文拉法辛的药代动力学主要研究药物代谢和潜在的生物标志物。

Paulo Magalhães, Gilberto Alves, Adrián Llerena, Amílcar Falcão
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引用次数: 34

摘要

文拉法辛(VEN)是用于治疗选择性血清素再摄取抑制剂抵抗性抑郁症的最安全、最有效的药物之一,因此它是目前最常用的抗抑郁药之一。然而,包括VEN在内的抗抑郁药物治疗的患者在药物疗效方面表现出很大的个体差异,这可能是由于遗传和非遗传因素对药物药代动力学和/或药效学的影响。其中,在过去几年中,对药物代谢细胞色素P450同位酶和药物转运体的遗传和/或表型谱的兴趣日益增加,如药物生物处置和抗抑郁反应中发现的可变性的潜在预测药代动力学生物标志物。将这些关键的治疗性生物标志物与经典的治疗性药物监测相结合,构成了VEN药物治疗个性化的一种有希望的方式,为临床医生提供了更好地预测和管理药物治疗的能力,以最大限度地提高药物疗效。因此,本综述对VEN的药代动力学进行了广泛的讨论,特别关注代谢问题,同时没有忘记药代动力学变异性的临床相关来源(主要是遗传来源),并旨在识别用于治疗优化的表型和/或遗传生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Venlafaxine pharmacokinetics focused on drug metabolism and potential biomarkers.

Venlafaxine (VEN) is one of the safest and most effective drugs used in the treatment of selective serotonin reuptake inhibitors-resistant depression, and thereby it is nowadays one of the most commonly prescribed antidepressants. Nevertheless, patients treated with antidepressant drugs including VEN have exhibited large inter-individual variability in drug outcomes, possibly due to the influence of genetic and nongenetic factors on the drug pharmacokinetics and/or pharmacodynamics. Among them, an increased interest has emerged over the last few years on the genetic and/or phenotypic profile for drug-metabolizing cytochrome P450 isoenzymes and drug transporters such as potential predictive pharmacokinetic-based biomarkers of the variability found in drug biodisposition and antidepressant response. The integration of some of these key therapeutic biomarkers with classic therapeutic drug monitoring constitutes a promising way to individualization of VEN's pharmacotherapy, offering to clinicians the ability to better predict and manage pharmacological treatments to maximize the drug effectiveness. Thus, this review provides an extensive discussion of the pharmacokinetics of VEN focusing in particular on metabolism issues, without forgetting the clinically relevant sources of pharmacokinetics variability (mainly the genetic sources) and aiming on the identification of phenotypic and/or genetic biomarkers for therapy optimization.

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