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Development of population pharmacokinetics model of isoniazid in Indonesian patients with tuberculosis.

Authors :
Soedarsono S
Jayanti RP
Mertaniasih NM
Kusmiati T
Permatasari A
Indrawanto DW
Charisma AN
Yuliwulandari R
Long NP
Choi YK
Hoa PQ
Hoa PV
Cho YS
Shin JG
Source :
International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases [Int J Infect Dis] 2022 Apr; Vol. 117, pp. 8-14. Date of Electronic Publication: 2022 Jan 10.
Publication Year :
2022

Abstract

Objectives: No population pharmacokinetics (PK) model of isoniazid (INH) has been reported for the Indonesian population with tuberculosis (TB). Therefore, we aimed to develop a population PK model to optimize pharmacotherapy of INH on the basis of therapeutic drug monitoring (TDM) implementation in Indonesian patients with TB.<br />Materials and Methods: INH concentrations, N-acetyltransferase 2 (NAT2) genotypes, and clinical data were collected from Dr. Soetomo General Academic Hospital, Indonesia. A nonlinear mixed-effect model was used to develop and validate the population PK model.<br />Results: A total of 107 patients with TB (with 153 samples) were involved in this study. A one-compartment model with allometric scaling for bodyweight effect described well the PK of INH. The NAT2 acetylator phenotype significantly affected INH clearance. The mean clearance rates for the rapid, intermediate, and slow NAT2 acetylator phenotypes were 55.9, 37.8, and 17.7 L/h, respectively. Our model was well-validated through visual predictive checks and bootstrapping.<br />Conclusions: We established the population PK model for INH in Indonesian patients with TB using the NAT2 acetylator phenotype as a significant covariate. Our Bayesian forecasting model should enable optimization of TB treatment for INH in Indonesian patients with TB.<br />Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest.<br /> (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Details

Language :
English
ISSN :
1878-3511
Volume :
117
Database :
MEDLINE
Journal :
International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
Publication Type :
Academic Journal
Accession number :
35017103
Full Text :
https://doi.org/10.1016/j.ijid.2022.01.003