Population pharmacokinetics of delamanid and its main metabolite DM-6705 in patients with multidrug resistant tuberculosis
Lénaïg Tanneau (1), Mats O Karlsson (1), Andreas H Diacon (2), Justin Shenje (3), Jorge De Los Rios (4), Kelly E Dooley (5), Gary Maartens (6), Elin M Svensson (1, 7)
(1) Department of Pharmacy, Uppsala University, Uppsala, Sweden (2) TASK Applied Science, Cape Town, South Africa (3) SATVI, University of Cape Town, South Africa (4) Barranco Clinical Research Site, Asociacion Civil Impacta Salud y Educacion, Lima, Peru (5) Center for Tuberculosis Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA (6) Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa (7) Department of Pharmacy, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
Objectives: With approximately 10 million new cases and 1.4 million related deaths reported in 2019, tuberculosis (TB) was the most common cause of death due to an infectious disease globally, before the emergence of Covid-19 [1]. The public threat is aggravated by resistance to first line treatment and limited therapeutic options for patients with drug-resistant (DR) TB. Delamanid was registered by the EMA in 2014 as a new treatment of DR TB. Delamanid is a nitromidazole agent primarily metabolized by albumin into DM-6705 [2]. This metabolite appears to be associated with QTc prolongation [3]. The aims of this analysis were to develop a population pharmacokinetics (PK) model to describe observed delamanid and DM-6705 concentrations over time, and to test possible covariate parameter relationships that could influence absorption, distribution and clearance.
Methods: PK data from a randomized, open-label, phase 2 study to assess the safety of delamanid and bedaquiline co-administration were analyzed [4]. We focused on participants who received delamanid with or without bedaquiline (28 patients in each group), together with a multidrug background regimen. Delamanid was dosed at 100mg twice daily. Six blood samples were collected over 24 hours at weeks 2, 8 and 24, and samples 4h after dosing were drawn every two weeks. Exact time and date were recorded for the 3 doses before each PK sampling in the analysis dataset. Pill count and adherence questions (about how well the patients remembered to take the study drugs) were performed weekly between weeks 1 and 8, every second week between weeks 10 and 24. Modeling was performed using a non-linear mixed effect approach. Models to describe the mechanism of albumin metabolizing delamanid into DM-6705, as well as models to describe adherence were explored. Patients’ demographics such as gender, age, baseline albumin, race, HIV co-infection and TB type (drug sensitive vs DR), as well as bedaquiline co-administration and time of the day (morning vs evening) were tested as covariates.
Results: Delamanid PK was best described by a one-compartment disposition model with transit compartment absorption and linear elimination. The formation of the metabolite DM-6705 and its PK was described by a one-compartment disposition model with a linear elimination from the central compartment. Allometric scaling with body weight was included on all disposition parameters. Population estimates for mean absorption time, apparent delamanid CLDLM, VDLM and DM-6705 CLDM-6705, V DM-6705 were 1.39 h (RSE 19.1%), 28.8 L/h (RSE 4.64%), 635.7 L (RSE 7.92%), 81.4 L/h (RSE 11.7%), 22140 L (RSE 15.9%) respectively. Predicted terminal half-life values for delamanid and DM-6705 were 15.3 hours and 7.8 days, respectively. The relative bioavailability was found to vary by -/+60% over the day (morning/evening step effect). An adherence model allowing changing bioavailability after week 8 was included with 2 different components (ADHMD and ADHNMD) , depending on the patient’s answer to the adherence questions (18% reduction in patients that never declared to have missed a dose vs 39% reduction in patients that declared to have missed a dose at least once). Inter-individual variability was included on CLDLM, VDLM, CLDM-6705 ,V DM-6705, ADHMD, ADHNMD and proportional residual errors for delamanid and DM-6705. Inter-occasion variability was included on bioavailability. None of the attempts to describe the effect of albumin on delamanid metabolism were successful; neither observed baseline albumin levels nor model-derived albumin levels over the study period had a correlation with DLM/DM-6705 clearances. Delamanid PK was not found to be impacted by bedaquiline co-administration, and, additional to allometry, no patients’ demographics were included as covariates.
Conclusions: The PK of delamanid and DM-6705 was adequately described using one combined model. This is the first public presentation of a population PK model of delamanid and its main metabolite that can be utilized in future exposure-response or exposure-safety analyzes.
References:
[1] World Health Organization, “WHO | Global tuberculosis report 2020,” 2020. https://www.who.int/publications/i/item/9789240013131 (accessed Mar. 17, 2021).
[2] K. Sasahara et al., “Pharmacokinetics and Metabolism of Delamanid, a Novel Anti-Tuberculosis Drug, in Animals and Humans: Importance of Albumin Metabolism In Vivo,” Drug Metab. Dispos., vol. 43, no. 8, pp. 1267–1276, Aug. 2015, doi: 10.1124/dmd.115.064527.
[3] Y. Liu et al., “Delamanid: From discovery to its use for pulmonary multidrug-resistant tuberculosis (MDR-TB),” Tuberculosis, vol. 111, pp. 20–30, Jul. 2018, doi: 10.1016/j.tube.2018.04.008.
[4] K. E. Dooley et al., “QT effects of bedaquiline, delamanid, or both in patients with rifampicin-resistant tuberculosis: a phase 2, open-label, randomised, controlled trial,” Lancet Infect Dis, Feb. 2021, doi: 10.1016/S1473-3099(20)30770-2.