Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Department of Pharmacy, Uppsala University, Uppsala, Sweden.
Clin Pharmacokinet. 2021 Jun;60(6):685-710. doi: 10.1007/s40262-021-00997-0. Epub 2021 Mar 6.
Tuberculosis (TB) is still the number one cause of death due to an infectious disease. Pharmacokinetics and pharmacodynamics of anti-TB drugs are key in the optimization of TB treatment and help to prevent slow response to treatment, acquired drug resistance, and adverse drug effects. The aim of this review was to provide an update on the pharmacokinetics and pharmacodynamics of anti-TB drugs and to show how population pharmacokinetics and Bayesian dose adjustment can be used to optimize treatment. We cover aspects on preclinical, clinical, and population pharmacokinetics of different drugs used for drug-susceptible TB and multidrug-resistant TB. Moreover, we include available data to support therapeutic drug monitoring of these drugs and known pharmacokinetic and pharmacodynamic targets that can be used for optimization of therapy. We have identified a wide range of population pharmacokinetic models for first- and second-line drugs used for TB, which included models built on NONMEM, Pmetrics, ADAPT, MWPharm, Monolix, Phoenix, and NPEM2 software. The first population models were built for isoniazid and rifampicin; however, in recent years, more data have emerged for both new anti-TB drugs, but also for defining targets of older anti-TB drugs. Since the introduction of therapeutic drug monitoring for TB over 3 decades ago, further development of therapeutic drug monitoring in TB next steps will again depend on academic and clinical initiatives. We recommend close collaboration between researchers and the World Health Organization to provide important guideline updates regarding therapeutic drug monitoring and pharmacokinetics/pharmacodynamics.
结核病（TB）仍然是传染病导致死亡的头号原因。抗结核药物的药代动力学和药效学是优化结核病治疗的关键，有助于预防治疗反应缓慢、获得性耐药和药物不良反应。本综述的目的是提供抗结核药物药代动力学和药效学的最新信息，并展示群体药代动力学和贝叶斯剂量调整如何用于优化治疗。我们涵盖了不同用于药物敏感结核病和耐多药结核病的药物的临床前、临床和群体药代动力学方面。此外，我们还包括了支持这些药物治疗药物监测的可用数据以及可用于优化治疗的已知药代动力学和药效学目标。我们已经确定了广泛用于结核病的一线和二线药物的群体药代动力学模型，这些模型包括基于 NONMEM、Pmetrics、ADAPT、MWPharm、Monolix、Phoenix 和 NPEM2 软件构建的模型。第一个群体模型是针对异烟肼和利福平构建的；然而，近年来，无论是新的抗结核药物，还是旧的抗结核药物的目标，都有更多的数据出现。自 30 多年前引入结核病治疗药物监测以来，结核病治疗药物监测的进一步发展将再次取决于学术和临床的主动行动。我们建议研究人员与世界卫生组织密切合作，就治疗药物监测和药代动力学/药效学提供重要的指南更新。
