Population Pharmacokinetic Model-Based Optimization of Linezolid Dosing in Hematooncological Patients With Suspected or Proven Gram-Positive Sepsis

IF 2.8 3区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL
Alžběta Zavřelová, Sara Merdita, Pavel Žák, Jakub Radocha, Benjamin Víšek, Miriam Lánská, Jana Maláková, Pavel Michálek, Ondřej Slanař, Martin Šíma
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Abstract

The objective of this study was to develop a population pharmacokinetic model for linezolid in hematooncological patients with sepsis, and to propose dosing optimization based on pharmacokinetic covariates that would lead to improved achievement of the PK/PD target. Therapeutic drug monitoring data from hematooncological patients treated with linezolid for suspected or proven sepsis were analyzed. A pharmacokinetic population model for linezolid was constructed using a nonlinear mixed-effects modeling approach. Monte Carlo simulations were then used to compare various dosing regimens in terms of PK/PD target attainment. A total of 197 linezolid serum concentrations obtained from 22 patients were included in the analysis. Patients' age was found to be the most predictive covariate for linezolid pharmacokinetics. In a patient with a median age of 59 years, the volume of distribution and clearance of linezolid were 46.2 L and 12.1 L/h, respectively. During the first 4 days of therapy, linezolid clearance decreased by 33%. The probability of PK/PD target attainment increased through the individualization of the dose according to the patient's age, administration of a loading dose, and administration of linezolid via continuous infusion. For this scenario, an easy-to-use nomogram was designed.

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基于人群药代动力学模型的利奈唑胺在疑似或证实革兰氏阳性败血症的血液肿瘤患者中的剂量优化
本研究的目的是建立利奈唑胺在血液学脓毒症患者中的群体药代动力学模型,并根据药代动力学协变量提出优化给药剂量的建议,从而提高PK/PD指标的实现。对疑似或已证实接受利奈唑胺治疗的血液病患者的治疗药物监测数据进行分析。采用非线性混合效应建模方法建立了利奈唑胺的药代动力学种群模型。然后使用蒙特卡罗模拟来比较不同给药方案在PK/PD目标实现方面的差异。从22例患者中获得的197个利奈唑胺血清浓度被纳入分析。发现患者年龄是利奈唑胺药代动力学最具预测性的协变量。患者中位年龄为59岁,利奈唑胺的分布容积和清除率分别为46.2 L和12.1 L/h。在治疗的前4天,利奈唑胺清除率下降了33%。根据患者的年龄对剂量进行个体化、给予负荷剂量、通过持续输注给予利奈唑胺,增加了达到PK/PD目标的可能性。对于这个场景,设计了一个易于使用的nomogram。
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来源期刊
Cts-Clinical and Translational Science
Cts-Clinical and Translational Science 医学-医学:研究与实验
CiteScore
6.70
自引率
2.60%
发文量
234
审稿时长
6-12 weeks
期刊介绍: Clinical and Translational Science (CTS), an official journal of the American Society for Clinical Pharmacology and Therapeutics, highlights original translational medicine research that helps bridge laboratory discoveries with the diagnosis and treatment of human disease. Translational medicine is a multi-faceted discipline with a focus on translational therapeutics. In a broad sense, translational medicine bridges across the discovery, development, regulation, and utilization spectrum. Research may appear as Full Articles, Brief Reports, Commentaries, Phase Forwards (clinical trials), Reviews, or Tutorials. CTS also includes invited didactic content that covers the connections between clinical pharmacology and translational medicine. Best-in-class methodologies and best practices are also welcomed as Tutorials. These additional features provide context for research articles and facilitate understanding for a wide array of individuals interested in clinical and translational science. CTS welcomes high quality, scientifically sound, original manuscripts focused on clinical pharmacology and translational science, including animal, in vitro, in silico, and clinical studies supporting the breadth of drug discovery, development, regulation and clinical use of both traditional drugs and innovative modalities.
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