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多因素药代动力学相互作用:揭示精准药物治疗中的复杂性。

Multi-factorial pharmacokinetic interactions: unraveling complexities in precision drug therapy.

机构信息

Department of Pharmaceutical Sciences, Washington State University, Spokane, WA, USA.

出版信息

Expert Opin Drug Metab Toxicol. 2021 Apr;17(4):397-412. doi: 10.1080/17425255.2021.1867105. Epub 2021 Jan 20.

Abstract

Precision drug therapy requires accounting for pertinent factors in pharmacokinetic (PK) inter-individual variability (., pharmacogenetics, diseases, polypharmacy, and natural product use) that can cause sub-therapeutic or adverse effects. Although each of these individual factors can alter victim drug PK, multi-factorial interactions can cause additive, synergistic, or opposing effects. Determining the magnitude and direction of these complex multi-factorial effects requires understanding the rate-limiting redundant and/or sequential PK processes for each drug. Perturbations in drug-metabolizing enzymes and/or transporters are integral to single- and multi-factorial PK interactions. Examples of single factor PK interactions presented include gene-drug (pharmacogenetic), disease-drug, drug-drug, and natural product-drug interactions. Examples of multi-factorial PK interactions presented include drug-gene-drug, natural product-gene-drug, gene-gene-drug, disease-natural product-drug, and disease-gene-drug interactions. Clear interpretation of multi-factorial interactions can be complicated by study design, complexity in victim drug PK, and incomplete mechanistic understanding of victim drug PK. Incorporation of complex multi-factorial PK interactions into precision drug therapy requires advances in clinical decision tools, intentional PK study designs, drug-metabolizing enzyme and transporter fractional contribution determinations, systems and computational approaches (., physiologically-based pharmacokinetic modeling), and PK phenotyping of progressive diseases.

摘要

精准药物治疗需要考虑药代动力学(PK)个体间变异性中的相关因素(例如,药物遗传学、疾病、多药治疗和天然产物的使用),这些因素可能导致治疗效果不佳或不良反应。尽管这些个体因素中的每一个都可以改变药物的 PK,但多因素相互作用可能会导致加性、协同或相反的影响。确定这些复杂多因素影响的程度和方向需要了解每种药物的限速、冗余和/或顺序 PK 过程。药物代谢酶和/或转运体的干扰是单因素和多因素 PK 相互作用的重要组成部分。呈现的单因素 PK 相互作用的示例包括基因-药物(药物遗传学)、疾病-药物、药物-药物和天然产物-药物相互作用。呈现的多因素 PK 相互作用的示例包括药物-基因-药物、天然产物-基因-药物、基因-基因-药物、疾病-天然产物-药物和疾病-基因-药物相互作用。由于研究设计、受药物影响的 PK 的复杂性以及对受药物影响的 PK 的不完全机制理解,多因素相互作用的明确解释可能会变得复杂。将复杂的多因素 PK 相互作用纳入精准药物治疗需要在临床决策工具、有目的的 PK 研究设计、药物代谢酶和转运体的分数贡献测定、系统和计算方法(例如,基于生理学的药代动力学建模)以及进行进展性疾病的 PK 表型分析方面取得进展。

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