Jose Miguel Calderin (1), Sean Wasserman (2, 3), Juan Eduardo Resendiz-Galvan (1), Noha Abdelgawad (1), Angharad Davis (3, 5, 6), Cari Stek (3), Lubbe Wiesner (1), Robert J. Wilkinson (3, 4, 5, 7), Paolo Denti (1)
(1) Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, South Africa. (2) Institute for Infection and Immunity, St George’s University of London, United Kingdom. (3) 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. (4) Division of Infectious Diseases and HIV Medicine, Department of Medicine, University of Cape Town, Cape Town, South Africa. (5) The Francis Crick Institute, London NW1 1AT, United Kingdom. (6) Faculty of Life Sciences, University College London, WC1E 6BT, United Kingdom. (7) Department of Infectious Diseases, Imperial College London W12 0NN, United Kingdom.
Objectives: Tuberculosis Meningitis (TBM) represents the most severe and incapacitating manifestation of infection by Mycobacterium tuberculosis, especially among individuals with HIV, where mortality rates can exceed 50% (1).
Isoniazid (INH) is a key first-line drug in tuberculosis (TB) treatment (2). Although well-studied in pulmonary TB, INH plasma pharmacokinetics (PK) and its penetration into the cerebrospinal fluid (CSF) still require further research within the context of TBM. Disease-related changes in blood-brain barrier permeability and dynamic fluctuations in the CSF protein concentrations may significantly impact drug penetration, thus influencing efficacy (1). This analysis aimed to characterize the PK of INH in plasma and CSF from South African adults with HIV-associated TBM.
Methods: This PK study was nested in LASER-TBM, a phase 2a clinical trial evaluating the safety of intensified anti-TB and anti-inflammatory therapy (3). Participants were randomized to one of the three treatment arms to receive either the standard of care (4), or an experimental treatment. Experimental regimens consisted of standard therapy, including INH at 5 mg/kg, along with additional rifampicin (RIF, total oral dose 35 mg/kg/day) and linezolid, with or without aspirin.
Blood samples were collected on day 3 of study enrolment, at pre-dose, 0.5, 1, 2, 3, 6, 8-10, and 24 h post-dose. Sparse sampling was performed on day 28 at pre-dose, 2, and 4 h post-dose. One CSF sample was collected during each visit, with collection timing randomized to intervals of 1-3, 3-6, 6-10, and 24 h after drug administration. INH plasma and CSF concentrations were assayed using LC-MS/MS.
Plasma data were described by testing one- and two-compartment models with or without absorption delay. Since INH is mainly hepatically cleared, a well-stirred liver model was tested to capture the effect of the first-pass metabolism (5), assuming INH protein binding of 5% and hepatic blood flow (QH) of 90 L/h. Allometric scaling of all disposition parameters, including QH, was tested by using either body weight (WT) or fat-free mass (FFM). The effect of the N-acetyltransferase 2 (NAT2) enzyme on INH PK was assessed at an early stage of the modelling process by testing the NAT2 phenotype -slow, intermediate, or rapid– on clearance. A mixture model was used to assign participants with missing NAT2 phenotype to one of three subpopulations, with probabilities fixed to the proportions observed in participants with available information in the cohort (6). The CSF concentrations were modelled by implementing a hypothetical effect compartment linked to the central compartment (plasma), estimating the equilibration half-life and the pseudo-partition coefficient (7).
Results: Forty-nine participants underwent PK sampling during the first visit on day 3 and 34 during the second visit on day 28, contributing a total of 414 plasma and 44 CSF concentrations. The study population had median (1st – 3rd quartile range) age of 38 (34 – 45) years, WT 60 (54 – 74) kg, and FFM 46 (39 – 51) kg.
The plasma PK of INH was best described by a two-compartment disposition model with first-order absorption through a chain of transit compartments and first-order elimination implemented using a well-stirred liver model. As expected, the NAT2 phenotype had a strong effect on the PK variability of INH. The typical values of oral clearance, best scaled allometrically using FFM, were 14.3, 34.2, and 63.7 L/h for slow, intermediate, and rapid acetylators, respectively. CSF concentrations equilibrated with plasma with a half-life of 3.7 h and a pseudo-partition coefficient of 1.06, a value that indicates the relative exposure of INH in CSF compared to plasma at steady state. No statistically significant differences in any PK parameter were observed between the intervention arms receiving the high dose of RIF and the control arm.
Conclusions: We developed a model that adequately described INH PK in plasma and CSF. Our parameter estimates are consistent with published PK models using data from pulmonary TB patients (8,9), suggesting that INH plasma PK in TBM patients is similar to pulmonary TB, even when co-administered with a high dose of RIF, providing evidence for combined use. Furthermore, our model shows that INH achieves exposure in CSF that mirrors its exposure in plasma, supporting further efficacy evaluations in TBM.
References:
[1] Wasserman S, Davis A, Wilkinson RJ, Meintjes G. Key considerations in the pharmacotherapy of tuberculous meningitis. Expert Opin Pharmacother [Internet]. 2019 Oct 13;20(15):1791–5. Available from: https://doi.org/10.1080/14656566.2019.1638912
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[3] Davis AG, Wasserman S, Stek C, Maxebengula M, Jason Liang C, Stegmann S, et al. A Phase 2A Trial of the Safety and Tolerability of Increased Dose Rifampicin and Adjunctive Linezolid, With or Without Aspirin, for Human Immunodeficiency Virus–Associated Tuberculous Meningitis: The LASER-TBM Trial. Clinical Infectious Diseases [Internet]. 2023 Apr 15;76(8):1412–22. Available from: https://doi.org/10.1093/cid/ciac932
[4] WHO operational handbook on tuberculosis Module 4: Treatment Drug-susceptible tuberculosis treatment.
[5] Gordi T, Xie R, Huong N V., Huong DX, Karlsson MO, Ashton M. A semiphysiological pharmacokinetic model for artemisinin in healthy subjects incorporating autoinduction of metabolism and saturable first-pass hepatic extraction. Br J Clin Pharmacol. 2005 Feb;59(2):189–98.
[6] Keizer RJ, Zandvliet AS, Beijnen JH, Schellens JHM, Huitema ADR. Performance of Methods for Handling Missing Categorical Covariate Data in Population Pharmacokinetic Analyses. AAPS J [Internet]. 2012;14(3):601–11. Available from: https://doi.org/10.1208/s12248-012-9373-2
[7] Sheiner LB, Stanski DR, Vozeh S, Miller RD, Ham J. Simultaneous modeling of pharmacokinetics and pharmacodynamics: Application to d-tubocurarine. Clin Pharmacol Ther [Internet]. 1979 Mar 1;25(3):358–71. Available from: https://doi.org/10.1002/cpt1979253358
[8] Gausi K, Chirehwa M, Ignatius EH, Court R, Sun X, Moran L, et al. Pharmacokinetics of standard versus high-dose isoniazid for treatment of multidrug-resistant tuberculosis. Journal of Antimicrobial Chemotherapy [Internet]. 2022 Sep 1;77(9):2489–99. Available from: https://doi.org/10.1093/jac/dkac188
[9] Gausi K, Wiesner L, Norman J, Wallis CL, Onyango-Makumbi C, Chipato T, et al. Pharmacokinetics and Drug-Drug Interactions of Isoniazid and Efavirenz in Pregnant Women Living With HIV in High TB Incidence Settings: Importance of Genotyping. Clin Pharmacol Ther [Internet]. 2021 Apr 1;109(4):1034–44. Available from: https://doi.org/10.1002/cpt.2044
Reference: PAGE 32 (2024) Abstr 10946 [www.page-meeting.org/?abstract=10946]
Poster: Drug/Disease Modelling - Infection