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耐多药结核病患者利奈唑胺的模型引导精准给药

Model-Informed Precision Dosing of Linezolid in Patients with Drug-Resistant Tuberculosis.

作者信息

Mockeliunas Laurynas, Keutzer Lina, Sturkenboom Marieke G G, Bolhuis Mathieu S, Hulskotte Lotte M G, Akkerman Onno W, Simonsson Ulrika S H

机构信息

Department of Pharmaceutical Biosciences, Uppsala University, 75124 Uppsala, Sweden.

Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands.

出版信息

Pharmaceutics. 2022 Mar 30;14(4):753. doi: 10.3390/pharmaceutics14040753.

Abstract

Linezolid is an efficacious medication for the treatment of drug-resistant tuberculosis but has been associated with serious safety issues that can result in treatment interruption. The objectives of this study were thus to build a population pharmacokinetic model and to use the developed model to establish a model-informed precision dosing (MIPD) algorithm enabling safe and efficacious dosing in patients with multidrug- and extensively drug-resistant tuberculosis. Routine hospital therapeutic drug monitoring data, collected from 70 tuberculosis patients receiving linezolid, was used for model development. Efficacy and safety targets for MIPD were the ratio of unbound area under the concentration versus time curve between 0 and 24 h over minimal inhibitory concentration (AUC/MIC) above 119 and unbound plasma trough concentration (C) below 1.38 mg/L, respectively. Model building was performed in NONMEM 7.4.3. The final population pharmacokinetic model consisted of a one-compartment model with transit absorption and concentration- and time-dependent auto-inhibition of elimination. A flat dose of 600 mg once daily was appropriate in 67.2% of the simulated patients from an efficacy and safety perspective. Using the here developed MIPD algorithm, the proportion of patients reaching the efficacy and safety target increased to 81.5% and 88.2% using information from two and three pharmacokinetic sampling occasions, respectively. This work proposes an MIPD approach for linezolid and suggests using three sampling occasions to derive an individualized dose that results in adequate efficacy and fewer safety concerns compared to flat dosing.

摘要

利奈唑胺是治疗耐多药结核病的一种有效药物,但它与一些严重的安全问题相关,可能导致治疗中断。因此,本研究的目的是建立一个群体药代动力学模型,并使用所建立的模型来建立一个模型指导的精准给药(MIPD)算法,以实现对耐多药和广泛耐药结核病患者的安全有效给药。从70例接受利奈唑胺治疗的结核病患者收集的常规医院治疗药物监测数据用于模型开发。MIPD的疗效和安全性目标分别是0至24小时浓度-时间曲线下的非结合面积与最低抑菌浓度(AUC/MIC)之比高于119,以及非结合血浆谷浓度(C)低于1.38mg/L。模型构建在NONMEM 7.4.3中进行。最终的群体药代动力学模型由一个具有转运吸收以及浓度和时间依赖性自抑制消除的单室模型组成。从疗效和安全性角度来看,67.2%的模拟患者每天一次600mg的固定剂量是合适的。使用此处开发的MIPD算法,分别利用两次和三次药代动力学采样时机的信息,达到疗效和安全性目标的患者比例分别增加到81.5%和88.2%。这项工作提出了一种针对利奈唑胺的MIPD方法,并建议使用三次采样时机来得出个体化剂量,与固定剂量相比,该剂量能产生足够的疗效且安全性问题更少。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26f5/9032906/5f4f9a3a8789/pharmaceutics-14-00753-g001.jpg

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