TY - JOUR
T1 - Development of population pharmacokinetics model of isoniazid in Indonesian patients with tuberculosis
AU - Soedarsono, Soedarsono
AU - Jayanti, Rannissa Puspita
AU - Mertaniasih, Ni Made
AU - Kusmiati, Tutik
AU - Permatasari, Ariani
AU - Indrawanto, Dwi Wahyu
AU - Charisma, Anita Nur
AU - Yuliwulandari, Rika
AU - Long, Nguyen Phuoc
AU - Choi, Young Kyung
AU - Hoa, Pham Quang
AU - Hoa, Pham Vinh
AU - Cho, Yong Soon
AU - Shin, Jae Gook
N1 - Publisher Copyright:
© 2022 The Authors
PY - 2022/4
Y1 - 2022/4
N2 - 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. 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. 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. 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.
AB - 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. 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. 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. 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.
KW - Indonesia
KW - Isoniazid
KW - Population Pharmacokinetics
KW - Therapeutic Drug Monitoring
KW - Tuberculosis
UR - http://www.scopus.com/inward/record.url?scp=85125455521&partnerID=8YFLogxK
U2 - 10.1016/j.ijid.2022.01.003
DO - 10.1016/j.ijid.2022.01.003
M3 - Article
C2 - 35017103
AN - SCOPUS:85125455521
SN - 1201-9712
VL - 117
SP - 8
EP - 14
JO - International Journal of Infectious Diseases
JF - International Journal of Infectious Diseases
ER -