Predictions of Bedaquiline Central Nervous System Exposure in Patients with Tuberculosis Meningitis Using Physiologically based Pharmacokinetic Modeling.

IF 4.6 2区 医学 Q1 PHARMACOLOGY & PHARMACY Clinical Pharmacokinetics Pub Date : 2024-05-01 Epub Date: 2024-03-26 DOI:10.1007/s40262-024-01363-6
Krina Mehta, Pavel Balazki, Piet H van der Graaf, Tingjie Guo, J G Coen van Hasselt
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Abstract

Background and objective: The use of bedaquiline as a treatment option for drug-resistant tuberculosis meningitis (TBM) is of interest to address the increased prevalence of resistance to first-line antibiotics. To this end, we describe a whole-body physiologically based pharmacokinetic (PBPK) model for bedaquiline to predict central nervous system (CNS) exposure.

Methods: A whole-body PBPK model was developed for bedaquiline and its metabolite, M2. The model included compartments for brain and cerebrospinal fluid (CSF). Model predictions were evaluated by comparison to plasma PK time profiles following different dosing regimens and sparse CSF concentrations data from patients. Simulations were then conducted to compare CNS and lung exposures to plasma exposure at clinically relevant dosing schedules.

Results: The model appropriately described the observed plasma and CSF bedaquiline and M2 concentrations from patients with pulmonary tuberculosis (TB). The model predicted a high impact of tissue binding on target site drug concentrations in CNS. Predicted unbound exposures within brain interstitial exposures were comparable with unbound vascular plasma and unbound lung exposures. However, unbound brain intracellular exposures were predicted to be 7% of unbound vascular plasma and unbound lung intracellular exposures.

Conclusions: The whole-body PBPK model for bedaquiline and M2 predicted unbound concentrations in brain to be significantly lower than the unbound concentrations in the lung at clinically relevant doses. Our findings suggest that bedaquiline may result in relatively inferior efficacy against drug-resistant TBM when compared with efficacy against drug-resistant pulmonary TB.

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利用生理学药代动力学模型预测结核性脑膜炎患者的贝达喹啉中枢神经系统暴露量
背景和目的:使用贝达喹啉作为治疗耐药结核性脑膜炎(TBM)的一种选择,对于解决一线抗生素耐药性日益普遍的问题很有意义。为此,我们介绍了贝达喹啉的全身生理学药代动力学(PBPK)模型,以预测中枢神经系统(CNS)的暴露量:方法:我们为贝达喹啉及其代谢物 M2 建立了一个全身 PBPK 模型。该模型包括脑区和脑脊液区。通过与不同给药方案后的血浆 PK 时间曲线和患者稀少的 CSF 浓度数据进行比较,对模型预测进行了评估。然后进行了模拟,将中枢神经系统和肺部的暴露量与临床相关给药方案下的血浆暴露量进行了比较:结果:该模型恰当地描述了肺结核(TB)患者血浆和脑脊液中的贝达喹啉和 M2 浓度。该模型预测组织结合对中枢神经系统靶点药物浓度的影响很大。预测的脑间质内非结合暴露与非结合血管血浆和非结合肺部暴露相当。然而,根据预测,大脑细胞内的非结合暴露量是非结合血管血浆和非结合肺细胞内暴露量的 7%:结论:贝达喹啉和 M2 的全身 PBPK 模型预测,在临床相关剂量下,脑内的非结合浓度明显低于肺内的非结合浓度。我们的研究结果表明,与对耐药肺结核的疗效相比,贝达喹啉对耐药肺结核的疗效可能相对较差。
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来源期刊
CiteScore
8.80
自引率
4.40%
发文量
86
审稿时长
6-12 weeks
期刊介绍: Clinical Pharmacokinetics promotes the continuing development of clinical pharmacokinetics and pharmacodynamics for the improvement of drug therapy, and for furthering postgraduate education in clinical pharmacology and therapeutics. Pharmacokinetics, the study of drug disposition in the body, is an integral part of drug development and rational use. Knowledge and application of pharmacokinetic principles leads to accelerated drug development, cost effective drug use and a reduced frequency of adverse effects and drug interactions.
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