Population pharmacokinetics and pharmacodynamics of investigational regimens' drugs in the TB-PRACTECAL clinical trial (the PRACTECAL-PKPD study): a prospective nested study protocol in a randomised controlled trial

Bern-Thomas Nyang'wa, Frank Kloprogge, David A J Moore, Amaya Bustinduy, Ilaria Motta, Catherine Berry, Geraint R Davies, Bern-Thomas Nyang'wa, Frank Kloprogge, David A J Moore, Amaya Bustinduy, Ilaria Motta, Catherine Berry, Geraint R Davies

Abstract

Introduction: Drug-resistant tuberculosis (TB) remains a global health threat, with little over 50% of patients successfully treated. Novel regimens like the ones being studied in the TB-PRACTECAL trial are urgently needed. Understanding anti-TB drug exposures could explain the success or failure of these trial regimens. We aim to study the relationship between the patients' exposure to anti-TB drugs in TB-PRACTECAL investigational regimens and their treatment outcomes.

Methods and analysis: Adults with multidrug-resistant TB randomised to investigational regimens in TB-PRACTECAL will be recruited to a nested pharmacokinetic-pharmacodynamic (PKPD) study. Venous blood samples will be collected at 0, 2 and 23 hours postdose on day 1 and 0, 6.5 and 23 hours postdose during week 8 to quantify drug concentrations in plasma. Trough samples will be collected during week 12, 16, 20 and 24 visits. Opportunistic samples will be collected during weeks 32 and 72. Drug concentrations will be quantified using liquid chromatography-tandem mass spectrometry. Sputum samples will be collected at baseline, monthly to week 24 and then every 2 months to week 108 for MICs and bacillary load quantification. Full blood count, urea and electrolytes, liver function tests, lipase, ECGs and ophthalmology examinations will be conducted at least monthly during treatment.PK and PKPD models will be developed for each drug with nonlinear mixed effects methods. Optimal dosing will be investigated using Monte-Carlo simulations.

Ethics and dissemination: The study has been approved by the Médecins sans Frontières (MSF) Ethics Review Board, the LSHTM Ethics Committee, the Belarus RSPCPT ethics committee and PharmaEthics and the University of Witwatersrand Human Research ethics committee in South Africa. Written informed consent will be obtained from all participants. The study results will be shared with public health authorities, presented at scientific conferences and published in a peer-reviewed journal.

Trial registration number: NCT04081077; Pre-results.

Keywords: clinical trials; pharmacology; tuberculosis.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1
Figure 1
Trial sites participating in the PRACTECAL-PKPD sub-study. PKPD, pharmacokinetic-pharmacodynamic; TB, tuberculosis.
Figure 2
Figure 2
The PRACTECAL–PKPD study investigational schedule. Cfz, clofazimine; Mfx, moxifloxacin; PKPD, pharmacokinetic-pharmacodynamic.

References

    1. World Health Organization . Global tuberculosis report 2020. Geneva: World Health Organization; 2020.
    1. Conradie F, Diacon AH, Ngubane N, et al. . Treatment of highly drug-resistant pulmonary tuberculosis. N Engl J Med 2020;382:893–902. 10.1056/NEJMoa1901814
    1. World Health Organization . WHO consolidated guidelines on tuberculosis. Module 4: treatment - drug-resistant tuberculosis treatment. Geneva: World Health Organization; 2020.
    1. van Heeswijk RPG, Dannemann B, Hoetelmans RMW. Bedaquiline: a review of human pharmacokinetics and drug-drug interactions. J Antimicrob Chemother 2014;69:2310–8. 10.1093/jac/dku171
    1. Pasipanodya JG, McIlleron H, Burger A, et al. . Serum drug concentrations predictive of pulmonary tuberculosis outcomes. J Infect Dis 2013;208): :1464–73. 10.1093/infdis/jit352
    1. Kloprogge F, Mwandumba HC, Banda G, et al. . Longitudinal pharmacokinetic-pharmacodynamic biomarkers correlate with treatment outcome in drug-sensitive pulmonary tuberculosis: a population pharmacokinetic-pharmacodynamic analysis. Open Forum Infect Dis 2020;7:ofaa218. 10.1093/ofid/ofaa218
    1. Dooley KE, Hanna D, Mave V, et al. . Advancing the development of new tuberculosis treatment regimens: the essential role of translational and clinical pharmacology and microbiology. PLoS Med 2019;16:e1002842. 10.1371/journal.pmed.1002842
    1. Aarons L, Ogungbenro K. Optimal design of pharmacokinetic studies. Basic Clin Pharmacol Toxicol 2010;106:250–5. 10.1111/j.1742-7843.2009.00533.x
    1. Luque S, Grau S, Alvarez-Lerma F, et al. . Plasma and cerebrospinal fluid concentrations of linezolid in neurosurgical critically ill patients with proven or suspected central nervous system infections. Int J Antimicrob Agents 2014;44:409–15. 10.1016/j.ijantimicag.2014.07.001
    1. McGee B, Dietze R, Hadad DJ, et al. . Population pharmacokinetics of linezolid in adults with pulmonary tuberculosis. Antimicrob Agents Chemother 2009;53:3981–4. 10.1128/AAC.01378-08
    1. Meagher AK, Forrest A, Rayner CR, et al. . Population pharmacokinetics of linezolid in patients treated in a compassionate-use program. Antimicrob Agents Chemother 2003;47:548–53. 10.1128/AAC.47.2.548-553.2003
    1. Plock N, Buerger C, Joukhadar C, et al. . Does linezolid inhibit its own metabolism? Population pharmacokinetics as a tool to explain the observed nonlinearity in both healthy volunteers and septic patients. Drug Metab Dispos 2007;35:1816–23. 10.1124/dmd.106.013755
    1. Tsuji Y, Holford NHG, Kasai H, et al. . Population pharmacokinetics and pharmacodynamics of linezolid-induced thrombocytopenia in hospitalized patients. Br J Clin Pharmacol 2017;83:1758–72. 10.1111/bcp.13262
    1. Svensson EM, Murray S, Karlsson MO. Rifampicin and rifapentine significantly reduce concentrations of bedaquiline, a new anti-TB drug. J Antimicrob Chemother 2015;70:1106–14. 10.1093/jac/dku504
    1. Ganesan SSG, Hughes D. Identification of optimal dose and dosing regimen of clofazimine for the treatment of multidrug-resistant tuberculosis (MDR-TB) based on pharmacokinetic modelling. 46th Conference on Lung Health of the UNION, Cape Town, South AFrica, 2015.
    1. Chang MJ, Jin B, Chae J-W, et al. . Population pharmacokinetics of moxifloxacin, cycloserine, p-aminosalicylic acid and kanamycin for the treatment of multi-drug-resistant tuberculosis. Int J Antimicrob Agents 2017;49:677–87. 10.1016/j.ijantimicag.2017.01.024
    1. Peloquin CA, Hadad DJ, Molino LPD, et al. . Population pharmacokinetics of levofloxacin, gatifloxacin, and moxifloxacin in adults with pulmonary tuberculosis. Antimicrob Agents Chemother 2008;52:852–7. 10.1128/AAC.01036-07
    1. Pranger AD, Kosterink JGW, van Altena R, et al. . Limited-sampling strategies for therapeutic drug monitoring of moxifloxacin in patients with tuberculosis. Ther Drug Monit 2011;33:350–4. 10.1097/FTD.0b013e31821b793c
    1. Zvada SP, Denti P, Geldenhuys H, et al. . Moxifloxacin population pharmacokinetics in patients with pulmonary tuberculosis and the effect of intermittent high-dose rifapentine. Antimicrob Agents Chemother 2012;56:4471–3. 10.1128/AAC.00404-12
    1. Zvada SP, Denti P, Sirgel FA, et al. . Moxifloxacin population pharmacokinetics and model-based comparison of efficacy between moxifloxacin and ofloxacin in African patients. Antimicrob Agents Chemother 2014;58:503–10. 10.1128/AAC.01478-13
    1. Salinger DH, Subramoney V, Everitt D, et al. . Population pharmacokinetics of the antituberculosis agent Pretomanid. Antimicrob Agents Chemother 2019;63:e00907–19. 10.1128/AAC.00907-19
    1. Nyberg J, Ueckert S, Strömberg EA, et al. . PopED: an extended, parallelized, nonlinear mixed effects models optimal design tool. Comput Methods Programs Biomed 2012;108:789–805. 10.1016/j.cmpb.2012.05.005
    1. McLeay SC, Vis P, van Heeswijk RPG, et al. . Population pharmacokinetics of bedaquiline (TMC207), a novel antituberculosis drug. Antimicrob Agents Chemother 2014;58:5315–24. 10.1128/AAC.01418-13
    1. Lindbom L, Pihlgren P, Jonsson EN, et al. . PsN-Toolkit-a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Programs Biomed 2005;79:241–57. 10.1016/j.cmpb.2005.04.005
    1. Douch E. Engaging communities in tuberculosis research: the experience of the TB-PRACTECAL trial. the BMJ opinion 2018.
    1. Medecins SANS Frontieres PV-TB-D12 MSF severity grading scale 2016.
    1. Nguyen THT, Mouksassi M-S, Holford N, et al. . Model evaluation of continuous data pharmacometric models: metrics and graphics. CPT Pharmacometrics Syst Pharmacol 2017;6:87–109. 10.1002/psp4.12161

Source: PubMed

3
订阅