| Autor: |
Soedarsono Soedarsono, Rannissa Puspita Jayanti, Ni Made Mertaniasih, Tutik Kusmiati, Ariani Permatasari, Dwi Wahyu Indrawanto, Anita Nur Charisma, Rika Yuliwulandari, Nguyen Phuoc Long, Young-Kyung Choi, Pham Quang Hoa, Pham Vinh Hoa, Yong-Soon Cho, Jae-Gook Shin |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
International Journal of Infectious Diseases, Vol 117, Iss , Pp 8-14 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1201-9712 |
| DOI: |
10.1016/j.ijid.2022.01.003 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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