Venlafaxine pharmacokinetics focused on drug metabolism and potential biomarkers
Venlafaxine pharmacokinetics focused on drug metabolism and potential biomarkers
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DOI：
10.1515/dmdi-2013-0053
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发表时间：
2014-09-01
期刊：
影响因子：
--
通讯作者：
Falcao, Amilcar
中科院分区：
文献类型：
--
作者：
Magalhaes, Paulo;Alves, Gilberto;Falcao, Amilcar
文拉法辛（VEN）是用于治疗选择性血清素再摄取抑制剂耐药性抑郁症的最安全、最有效的药物之一，因此它是当今最常用的抗抑郁药之一。然而，接受包括 VEN 在内的抗抑郁药物治疗的患者在药物结果方面表现出较大的个体间差异，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，过去几年人们对药物代谢细胞色素 P450 同工酶和药物转运蛋白的遗传和/或表型谱的兴趣日益浓厚，例如药物生物处置和抗抑郁反应中发现的基于药代动力学的潜在预测变异性生物标志物。其中一些关键治疗生物标志物与经典治疗药物监测的整合构成了 VEN 药物治疗个体化的一种有前景的方法，使临床医生能够更好地预测和管理药物治疗，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的临床相关来源（主要是遗传来源），并旨在识别表型和/或遗传生物标志物以优化治疗。
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.