Jayanti Rannissa Puspita, Long Nguyen Phuoc, Phat Nguyen Ky, Cho Yong-Soon, Shin Jae-Gook
Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Korea.
Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan 47392, Korea.
Pharmaceutics. 2022 May 5;14(5):990. doi: 10.3390/pharmaceutics14050990.
Standard tuberculosis (TB) management has failed to control the growing number of drug-resistant TB cases worldwide. Therefore, innovative approaches are required to eradicate TB. Model-informed precision dosing and therapeutic drug monitoring (TDM) have become promising tools for adjusting anti-TB drug doses corresponding with individual pharmacokinetic profiles. These are crucial to improving the treatment outcome of the patients, particularly for those with complex comorbidity and a high risk of treatment failure. Despite the actual benefits of TDM at the bedside, conventional TDM encounters several hurdles related to laborious, time-consuming, and costly processes. Herein, we review the current practice of TDM and discuss the main obstacles that impede it from successful clinical implementation. Moreover, we propose a semi-automated TDM approach to further enhance precision medicine for TB management.
标准的结核病（TB）管理未能控制全球耐药结核病病例数量的不断增长。因此，需要创新方法来根除结核病。模型指导的精准给药和治疗药物监测（TDM）已成为根据个体药代动力学特征调整抗结核药物剂量的有前景的工具。这些对于改善患者的治疗结果至关重要，特别是对于那些患有复杂合并症和治疗失败风险高的患者。尽管床边TDM有实际益处，但传统TDM在费力、耗时和成本高昂的过程方面遇到了几个障碍。在此，我们回顾了TDM的当前实践，并讨论了阻碍其成功临床实施的主要障碍。此外，我们提出了一种半自动TDM方法，以进一步加强结核病管理的精准医学。
