Stijn W. van Beek (1), Precious Ngwalero (2), James C.M. Brust (3), Paolo Denti (2), Sean Wasserman (4), Gary Maartens (2, 4), Graeme Meintjes (4), Anton Joubert (2), Jennifer Norman (2), Sandra Castel (2), Neel R Gandhi (5,6), Helen McIlleron (2,4), Lubbe Wienser (2), Elin M. Svensson (1,7)
(1) Department of Pharmacy, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands, (2) Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa, (3) Division of General Internal Medicine, Department of Medicine, Albert Einstein College of Medicine & Montefiore Medical Center, Bronx, NY, USA, (4) Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine, Department of Medicine, University of Cape Town, Cape Town, South Africa, (5) Department of Epidemiology & Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA, (6) Division of Infectious Diseases, Emory School of Medicine, Emory University, Atlanta, GA, USA, (7) Department of Pharmacy, Uppsala University, Uppsala, Sweden
Objectives: Tuberculosis is one of the leading causes of mortality from a single pathogen worldwide [1]. Meanwhile, drug-resistant tuberculosis is becoming more widespread, making treatment increasingly difficult. The World Health Organization recommends a treatment regimen including bedaquiline (BDQ) for patients with drug-resistant tuberculosis [2]. While BDQ and its primary metabolite M2 accumulate within cells which may be important for efficacy and toxicity, intracellular pharmacokinetics have not been characterized [3]. The objective of this study was to determine the relationship between plasma and intracellular pharmacokinetics of BDQ and M2.
Methods: Data was obtained from the PROBeX study – an observational cohort study of patients with rifampicin-resistant tuberculosis in South Africa [4]. A selection of the participants was enrolled in a sub-study, in which single pharmacokinetic samples of plasma and peripheral blood mononuclear cells (PBMCs) were collected at months 1, 2 and 6 of BDQ treatment and at 3 and 6 months after end of treatment. Intensive pharmacokinetic sampling was also performed at month 2 with plasma sampling at pre-dose, 1, 2, 3, 4, 5, 6 and 24 hours after dosing and PBMC sampling at pre-dose, 4-6 and 24 hours after dosing. We developed a novel assay using high-performance liquid chromatography-tandem mass spectrometry to measure the intracellular BDQ and M2 concentrations in PBMCs. The plasma pharmacokinetic data were fitted without parameter re-estimation using a previously established model for BDQ and M2 which included models describing the change in total body weight and albumin over time [5]. The individual plasma pharmacokinetic parameters were used as input to the intracellular model. Intracellular drug penetration was described using effect compartment models in which the intracellular-plasma equilibration half-life and accumulation ratio were estimated [6]. Covariate effects of age, sex, race, total body weight and HIV status on the intracellular accumulation ratio were explored. Confidence intervals (CI) of the pharmacokinetic parameters were determined using sampling importance resampling [7].
Results: Twenty patients were included in the analysis providing 187 plasma pharmacokinetic observations and 67 intracellular pharmacokinetic observations for BDQ and M2 each. Of the twenty patients, nine were HIV-positive. The previously established model fitted the plasma pharmacokinetics well. Intracellular pharmacokinetics of BDQ and M2 were described by one effect compartment each. The intracellular-plasma equilibration half-life could not be estimated reliably and was fixed at 1 minute (i.e. practically instantaneous). We estimated a linear increase in the intracellular-plasma accumulation ratio for BDQ and M2, reaching maximum effect after 2 months of treatment. The time to maximum effect was chosen to reflect accumulation during the life-span of PBMCs, taking into account the frequencies of different PBMCs and their life-spans [8]. The typical intracellular-plasma ratio 1 month after start of treatment was 0.63 (95%CI: 0.43-0.95) for BDQ and 12.4 (95%CI: 8.97-18.7) for M2. Typical maximum intracellular-plasma ratios at month 2 for BDQ and M2 were estimated at 1.11 (95%CI: 0.79-1.65) and 22.1 (95%CI: 15.7-31.3), respectively. The intracellular-plasma ratio for both BDQ and M2 in HIV-positive patients was decreased by 53% (95%CI: 24-72%) compared to HIV-negative patients. Interindividual variability on the intracellular-plasma ratio was estimated at 52% (95%CI: 33-82%).
Conclusions: This is the first study to quantify the relationship between plasma and intracellular pharmacokinetics of BDQ and M2. We have shown that both BDQ and M2 accumulate over time in PBMCs. Intracellular BDQ concentrations were in the same range as in plasma, while intracellular M2 concentrations were much higher than the plasma concentrations. A possible explanation for the difference in intracellular-plasma ratio is the more avid binding of M2 to intracellular phospholipids [9]. HIV positivity was associated with a lower intracellular-plasma ratio of BDQ and M2. The HIV effect may be caused by infection-related dysfunction of immune cells affecting drug transfer or the decreased life-span of PBMCs in HIV-positive individuals [10-12]. Studies examining the correlation between intracellular concentrations and efficacy and safety will be an important next step to determine the significance of the presented findings and to optimize BDQ dosing.
References:
[1] World Health Organization. Global tuberculosis report 2020. 2020 [accesed at 05-05-2021]; Available from: https://www.who.int/teams/global-tuberculosis-programme/tb-reports.
[2] World Health Organization. WHO consolidated guidelines on drug-resistant tuberculosis treatment. 2019 [accesed at 05-05-2021]; Available from: https://www.who.int/tb/publications/2019/consolidated-guidelines-drug-resistant-TB-treatment/en/.
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[8] Abbas, A., A. Lichtman, and S. Pillai, Cellular and Molecular Immunology. 9th ed. 2017, Amsterdam: Elsevier.
[9] Mesens, N., et al., Elucidating the role of M2 in the preclinical safety profile of TMC207, in 38th World Conference on Lung Health. 2007: Cape Town, South Africa.
[10] Korencak, M., et al., Effect of HIV infection and antiretroviral therapy on immune cellular functions. JCI Insight, 2019. 4(12).
[11] Khaitan, A. and D. Unutmaz, Revisiting immune exhaustion during HIV infection. Curr HIV/AIDS Rep, 2011. 8(1): p. 4-11.
[12] Brenchley, J.M., et al., Preferential Infection Shortens the Life Span of Human ImmunodeficiencyVirus-Specific CD4+ T Cells In Vivo. Journal of Virology, 2006. 80(14): p. 6801-6809.
Reference: PAGE 29 (2021) Abstr 9799 [www.page-meeting.org/?abstract=9799]
Poster: Drug/Disease Modelling - Infection