Suppr超能文献

印度尼西亚结核病患者异烟肼群体药代动力学模型的建立。

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

作者信息

Soedarsono Soedarsono, Jayanti Rannissa Puspita, Mertaniasih Ni Made, Kusmiati Tutik, Permatasari Ariani, Indrawanto Dwi Wahyu, Charisma Anita Nur, Yuliwulandari Rika, Long Nguyen Phuoc, Choi Young-Kyung, Hoa Pham Quang, Hoa Pham Vinh, Cho Yong-Soon, Shin Jae-Gook

机构信息

Department of Pulmonology & Respiratory Medicine, Faculty of Medicine, Universitas Airlangga, Surabaya 60131, Indonesia; Tuberculosis Study Group, Universitas Airlangga, Surabaya 60131, Indonesia; Dr. Soetomo General Hospital, Surabaya 60131, Indonesia.

Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Republic of Korea; Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan 47392, Republic of Korea.

出版信息

Int J Infect Dis. 2022 Apr;117:8-14. doi: 10.1016/j.ijid.2022.01.003. Epub 2022 Jan 10.

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.

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.

摘要

目的

尚未有针对印度尼西亚结核病(TB)患者群体的异烟肼(INH)群体药代动力学(PK)模型报道。因此,我们旨在建立一个群体PK模型,以便在印度尼西亚结核病患者中实施治疗药物监测(TDM)的基础上优化INH的药物治疗。

材料与方法

从印度尼西亚苏托莫综合学术医院收集INH浓度、N-乙酰转移酶2(NAT2)基因型和临床数据。使用非线性混合效应模型来建立和验证群体PK模型。

结果

本研究共纳入107例结核病患者(153份样本)。一个对体重效应采用异速缩放的单室模型很好地描述了INH的PK。NAT2乙酰化表型显著影响INH清除率。快速、中间和慢速NAT2乙酰化表型的平均清除率分别为55.9、37.8和17.7 L/h。通过直观预测检查和自抽样法对我们的模型进行了充分验证。

结论

我们以NAT2乙酰化表型作为显著协变量,建立了印度尼西亚结核病患者INH的群体PK模型。我们的贝叶斯预测模型应能优化印度尼西亚结核病患者INH的结核病治疗。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验