Kamunkhwala Gausi (1); Sachiko Miyahara (2); Elisa Ignatius (5); Xin Sun (2); Laura Moran (7); Richard Hafner (6); Susan Rosenkranz (2); Susan Swindells (4); Andreas Diacon (3); Kelly Dooley (5); Paolo Denti (1)
1. Division of Clinical Pharmacology, University of Cape Town, Cape Town, South Africa. 2. Harvard T.H. Chan School of Public Health, Boston, MA, USA. 3. Task Applied Science, Bellville, South Africa. 4. University of Nebraska Medical Center, Omaha, NE, USA. 5.Johns Hopkins University School of Medicine, Baltimore, MD, USA . 6. Division of AIDS, National Institute of Allergy and Infectious Diseases, Bethesda, MD, USA . 7.Social & Scientific Systems, Silver Spring, MD, USA
Objectives: Recent pharmacodynamic studies have reported the effectiveness of high doses of isoniazid against strains of tuberculosis with low to moderate levels of isoniazid resistance1(e.g. inhA mutation). Even though the World Health Organization (WHO) guidelines on drug-resistant tuberculosis recommend the inclusion of double dose (10 mg/kg) isoniazid within the 9-month regimen for multi-drug-resistant tuberculosis 2,3, very little information is available on its pharmacokinetics at these doses. This study aims at investigating the pharmacokinetics of high dose isoniazid in individuals with isoniazid-resistant TB, taking into account the large variability in isoniazid due to N-acetyltransferase type 2 (NAT2) genotype4.
Methods: Adults with drug-sensitive or isoniazid-resistant tuberculosis were recruited into an open-label phase 2A, randomized clinical trial (ACTG A5312). All participants were prescribed a daily dose of isoniazid monotherapy for 7 days. Participants with drug-sensitive isolates were prescribed isoniazid 5 mg/kg, while those with inhA mutated isolates were randomized to 5, 10, and 15 mg/kg. PK samples were collected on day 6 after commencing isoniazid dose at pre-dose, 0.5, 1, 2, 4, 6, 8, 12, and 24 hours after dose. The data was interpreted in NONMEM. Records of concentration below the limit of quantification (BLQ) values were imputed as half of the lower limit of quantification (LLOQ)5 and the additive error was inflated by 20% of the LLOQ . When the terminal phase of a PK profile contained a series of BLQ values, only the first one was used for estimation, but all points were retained for simulation diagnostics as visual predictive checks (VPCs).
Results: 58 adults were recruited, of whom 16 had drug-sensitive isolates and received 5mg/kg and 42 had drug-resistant isolates of whom 16 were randomized to 5mg/kg, 13 to 10mg/kg, and 13 to 15mg/kg. The median weight, and age at study entry were 51 (range 41, 82) kg, and 31 (range 18, 58) years, respectively. The pharmacokinetics of isoniazid was well described using a two-compartment disposition model with transit compartment absorption and first-order elimination implemented using a well-stirred liver model with saturation of hepatic extraction6. The well-stirred liver model required the following assumptions: isoniazid protein binding of 5%, hepatic blood flow of 90 L/h, and a liver volume of 1 L for a typical individual (70-kg body weight/56.1-kg fat-free mass). Allometric scaling based on fat-free mass was applied to all disposition and liver parameters. A mixture model was used to allocate the participants into rapid, intermediate, and slow NAT2 acetylators7. The model predicted a typical individual with fat-free mass of 44 kg to have oral clearance of 10.4, 31.1, and 59.2 L/h if slow, intermediate, or rapid acetylator, respectively. Saturation of first-pass was parameterized using Michaelis-Menten model and had a Km of 14.8 mg/L (delta OFV = 20), thus mainly affecting slow metabolisers on higher dose who achieve higher concentrations.
Conclusions: We have developed a PK model of isoniazid characterizing the saturation of first-pass metabolism when a high dose of isoniazid is administered. While the clinical relevance of this phenomenon is unclear, it should be taken into account when identifying safe and effective doses of isoniazid for patients with drug-resistant tuberculosis.
References:
[1] Lempens, P. et al. Isoniazid resistance levels of Mycobacterium tuberculosis can largely be predicted by high-confidence resistance-conferring mutations. Sci. Rep. 8, (2018).
[2] World Health Organization WHO consolidated guidelines on drug-resistant tuberculosis treatment. (Geneva, 2019).at <http://apps.who.int/bookorders.>
[3] World Health Organization Frequently asked questions about the implementation of the new WHO recommendation on the use of the shorter MDR-TB regimen under programmatic conditions. (2016).at <https://www.who.int/tb/areas-of-work/drug-resistant-tb/treatment/FAQshorter_MDR_regimen.pdf>
[4] Kinzig-Schippers, M. et al. Should we use N-acetyltransferase type 2 genotyping to personalize isoniazid doses? Antimicrob. Agents Chemother. 49, 1733–1738 (2005).
[5] Beal, S. L. Ways to Fit a PK Model with Some Data Below the Quantification Limit. J. Pharmacokinet. Pharmacodyn. 28, (2001).
[6] Gordi, T. et al. A semiphysiological pharmacokinetic model for artemisinin in healthy subjects incorporating autoinduction of metabolism and saturable first-pass hepatic extraction. Br. J. Clin. Pharmacol. 59, 189–98 (2005).
[7] Keizer, R. J., Zandvliet, A. S., Beijnen, J. H., Schellens, J. H. M. & Huitema, A. D. R. Performance of Methods for Handling Missing Categorical Covariate Data in Population Pharmacokinetic Analyses. AAPS J. 14, 601–611 (2012).
Reference: PAGE () Abstr 9479 [www.page-meeting.org/?abstract=9479]
Poster: Drug/Disease Modelling - Infection