1. Academic Validation
  2. Population pharmacokinetic analysis of isoniazid, acetylisoniazid, and isonicotinic acid in healthy volunteers

Population pharmacokinetic analysis of isoniazid, acetylisoniazid, and isonicotinic acid in healthy volunteers

  • Antimicrob Agents Chemother. 2015 Nov;59(11):6791-9. doi: 10.1128/AAC.01244-15.
Kok-Yong Seng 1 Kim-Hor Hee 2 Gaik-Hong Soon 2 Nicholas Chew 3 Saye H Khoo 4 Lawrence Soon-U Lee 5
Affiliations

Affiliations

  • 1 Yong Loo Lin School of Medicine, National University of Singapore, Singapore Defence Medical and Environmental Research Institute, DSO National Laboratories, Singapore.
  • 2 Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • 3 Yong Loo Lin School of Medicine, National University of Singapore, Singapore National University Health System, Singapore.
  • 4 University of Liverpool, Liverpool, United Kingdom.
  • 5 Yong Loo Lin School of Medicine, National University of Singapore, Singapore National University Health System, Singapore lawrence_lee@nuhs.edu.sg.
Abstract

In this study, we aimed to quantify the effects of the N-acetyltransferase 2 (NAT2) phenotype on isoniazid (INH) metabolism in vivo and identify Other sources of pharmacokinetic variability following single-dose administration in healthy Asian adults. The concentrations of INH and its metabolites acetylisoniazid (AcINH) and isonicotinic acid (INA) in plasma were evaluated in 33 healthy Asians who were also given efavirenz and rifampin. The pharmacokinetics of INH, AcINH, and INA were analyzed using nonlinear mixed-effects modeling (NONMEM) to estimate the population pharmacokinetic parameters and evaluate the relationships between the parameters and the elimination status (fast, intermediate, and slow acetylators), demographic status, and measures of renal and hepatic function. A two-compartment model with first-order absorption best described the INH pharmacokinetics. AcINH and INA data were best described by a two- and a one-compartment model, respectively, linked to the INH model. In the final model for INH, the derived metabolic phenotypes for NAT2 were identified as a significant covariate in the INH clearance, reducing its interindividual variability from 86% to 14%. The INH clearance in fast eliminators was 1.9- and 7.7-fold higher than in intermediate and slow eliminators, respectively (65 versus 35 and 8 liters/h). Creatinine clearance was confirmed as a significant covariate for AcINH clearance. Simulations suggested that the current dosing guidelines (200 mg for 30 to 45 kg and 300 mg for >45 kg) may be suboptimal (3 mg/liter ≤ Cmax ≤ 6 mg/liter) irrespective of the acetylator class. The analysis established a model that adequately characterizes INH, AcINH, and INA pharmacokinetics in healthy Asians. Our results refine the NAT2 phenotype-based predictions of the pharmacokinetics for INH.

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