

The Changing Paradigm of Drug-Resistant Tuberculosis Treatment: Successes, Pitfalls, and Future Perspectives

Drug-resistant tuberculosis (DR-TB) remains a global crisis due to the increasing incidence of drug-resistant forms of the disease, gaps in detection and prevention, models of care, and limited treatment options. The DR-TB treatment landscape has evolved over the last 10 years. Recent developments include the remarkable activity demonstrated by the newly approved anti-TB drugs bedaquiline and pretomanid against Mycobacterium tuberculosis. Hence, treatment of DR-TB has drastically evolved with the introduction of the short-course regimen for multidrug-resistant TB (MDR-TB), transitioning to injection-free regimens and the approval of the 6-month short regimens for rifampin-resistant TB and MDR-TB. Moreover, numerous clinical trials are under way with the aim to reduce pill burden and shorten the DR-TB treatment duration. While there have been apparent successes in the field, some challenges remain. These include the ongoing inclusion of high-dose isoniazid in DR-TB regimens despite a lack of evidence for its efficacy and the inclusion of ethambutol and pyrazinamide in the standard short regimen despite known high levels of background resistance to both drugs. Furthermore, antimicrobial heteroresistance, extensive cavitary disease and intracavitary gradients, the emergence of bedaquiline resistance, and the lack of biomarkers to monitor DR-TB treatment response remain serious challenges to the sustained successes. In this review, we outline the impact of the new drugs and regimens on patient treatment outcomes, explore evidence underpinning current practices on regimen selection and duration, reflect on the disappointments and pitfalls in the field, and highlight key areas that require continued efforts toward improving treatment approaches and rapid biomarkers for monitoring treatment response.

Safety of Rifampicin at High Dose for Difficult-to-Treat Tuberculosis: Protocol for RIAlta Phase 2b/c Trial

Previous clinical trials for drug-susceptible tuberculosis (DS-TB) have shown that first-line treatment with doses of rifampicin up to 40 mg/kg are safe and increase the early treatment response for young adults with pulmonary tuberculosis. This may lead to a shorter treatment duration for those persons with TB and a good baseline prognosis, or increased treatment success for vulnerable subgroups (age > 60, diabetes, malnutrition, HIV, hepatitis B or hepatitis C coinfection, TB meningitis, stable chronic liver diseases). Here, we describe the design of a phase 2b/c clinical study under the hypothesis that rifampicin at 35 mg/kg is as safe for these vulnerable groups as for the participants included in previous clinical trials. RIAlta is an interventional, open-label, multicenter, prospective clinical study with matched historical controls comparing the standard DS-TB treatment (isoniazid, pyrazinamide, and ethambutol) with rifampicin at 35 mg/kg (HR35ZE group) vs. rifampicin at 10 mg/kg (historical HR10ZE group). The primary outcome is the incidence of grade ≥ 3 Adverse Events or Severe Adverse Events. A total of 134 participants will be prospectively included, and compared with historical matched controls with at least a 1:1 proportion. This will provide a power of 80% to detect non-inferiority with a margin of 8%. This study will provide important information for subgroups of patients that are more vulnerable to TB bad outcomes and/or treatment toxicity. Despite limitations such as non-randomized design and the use of historical controls, the results of this trial may inform the design of future more inclusive clinical trials, and improve the management of tuberculosis in subgroups of patients for whom scientific evidence is still scarce. Trial registration: EudraCT 2020-003146-36, NCT04768231.

Pharmacogenetic variability and the probability of site of action target attainment during tuberculosis meningitis treatment: A physiologically based pharmacokinetic modeling and simulations study

OBJECTIVE AND METHODS

Our objective was to investigate the role of patient pharmacogenetic variability in determining site of action target attainment during tuberculous meningitis (TBM) treatment. Rifampin and isoniazid PBPK model that included SLCO1B1 and NAT2 effects on exposures respectively were obtained from literature, modified, and validated using available cerebrospinal-fluid (CSF) concentrations. Population simulations of isoniazid and rifampin concentrations in brain interstitial fluid and probability of target attainment according to genotypes and M. tuberculosis MIC levels, under standard and intensified dosing, were conducted.

RESULTS

The rifampin and isoniazid model predicted steady-state drug concentration within brain interstitial fluid matched with the observed CSF concentrations. At MIC level of 0.25 mg/L, 57% and 23% of the patients with wild type and heterozygous SLCO1B1 genotype respectively attained the target in CNS with rifampin standard dosing, improving to 98% and 91% respectively with 35 mg/kg dosing. At MIC level of 0.25 mg/L, 33% of fast acetylators attained the target in CNS with isoniazid standard dosing, improving to 90% with 7.5 mg/kg dosing.

CONCLUSION

In this study, the combined effects of pharmacogenetic and M. tuberculosis MIC variability were potent determinants of target attainment in CNS. The potential for genotype-guided dosing during TBM treatment should be further explored in prospective clinical studies.

Whole-Genome Sequencing for Resistance Prediction and Transmission Analysis of Mycobacterium tuberculosis Complex Strains from Namibia

Namibia is among 30 countries with a high burden of tuberculosis (TB), with an estimated incidence of 460 per 100,000 population and around 800 new multidrug-resistant (MDR) TB cases per year. Still, data on the transmission and evolution of drug-resistant Mycobacterium tuberculosis complex (Mtbc) strains are not available. Whole-genome sequencing data of 136 rifampicin-resistant (RIFr) Mtbc strains obtained from 2016 to 2018 were used for phylogenetic classification, resistance prediction, and cluster analysis and linked with phenotypic drug susceptibility testing (pDST) data. Roughly 50% of the strains investigated were resistant to all first-line drugs. Furthermore, 13% of the MDR Mtbc strains were already pre-extensively drug resistant (pre-XDR). The cluster rates were high, at 74.6% among MDR and 85% among pre-XDR strains. A significant proportion of strains had borderline resistance-conferring mutations, e.g., inhA promoter mutations or rpoB L430P. Accordingly, 25% of the RIFr strains tested susceptible by pDST. Finally, we determined a potentially new bedaquiline resistance mutation (Rv0678 D88G) occurring in two independent clusters. High rates of resistance to first-line drugs in line with emerging pre-XDR and likely bedaquiline resistance linked with the ongoing recent transmission of MDR Mtbc clones underline the urgent need for the implementation of interventions that allow rapid diagnostics to break MDR TB transmission chains in the country. A borderline RIFr mutation in the dominant outbreak strain causing discrepancies between phenotypic and genotypic resistance testing results may require breakpoint adjustments but also may allow individualized regimens with high-dose treatment. IMPORTANCE The transmission of drug-resistant tuberculosis (TB) is a major problem for global TB control. Using genome sequencing, we showed that 13% of the multidrug-resistant (MDR) M. tuberculosis complex strains from Namibia are already pre-extensively drug resistant (pre-XDR), which is substantial in an African setting. Our data also indicate that the ongoing transmission of MDR and pre-XDR strains contributes significantly to the problem. In contrast to other settings with higher rates of drug resistance, we found a high proportion of strains having so-called borderline low-level resistance mutations, e.g., inhA promoter mutations or rpoB L430P. This led to the misclassification of 25% of the rifampicin-resistant strains as susceptible by phenotypic drug susceptibility testing. This observation potentially allows individualized regimens with high-dose treatment as a potential option for patients with few treatment options. We also found a potentially new bedaquiline resistance mutation in rv0678.

The second national anti-tuberculosis drug resistance survey in Tanzania, 2017-2018

OBJECTIVE

To determine the levels and patterns of resistance to first- and second-line anti-tuberculosis (TB) drugs among new and previously treated sputum smear positive pulmonary TB (PTB) patients.

METHODS

We conducted a nationally representative cross-sectional facility-based survey in June 2017-July 2018 involving 45 clusters selected based on probability proportional to size. The survey aimed to determine the prevalence of anti-TB drug resistance and associated risk factors among smear positive PTB patients in Tanzania. Sputum samples were examined using smear microscopy, Xpert MTB/RIF, culture and drug susceptibility testing (DST). Logistic regression was used to account for missing data and sampling design effects on the estimates and their standard errors.

RESULTS

We enrolled 1557 TB patients, including 1408 (90.4%) newly diagnosed and 149 (9.6%) previously treated patients. The prevalence of multidrug-resistant TB (MDR-TB) was 0.85% [95% confidence interval (CI): 0.4-1.3] among new cases and 4.6% (95% CI: 1.1-8.2) among previously treated cases. The prevalence of Mycobacterium tuberculosis strains resistant to any of the four first-line anti-TB drugs (isoniazid, rifampicin, streptomycin and ethambutol) was 1.7% among new TB patients and 6.5% among those previously treated. Drug resistance to all first-line drugs was similar (0.1%) in new and previously treated patients. None of the isolates displayed poly-resistance or extensively drug-resistant TB (XDR-TB). The only risk factor for MDR-TB was history of previous TB treatment (odds ratio = 5.7, 95% CI: 1.9-17.2).

CONCLUSION

The burden of MDR-TB in the country was relatively low with no evidence of XDR-TB. Given the overall small number of MDR-TB cases in this survey, it will be beneficial focusing efforts on intensified case detection including universal DST.

Pharmacogenetic testing for NAT2 genotypes in a Tanzanian population across the lifespan to guide future personalized isoniazid dosing

Despite updated recommendations for weight-based isoniazid dosing in children with drug-susceptible tuberculosis (TB) and higher dose isoniazid in regimens for adults with drug-resistant TB, individual pharmacokinetic variability can lead to sub-target isoniazid exposure. Host pharmacogenetics and isoniazid exposure remain understudied, especially in the East African population. We therefore employed a real-time polymerase chain reaction (qPCR) assay system to test genomic DNA extracted from saliva samples targeting the NAT2 gene responsible for isoniazid metabolism to describe the frequency of human single nucleotide polymorphisms in NAT2 within populations of children and adults in Tanzania, ascribe those polymorphisms to acetylator phenotype, and correlate to serum isoniazid exposures. In adults treated with higher dose isoniazid, genotypes with a predicted allelic phenotype of slow or intermediate acetylation were able to achieve a 0.41 μg/mL higher C_max (p = 0.018) and a 2.9h*μg/mL higher AUC_0-12 (p = 0.003) per mg/kg increase in isoniazid dosage versus adults with rapid acetylation phenotype. A similar relationship was not found in the younger age population as predicted by timing of NAT2 maturation. This saliva based qPCR assay was fieldable to guide personalized isoniazid dosing in adults but not young children that may not have full NAT2 maturation and activity.

SLCO1B1 and SLC10A1 polymorphism and plasma rifampin concentrations in patients with co-morbidity tuberculosis-diabetes mellitus in Baja California, Mexico

Rifampicin is one of the most important drugs for the treatment of tuberculosis (TB). Polymorphisms in SLCO1B1 and SLC10A1 genes are associated with impaired transporter function of drug compounds such as rifampicin. The relationship between genetic variation, clinical comorbidities, and rifampicin exposures in TB patients has not been completely elucidated. The aim of this study was to investigate the prevalence of SLCO1A1 and SLCO1B1 polymorphisms in TB and TB-DM patients and to determine their relationship with rifampicin pharmacokinetics on patients from México. Blood samples were collected in two hospitals in Baja California, Mexico from February through December 2017. Sampling included 19 patients with TB, 11 with T2DM and 17 healthy individuals. Polymorphisms genotype rs2306283, rs11045818, rs11045819, rs4149056, rs4149057, rs72559746,rs2291075 and rs4603354 of SLCO1B1 and rs4646285 and rs138880008 of SLC10A1 were analyzed by Sanger's sequencing. None of the SLCO1B1 and SLC10A1 variants were significantly associated with rifampicin C_max. TB and T2DM patients with suboptimal C_max rifampicin levels showed wild alleles in rs11045819 and rs2291075 in SLCO1B1 SLC10A1 and SLC10A1. This is the first study to analyze SLC10A1 and SLCO1B1 polymorphisms in TB and TB-T2DM patients and healthy individuals in Mexico. Further research to confirm and extend these findings is necessary.

Influence of N-acetyltransferase 2 (NAT2) genotype/single nucleotide polymorphisms on clearance of isoniazid in tuberculosis patients: a systematic review of population pharmacokinetic models

Purpose

Significant pharmacokinetic variabilities have been reported for isoniazid across various populations. We aimed to summarize population pharmacokinetic studies of isoniazid in tuberculosis (TB) patients with a specific focus on the influence of N-acetyltransferase 2 (NAT2) genotype/single-nucleotide polymorphism (SNP) on clearance of isoniazid.

Methods

A systematic search was conducted in PubMed and Embase for articles published in the English language from inception till February 2022 to identify population pharmacokinetic (PopPK) studies of isoniazid. Studies were included if patient population had TB and received isoniazid therapy, non-linear mixed effects modelling, and parametric approach was used for building isoniazid PopPK model and NAT2 genotype/SNP was tested as a covariate for model development.

Results

A total of 12 articles were identified from PubMed, Embase, and hand searching of articles. Isoniazid disposition was described using a two-compartment model with first-order absorption and linear elimination in most of the studies. Significant covariates influencing the pharmacokinetics of isoniazid were NAT2 genotype, body weight, lean body weight, body mass index, fat-free mass, efavirenz, formulation, CD4 cell count, and gender. Majority of studies conducted in adult TB population have reported a twofold or threefold increase in isoniazid clearance for NAT2 rapid acetylators compared to slow acetylators.

Conclusion

The variability in disposition of isoniazid can be majorly attributed to NAT2 genotype. This results in a trimodal clearance pattern with a multi-fold increase in clearance of NAT2 rapid acetylators compared to slow acetylators. Further studies exploring the generalizability/adaptability of developed PopPK models in different clinical settings are required.

Effect of Genetic Variations in Drug-Metabolizing Enzymes and Drug Transporters on the Pharmacokinetics of Rifamycins: A Systematic Review

Background

Rifamycins are a novel class of antibiotics clinically approved for tuberculosis chemotherapy. They are characterized by high inter-individual variation in pharmacokinetics. This systematic review aims to present the contribution of genetic variations in drug-metabolizing enzymes and transporter proteins to the inter-individual variation of rifamycin pharmacokinetics.

Method

We followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines. The search for relevant studies was done through PubMed, Embase, Web of Science, and Scopus databases. Studies reporting single nucleotide polymorphism in drug transporters and metabolizing enzymes' influence on rifamycin pharmacokinetics were solely included. Two reviewers independently performed data extraction.

Results

The search identified 117 articles of which 15 fulfilled the eligibility criteria and were included in the final data synthesis. The single nucleotides polymorphism in the drug transporters SLCO1B1 rs4149032, rs2306283, rs11045819, and ABCB1 rs1045642 for rifampicin, drug metabolizing enzyme AADAC rs1803155 for rifapentine and CES2 c.-22263A>G (g.738A>G) for rifampicin partly contributes to the variability of pharmacokinetic parameters in tuberculosis patients.

Conclusion

The pharmacokinetics of rifamycins is influenced by genetic variation of drug-metabolizing enzymes and transporters. Controlled clinical studies are, however, required to establish these relationships.

Real-life isoniazid and rifampicin plasma concentrations in children: a tool for therapeutic drug monitoring of tuberculosis

Background

Low plasma levels of first-line antitubercular drugs can be counted among the main causes of poor response to antitubercular therapy, and therapeutic drug monitoring has been proposed as a method to promote tailored treatments for both child and adult patients. The main aim of the study was to evaluate serum concentrations of isoniazid (INH) and rifampicin (RIF) and to investigate reasons for sub-therapeutic plasma concentrations in order to fix dosages.

Methods

Children with TB were prospectively enrolled from January to August 2019. Two venous blood samples were collected (the first at least 15 days after the beginning of antitubercular treatment, and the second between 1 and 8 weeks later). Plasma concentrations were determined by a validated high-performance liquid chromatography method.

Results

In all, 45 children were included. Seventy blood samples for INH plasma concentration were collected between 120 and 240 min after drug intake. Adjusting for dose (mg/kg/day) and time of INH administration, when considering three different age groups (≤ 2 years, 2–12 years, > 12 years), a statistically significant lower INH plasma concentration was observed in younger children compared to the older age groups in the multivariate analysis (p < 0.001 and p < 0.001). A total of 68 blood samples were evaluated for RIF concentrations. Both for INH and RIF a statistically significant lower plasma concentration was also observed in adolescents (p < 0.001). Fifteen children (15/45, 33%) presented drug concentrations under the referral therapeutic range.

Conclusions

Based on our findings, monitoring patients’ drug plasma concentrations in children under 2 years of age and in adolescents can make treatment more patient-tailored.

A Rapid Pharmacogenomic Assay to Detect NAT2 Polymorphisms and Guide Isoniazid Dosing for Tuberculosis Treatment

RATIONALE

Standardized dosing of anti-tubercular drugs contributes to a substantial incidence of toxicities, inadequate treatment response, and relapse, in part due to variable drug levels achieved. Single nucleotide polymorphisms (SNPs) in the N-acetyltransferase-2 (NAT2) gene explain the majority of interindividual pharmacokinetic variability of isoniazid (INH). However, an obstacle to implementing pharmacogenomic-guided dosing is the lack of a point-of-care assay.

OBJECTIVES

To develop and test a NAT2 classification algorithm, validate its performance in predicting isoniazid clearance, and develop a prototype pharmacogenomic assay.

METHODS

We trained random forest models to predict NAT2 acetylation genotype from unphased SNP data using a global collection of 8,561 phased genomes. We enrolled 48 pulmonary TB patients, performed sparse pharmacokinetic sampling, and tested the acetylator prediction algorithm accuracy against estimated INH clearance. We then developed a cartridge-based multiplex qPCR assay on the GeneXpert platform and assessed its analytical sensitivity on whole blood samples from healthy individuals.

MEASUREMENTS AND MAIN RESULTS

With a 5-SNP model trained on two-thirds of the data (n=5,738), out-of-sample acetylation genotype prediction accuracy on the remaining third (n=2,823) was 100%. Among the 48 TB patients, predicted acetylator types were: 27 (56.2%) slow, 16 (33.3%) intermediate and 5 (10.4%) rapid. INH clearance rates were lowest in predicted slow acetylators (median 14.5 L/hr), moderate in intermediate acetylators (median 40.3 L/hr) and highest in fast acetylators (median 53.0 L/hr). The cartridge-based assay accurately detected all allele patterns directly from 25 ul of whole blood.

CONCLUSIONS

An automated pharmacogenomic assay on a platform widely used globally for tuberculosis diagnosis could enable personalized dosing of isoniazid.

Development of a population pharmacokinetic model and Bayesian estimators for isoniazid in Tunisian tuberculosis patients

This study aimed to develop a population pharmacokinetic model using full pharmacokinetic (PK) profiles of isoniazid (INH) taking into account demographic and genetic covariates and to develop Bayesian estimators for predicting INH area under the curve (AUC) in Tunisian tuberculosis patients. The INH concentrations in the building data set were fitted using a one- to three-compartment model. The impact of the different covariates was assessed on the PK parameters of the best model. The best limited sampling strategy (LSS) for estimating the INH AUC was selected by comparing the predicted values to an independent data set. INH PK was best described using a three-compartment model with lag-time absorption. The different studied covariates did not have any impact on the PK parameters of the building model. The Bayesian estimation using one-point concentrations gave the lowest values of prediction errors for the C₃ LSS model. This model could be sufficient in routine activity for INH monitoring in this population.

Chronological Metabolic Response to Intensive Phase TB Therapy in Patients with Cured and Failed Treatment Outcomes

Despite the arguable success of the standardized tuberculosis (TB) treatment regime, a significant number of patients still present with treatment failure. To improve on current TB treatment strategies, we sought to gain a better understanding of the hosts' response to TB therapy. A targeted metabolomics approach was used to compare the urinary acylcarnitine and amino acid profiles of eventually cured TB patients with those of patients presenting with a failed treatment outcome, comparing these patient groups at the time of diagnosis and at weeks 1, 2, and 4 of treatment. Among the significant metabolites identified were histidine, isoleucine, leucine, methionine, valine, proline, tyrosine, alanine, serine, and γ-aminobutyric acid. In general, metabolite fluctuations in time followed a similar pattern for both groups for most compounds but with a delayed onset or shift of the pattern in the successfully treated patient group. These time-trends detected in both groups could potentially be ascribed to a vitamin B6 deficiency and fluctuations in the oxidative stress levels and urea cycle intermediates, linked to the drug-induced inhibition and stimulation of various enzymes. The earlier onset of observed trends in the failed patients is proposed to relate to genotypic and phenotypic variations in drug metabolizing enzymes, subsequently leading to a poor treatment efficiency either due to the rise of adverse drug reactions or to insufficient concentrations of the active drug metabolites. This study emphasizes the need for a more personalized TB treatment approach, by including enzyme phenotyping and the monitoring of oxidative stress and vitamin B6 levels, for example.

Functional Characterization of the Effects of N-acetyltransferase 2 Alleles on N-acetylation of Eight Drugs and Worldwide Distribution of Substrate-Specific Diversity

Variability in the enzymatic activity of N-acetyltransferase 2 (NAT2) is an important contributor to interindividual differences in drug responses. However, there is little information on functional differences in N-acetylation activities according to NAT2 phenotypes, i.e., rapid, intermediate, slow, and ultra-slow acetylators, between different substrate drugs. Here, we estimated NAT2 genotypes in 990 Japanese individuals and compared the frequencies of different genotypes with those of different populations. We then calculated in vitro kinetic parameters of four NAT2 alleles (NAT2^∗4, ^∗5, ^∗6, and ^∗7) for N-acetylation of aminoglutethimide, diaminodiphenyl sulfone, hydralazine, isoniazid, phenelzine, procaineamide, sulfamethazine (SMZ), and sulfapyrizine. NAT2^∗5, ^∗6, and ^∗7 exhibited significantly reduced N-acetylation activities with lower Vmax and CLint values of all drugs when compared with NAT2^∗4. Hierarchical clustering analysis revealed that 10 NAT2 genotypes were categorized into three or four clusters. According to the results of in vitro metabolic experiments using SMZ as a substrate, the frequencies of ultra-slow acetylators were calculated to be 29.05–54.27% in Europeans, Africans, and South East Asians, whereas Japanese and East Asian populations showed lower frequencies (4.75 and 11.11%, respectively). Our findings will be helpful for prediction of responses to drugs primarily metabolized by NAT2.

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.

Relationship among genetic polymorphism of SLCO1B1, rifampicin exposure and clinical outcomes in patients with active pulmonary tuberculosis

AIMS

Rifampicin is a key drug for the treatment of tuberculosis (TB). Little is known for the relationship between the rifampicin pharmacokinetics and genetic polymorphisms in the Asian population. We aimed to investigate relationship between genetic polymorphism of SLCO1B1 and rifampicin exposure and its impact on clinical outcomes in Korean patients with active pulmonary TB.

METHODS

From February 2016 to December 2019, patients with active pulmonary TB who were taking rifampicin for >1 week were prospectively enrolled. Serial or 1-time blood sampling was conducted to determine rifampicin concentrations. The genotype of 4 single nucleotide polymorphisms of SLCO1B1 was determined. To estimate the drug clearance and exposure, population pharmacokinetics analysis was conducted. Clinical outcomes such as time to acid-fast bacteria culture conversion, chest radiograph score changes from baseline, and all-cause mortality were also evaluated. The exposure among different SLCO1B1 genotype was compared and relationship between drug exposure and clinical outcomes were explored.

RESULTS

A total of 105 patients (70 males and 35 females) were included in the final analysis. The mean age of patients was 55.4 years. The mean drug clearance and exposure were 13.6 L/h and 57.9 mg h/L, respectively. The genetic polymorphisms of SLCO1B1 were not related to rifampicin clearance or exposure. As the rifampicin exposure increased, the chest radiographs improved significantly, but the duration of acid-fast bacteria culture conversion was not related to the drug exposure.

CONCLUSION

SLCO1B1 gene polymorphisms did not influence rifampicin concentrations and clinical outcomes in Korean patients with active pulmonary TB.

Prior information for population pharmacokinetic and pharmacokinetic/pharmacodynamic analysis: overview and guidance with a focus on the NONMEM PRIOR subroutine

Abstract

Population pharmacokinetic analysis is used to estimate pharmacokinetic parameters and their variability from concentration data. Due to data sparseness issues, available datasets often do not allow the estimation of all parameters of the suitable model. The PRIOR subroutine in NONMEM supports the estimation of some or all parameters with values from previous models, as an alternative to fixing them or adding data to the dataset. From a literature review, the best practices were compiled to provide a practical guidance for the use of the PRIOR subroutine in NONMEM. Thirty-three articles reported the use of the PRIOR subroutine in NONMEM, mostly in special populations. This approach allowed fast, stable and satisfying modelling. The guidance provides general advice on how to select the most appropriate reference model when there are several previous models available, and to implement and weight the selected parameter values in the PRIOR function. On the model built with PRIOR, the similarity of estimates with the ones of the reference model and the sensitivity of the model to the PRIOR values should be checked. Covariates could be implemented a priori (from the reference model) or a posteriori, only on parameters estimated without prior (search for new covariates).

Graphic abstract

Electronic supplementary material

The online version of this article (10.1007/s10928-020-09695-z) contains supplementary material, which is available to authorized users.

Influence of Single Nucleotide Polymorphisms on Rifampin Pharmacokinetics in Tuberculosis Patients

Rifampin (RF) is metabolized in the liver into an active metabolite 25-desacetylrifampin and excreted almost equally via biliary and renal routes. Various influx and efflux transporters influence RF disposition during hepatic uptake and biliary excretion. Evidence has also shown that Vitamin D deficiency (VDD) and Vitamin D receptor (VDR) polymorphisms are associated with tuberculosis (TB). Hence, genetic polymorphisms of metabolizing enzymes, drug transporters and/or their transcriptional regulators and VDR and its pathway regulators may affect the pharmacokinetics of RF. In this narrative review, we aim to identify literature that has explored the influence of single nucleotide polymorphisms (SNPs) of genes encoding drug transporters and their transcriptional regulators (SLCO1B1, ABCB1, PXR and CAR), metabolizing enzymes (CES1, CES2 and AADAC) and VDR and its pathway regulators (VDR, CYP27B1 and CYP24A1) on plasma RF concentrations in TB patients on antitubercular therapy. Available reports to date have shown that there is a lack of any association of ABCB1, PXR, CAR, CES1 and AADAC genetic variants with plasma concentrations of RF. Further evidence is required from a more comprehensive exploration of the association of SLCO1B1, CES2 and Vitamin D pathway gene variants with RF pharmacokinetics in distinct ethnic groups and a larger population to reach conclusive information.

The role of NAT2 polymorphism and methylation in anti-tuberculosis drug-induced liver injury in Mongolian tuberculosis patients

WHAT IS KNOWN AND OBJECTIVE

Anti-tuberculosis drug-induced liver injury (ATLI) is one of the most significant adverse reactions for this line of therapy. N-acetyltransferase 2 (NAT2) is an important metabolic enzyme involved in drug metabolism and detoxification. Genetic polymorphism and DNA methylation have been proven to be key factors that affect the expression of NAT2. Therefore, the objective of the study was to investigate the relationship between NAT2 gene polymorphism and DNA methylation in the promoter region with ATLI risk in Mongolian tuberculosis patients.

METHODS

Our study is a case-control design. Chi-square test, Mann-Whitney U non-parametric test and Pearson test were all used to analyse existing relationships. The association between NAT2 gene acetylation phenotype and the total methylation of the NAT2 promoter region was analysed by means of binary logistic regression analysis. The general situation of the patients was evaluated by questionnaire, and the NAT2 genotyping of the three major polymorphism loci of gene coding was carried out by a gene sequencing technique. The methylation status of the NAT2 gene promoter region was detected by bisulphite sequencing and mass spectrometry.

RESULT AND DISCUSSION

Our study found that the detection rate of ATLI in Mongolian tuberculosis patients was 27.6%. There were no significant differences in demographic characteristics and living habits amongst the two groups, while significant differences were observed in the polymorphism of the NAT2 genes 481 (rs1799929) and 590 (rs1799930) and the acetylation phenotype. Moreover, the composition and distribution of the NAT2*4/4 and NAT2*4/5 genotypes were found in the two groups. The risk of ATLI in the slow acetylation type was 3.56 times higher than that of the fast acetylation type. Compared with the control group, the CpG5, CpG10, CpG11.12 and total methylation of the NAT2 promoter region in the ATLI group showed a hypermethylated pattern (P < .05). However, on performing binary logistic regression, neither the slow acetylation, intermediate acetylation nor rapid acetylation were found to be associated with ATLI (P > .05). It was found that the total methylation of NAT2 gene promoter region was an independent influencing factor of ATLI in Mongolian tuberculosis patients. With the increase of the total methylation level of NAT2 gene promoter region, the risk of ATLI increased gradually. (OR = 8.371, 95% CI: 2.391 ~ 29.315). CpG1, CpG4, CpG9, CpG10 and CpG11.12 were positively correlated with a total methylation level in the ATLI group.

WHAT IS NEW AND CONCLUSION

The detection rate of ATLI in Mongolian tuberculosis patients was 27.6%, and there were differences in the NAT2 genotypes and acetylated phenotypes. The slow acetylated type was the risk factor for ATLI. Methylation in the promoter region of the NAT2 gene has an effect on the risk of ATLI. After adjusting for the interference of three acetylation types, it was found that the total methylation of the promoter region of NAT2 gene in Mongolian tuberculosis patients is an independent influencing factor of ATLI. Furthermore, there is a moderate to high correlation between some sites and the overall level of methylation.

N-Acetyltransferase 2 Genotypes among Zulu-Speaking South Africans and Isoniazid and N-Acetyl-Isoniazid Pharmacokinetics during Antituberculosis Treatment

The distribution of N-acetyltransferase 2 gene (NAT2) polymorphisms varies considerably among different ethnic groups. Information on NAT2 single-nucleotide polymorphisms in the South African population is limited. We investigated NAT2 polymorphisms and their effect on isoniazid pharmacokinetics (PK) in Zulu black HIV-infected South Africans in Durban, South Africa. HIV-infected participants with culture-confirmed pulmonary tuberculosis (TB) were enrolled from two unrelated studies. Participants with culture-confirmed pulmonary TB were genotyped for the NAT2 polymorphisms 282C>T, 341T>C, 481C>T, 857G>A, 590G>A, and 803A>G using Life Technologies prevalidated TaqMan assays (Life Technologies, Paisley, UK). Participants underwent sampling for determination of plasma isoniazid and N-acetyl-isoniazid concentrations. Among the 120 patients, 63/120 (52.5%) were slow metabolizers (NAT2*5/*5), 43/120 (35.8%) had an intermediate metabolism genotype (NAT2*5/12), and 12/120 (11.7%) had a rapid metabolism genotype (NAT2*4/*11, NAT2*11/12, and NAT2*12/12). The NAT2 alleles evaluated in this study were *4, *5C, *5D, *5E, *5J, *5K, *5KA, *5T, *11A, *12A/12C, and *12M. NAT2*5 was the most frequent allele (70.4%), followed by NAT2*12 (27.9%). Fifty-eight of 60 participants in study 1 had PK results. The median area under the concentration-time curve from 0 to infinity (AUC_0-∞) was 5.53 (interquartile range [IQR], 3.63 to 9.12 μg h/ml), and the maximum concentration (C _max) was 1.47 μg/ml (IQR, 1.14 to 1.89 μg/ml). Thirty-four of 40 participants in study 2 had both PK results and NAT2 genotyping results. The median AUC_0-∞ was 10.76 μg·h/ml (IQR, 8.24 to 28.96 μg·h/ml), and the C _max was 3.14 μg/ml (IQR, 2.39 to 4.34 μg/ml). Individual polymorphisms were not equally distributed, with some being represented in small numbers. The genotype did not correlate with the phenotype, with those with a rapid acetylator genotype showing higher AUC_0-∞ values than those with a slow acetylator genotype, but the difference was not significant (P = 0.43). There was a high prevalence of slow acetylator genotypes, followed by intermediate and then rapid acetylator genotypes. The poor concordance between genotype and phenotype suggests that other factors or genetic loci influence isoniazid metabolism, and these warrant further investigation in this population.

Role of pharmacogenetics in rifampicin pharmacokinetics and the potential effect on TB–rifampicin sensitivity among Ugandan patients

Background

Suboptimal anti-TB drugs exposure may cause multidrug-resistant TB. The role of African predominant SLCO1B1 variant alleles on rifampicin pharmacokinetics and the subsequent effect on the occurrence of Mycobacterium tuberculosis–rifampicin sensitivity needs to be defined. We describe the rifampicin population pharmacokinetics profile and investigate the relevance of SLCO1B1 genotypes to rifampicin pharmacokinetics and rifampicin-TB sensitivity status.

Methods

Fifty patients with TB (n=25 with rifampicin-resistant TB and n=25 with rifampicin-susceptible TB) were genotyped for SLOC1B1 rs4149032 (g.38664C&gt;T), SLOC1B1*1B (c.388A&gt;G) and SLOC1B1*5 (c.521 T&gt;C). Steady state plasma rifampicin levels were determined among patients infected with rifampicin-sensitive TB. Data were analysed using NONMEM to estimate population rifampicin pharmacokinetics as well as the effect of SLOC1B1 genotypes on rifampicin pharmacokinetics and on rifampicin-TB sensitivity status.

Results

Overall allele frequencies of SLOC1B1 rs4149032, *1B and *5 were 0.66, 0.90 and 0.01, respectively. Median (IQR) Cmax and Tmax were 10.2 (8.1–12.5) mg/L and 1.7 (1.125–2.218) h, respectively. Twenty-four percent of patients exhibited Cmax below the recommended 8–24 mg/L range. SLOC1B1 genotypes, gender and age did not influence rifampicin pharmacokinetics or TB-rifampicin sensitivity.

Conclusions

Although SLOC1B1 genotype, age and gender do not influence either rifampicin pharmacokinetics or rifampicin-TB sensitivity status, one in every four Ugandan TB patients achieve subtherapeutic plasma rifampicin concentrations.