Henrik Bjugård Nyberg [1], Heather Draper [2], Anthony J. Garcia-Prats [2], Stephanie Thee [3], Andrew C. Hooker [1], H. Simon Schaaf [2], Helen McIlleron [4], Anneke C. Hesseling [2], Paolo Denti [4]
[1] Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden [2] Desmond Tutu TB Centre, Department of Paediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, South Africa [3] Department of Pediatrics, Division of Pneumonology and Immunology, Charité University Medicine, Berlin, Germany [4] Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, South Africa
Objectives: As drug resistant tuberculosis becomes more prevalent, improved knowledge of drugs also beyond first-line treatment becomes increasingly important. Ethionamide is used both in first-line and second-line treatment of tuberculosis, including in tuberculous meningitis [1] but the current understanding of its pharmacokinetics (PK) is limited, especially in children. Ethionamide metabolism follows a range of different pathways, with the most prominent being the flavin-dependent monooxygenases found in both humans and in Mycobacterium tuberculosis. This pathway is also the activation mechanism for this pro-drug [2]. The aim of the study was to develop a pediatric population PK model for ethionamide.
Methods: Pharmacokinetic data on ethionamide in children was pooled from 2 observational clinical studies [3,4] conducted in Cape Town, South Africa. The first study contributed 110 children on treatment for multi-drug resistant tuberculosis (MDR-TB), while the second contributed 9 young children (3 mos – 2.5 yrs) treated for drug-susceptible TB. The two studies otherwise had very similar study procedures and demographics. Overall median age was 2.6 years (range: 3 mos – 15 yrs), and their weight median was 12.5 kg (range: 2.5–66 kg). Children received ethionamide once-daily with weight-based dosing of 20 mg/kg up to a maximum of 1,000 mg, in combination with other first- or second-line antituberculosis medications, and with antiretroviral therapy (ART) in the case of HIV co-infection.
Twenty-four of 119 children were HIV-positive, mainly on lopinavir/ritonavir-based ART therapy; 21 were simultaneously treated with rifampicin. Smaller children received crushed tablets (n=101), due to lack of child-friendly formulations, often using a nasogastric tube (n=82) on the day of sampling. Blood samples were collected pre-dose and at 1, 2, 4, 6 (study 2), 8, and 11 (study 1) hours post-dose. The samples from both studies were analyzed in the same laboratory using LC-MS/MS with a validated method; the limit of quantification (LLoQ) was 0.0313 mg/L.
Model development was performed in NONMEM 7.4 [5] using improvements in likelihood, diagnostic plots, and physiological plausibility as criteria for selection. The effects of body weight and fat-free mass (FFM) were investigated using allometric scaling, and that of age, using a maturation function. Other potential covariates such as HIV-status, weight-for-age Z-scores, administration method (crushed vs whole tablet, swallowed vs nasogastric tube) and concomitant medications were explored using step-wise covariate modelling in the PsN software [6]. Several models for absorption and disposition were compared. A combined proportional and additive error model was used, and data below LLoQ was handled using the M6 method [7].
Results: Ethionamide PK in children was best described by a one-compartment disposition model with transit compartment absorption [8] and first-order elimination. Volume of distribution (V) and clearance (CL) were scaled by weight and FFM, respectively. For a typical child weighing 12.5 kg (10 kg of FFM), the model estimated the typical value of CL to be 9.3 L/h and of V to be 21.2 L. A maturation function for clearance improved model fit, but ultimately needed to be stabilized by a weakly-informative prior. Clearance was expected to reach 50% of its mature value one month after birth. HIV-co-infected children had 21% lower bioavailability. A faster absorption (40% shorter mean transit time, MTT) was found in children receiving crushed tablets with or without nasogastric tube, but no difference was found in bioavailability. No drug-drug interactions were identified, most notably with rifampicin, an inducer of several drug-metabolizing enzymes. The stochastic model supported inter-individual variability for clearance (28%) as well as inter-occasion variability for bioavailability (37%) and MTT (62%).
Conclusions: We propose a model that successfully describes ethionamide pharmacokinetics in children, and that could be used for optimization of dosing regimens. The model detects a faster than expected maturation function, which may be a feature of the complex metabolism of ethionamide. The observed HIV effect may be due to one of the concomitantly administered antiretroviral drugs, but with the limited current data we were unable to confirm the precise cause this effect. Crushing tablets or using a nasogastric tube affects the speed, but not the extent of absorption.
References:
[1] Falzon, D. et al, WHO guidelines for the programmatic management of drug resistant tuberculosis: 2016 update, Eur. Respir. J., 2017, 49(3): 1602308.
[2] Vale, N., Gomes, P., Santos, H.A, Metabolism of the Antituberculosis Drug Ethionamide, Current Drug Metabolism, 2013, 14, 151-158.
[3] Denti, P. et al, Levofloxacin Population Pharmacokinetics in South African Children Treated for Multidrug-Resistant Tuberculosis, Antimicrob Agents Chemother. 2018, 62(2).
[4] Bekker, A. et al, Pharmacokinetics of Rifampin, Isoniazid, Pyrazinamide, and Ethambutol in Infants Dosed According to Revised WHO-Recommended Treatment Guidelines, Antimicrob Agents Chemother. 2016, 60(4).
[5] Beal S., Sheiner L.B., Boeckmann A., & Bauer R.J., NONMEM User’s Guides. (1989-2017), Icon Development Solutions, Ellicott City, MD, USA, 2017.
[6] Keizer, R.J., Karlsson, M.O., Hooker, A., Modeling and Simulation Workbench for NONMEM: Tutorial on Pirana, PsN, and Xpose. CPT Pharmacometrics Syst Pharmacol 2013, 2: e50. http://psn.sourceforge.net/
[7] Beal S.L., Ways to fit a PK model with some data below the quantification limit, Journal of pharmacokinetics and pharmacodynamics, vol. 28, Oct. 2001, pp. 481-504.
[8] Savic, R.M., Jonker, D.M., Kerbusch T., and Karlsson, M.O., Implementation of a transit compartment model for describing drug absorption in pharmacokinetic studies, Journal of pharmacokinetics and pharmacodynamics, vol. 34, Oct. 2007, pp. 711-26.
Reference: PAGE 27 (2018) Abstr 8679 [www.page-meeting.org/?abstract=8679]
Poster: Drug/Disease Modelling - Infection