Rentia Lourens 1, Carene Anne Alene Ndong Sima 2, Marlo Möller 2,3,4,5, Caitlin Uren 2,3,4,5, Geriant Davies 6, Paolo Denti 1, James Millard 6,7,8
1 Division of Clinical Pharmacology, Department of Medicine, University of Cape (Cape Town, South Africa), 2 South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University (Cape Town, South Africa), 3 Centre for Bioinformatics and Computational Biology (Cape Town, South Africa), 4 Genomics for Health in Africa, Africa-Europe Cluster of Research Excellence (, South Africa), 5 National Institute for Theoretical and Computational Sciences (, South Africa), 6 Department of Clinical Infection, Microbiology and Immunology, University of Liverpool (Liverpool, United Kingdom), 7 Imperial NHS Foundation Trust (London, United Kingdom), 8 Africa Health Research Institute (Durban, South Africa)
Objectives:
Ethambutol is a first-line antitubercular drug included in World Health Organization recommended regimen for tuberculosis (TB) and is also used to treat rifampicin-resistant or multidrug-resistant tuberculosis (RR/MDR-TB) [1,2]. The drug is minimally metabolized and primarily eliminated unchanged via the kidneys [3,4]. Despite widespread use, ethambutol population pharmacokinetic (popPK) data in RR/MDR-TB populations are limited. This study aimed to characterise ethambutol popPK in adults with pulmonary RR/MDR-TB and explore genetic variants associated with exposure variability.
Methods:
Adults with pulmonary RR/MDR-TB were recruited from Don McKenzie TB Hospital, KwaZulu-Natal, South Africa from 2017 to 2019. Participants received 800, 1200, or 1600 mg oral ethambutol dihydrochloride as per national guidelines based on body weight at the time of the study [5]. Pharmacokinetic sampling was conducted approximately four weeks after treatment initiation and plasma samples were collected pre-dose and at 1, 2, 4, 6, and 8 hours post-dose. Plasma concentrations were measured using a validated high performance liquid chromatography tandem mass spectrometry method with a lower limit of quantification of 0.025 mg/L.
Renal function was described using creatinine clearance estimated by the Cockcroft–Gault equation. Population pharmacokinetic modelling was performed in NONMEM v7.5.1, with first-order conditional estimation with eta-epsilon interaction (FOCE-I). Perl-speaks-NONMEM and Xpose were used for diagnostics. Doses were adjusted by a factor of 0.74 in accordance with the salt factor for ethambutol dihydrochloride. One- and two-compartment disposition models with first-order absorption with other absorption models including lag-time and transit compartments were evaluated. Between-subject variability and -occasion variability were included on clearance and absorption parameters, respectfully, and residual unexplained variability was implemented using a combined additive and proportional error model.
Allometric scaling of clearance and volume parameters was tested using total body weight and fat-free mass (FFM) [6]. Renal function was tested on clearance [7]. Exploratory pharmacogenomic analyses were conducted using H3Africa Array data and imputation from an African-focused reference panel on the Sanger platform. Single nucleotide polymorphisms (SNPs) were screened on overall dose- and weight-adjusted AUC and the most significant ones evaluated in the model as categorical covariates on clearance and bioavailability.
Results:
The dataset included 651 plasma concentrations from 109 participants, 82% of whom were living with HIV. Median body weight was 55 kg (range 30-87), median age was 35 years (20-68), and median creatinine clearance was 96 mL/min (40-187).
Ethambutol pharmacokinetics was best described by a two-compartment model with first-order elimination (∆OFV = -59.9; P < 10^-6 compared to a one-compartment model). Absorption was optimally described using eight transit compartments prior to first-order absorption, reflecting delayed and variable uptake. Clearance and volume parameters scaled best with FFM (∆OFV = -40.3; P < 10^-6 compared to no allometry). Total clearance was split into renal and non-renal pathways, with creatinine clearance (used as an estimate of renal function) as a covariate on renal clearance (∆OFV = -20.3; P < 10^-5). Renal clearance accounted for ~40% of total clearance. The typical values of renal clearance and non-renal clearance were 6.29 L/h and 10.4 L/h, respectively. The typical values of the central and peripheral volume of distribution were 103 L and 122 L, respectively. Exploratory pharmacogenomics identified an imputed SNP (rs62341564 A>C) associated with a ~60% reduction in bioavailability in variant carriers (AC) (∆OFV = -43.9; P < 10^-10). Within this cohort, 99 participants had the wildtype (AA), 7 participants were carriers of the variant (heterozygous) (AC), and the SNP was missing for 3 participants. Conclusions: Ethambutol disposition in adults with RR/MDR-TB was well described by a two-compartment model with transit-compartment absorption. Renal function was an important predictor of clearance. The ethambutol two-compartment disposition model with first-order absorption and transit compartments is in agreement with previous reports [8,9], but the typical values of clearance and peripheral volume of distribution were lower than previously reported, possibly because the study was conducted in a cohort with RR/MDR-TB, whereas most previous work is in drug susceptible TB [8,10]. A novel SNP was associated with reduced bioavailability. This SNP is not linked to any known genes, has not previously been reported in any studies or linked to ethambutol pharmacokinetics. Further validation is required. References: [1] World Health Organization. WHO treatment guidelines for drug-resistant tuberculosis, 2016 update. Geneva: World Health Organization; 2016. [2] World Health Organization. Consolidated Guidelines on Tuberculosis Treatment. Geneva: World Health Organization; 2019. [3] Mitchison DA. The action of antituberculosis drugs in short-course chemotherapy. Tubercle 1985;66:219–25. https://doi.org/10.1016/0041-3879(85)90040-6. [4] Lee CS, Brater DC, Gambertoglio JG, Benet LZ. Disposition kinetics of ethambutol in man. Journal of Pharmacokinetics and Biopharmaceutics 1980 8:4 1980;8:335–46. https://doi.org/10.1007/BF01059382. [5] Republic of South Africa Department of Health. Interim Clinical Guidance for the Implementation of Injectable-Free Regimens for Rifampicin-Resistant Tuberculosis in Adults, Adolescents and Children. 2018. [6] Anderson BJ, Holford NHG. Mechanism-based concepts of size and maturity in pharmacokinetics. Annu Rev Pharmacol Toxicol 2008;48:303–32. https://doi.org/10.1146/annurev.pharmtox.48.113006.094708. [7] Holford N, Heo YA, Anderson B. A Pharmacokinetic Standard for Babies and Adults. J Pharm Sci 2013;102:2941–52. https://doi.org/10.1002/jps.23574. [8] Ndzamba B, Denti P, McIlleron H, Smith P, Mthiyane T, Rustomjee R, et al. Pharmacokinetics of ethambutol and weight banded dosing in South African adults newly diagnosed with tuberculosis and HIV. Antimicrob Agents Chemother 2025;69. https://doi.org/10.1128/aac.01200-24. [9] Beraldi-Magalhaes F, Parker SL, Sanches C, Garcia LS, Carvalho BKS, Fachi MM, et al. Is Dosing of Ethambutol as Part of a Fixed-Dose Combination Product Optimal for Mechanically Ventilated ICU Patients with Tuberculosis? A Population Pharmacokinetic Study. Antibiotics 2021, Vol 10, Page 1559 2021;10:1559. https://doi.org/10.3390/antibiotics10121559. [10] Jönsson S, Davidse A, Wilkins J, Van Der Walt JS, Simonsson USH, Karlsson MO, et al. Population pharmacokinetics of ethambutol in South African tuberculosis patients. Antimicrob Agents Chemother 2011;55:4230–7. https://doi.org/10.1128/AAC.00274-11.
Reference: PAGE 34 (2026) Abstr 11924 [www.page-meeting.org/?abstract=11924]
Poster: Drug/Disease Modelling - Infection