• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

基于生理学的药代动力学(PBPK)模型在药物吸收、清除和药物-药物相互作用中的应用。

Physiologically-based Pharmacokinetic (PBPK) Modelling of Transporter Mediated Drug Absorption, Clearance and Drug-drug Interactions.

机构信息

DMPK, IVIVT, GlaxoSmithKline R&D, Stevenage, United Kingdom.

Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, United Kingdom.

出版信息

Curr Drug Metab. 2021;22(7):523-531. doi: 10.2174/1389200221999210101233340.

DOI:10.2174/1389200221999210101233340
PMID:33397250
Abstract

Membrane transporters play an important role in intestinal absorption, distribution and clearance of drugs. Additionally transporters along with enzymes regulate tissue exposures (e.g. liver, kidney and brain), which are important for safety and efficacy considerations. Early identification of transporters involved guides generation of in vitro and in vivo data needed to gain mechanistic understanding on the role of transporters in organ clearance, tissue exposures and enables development of physiological-based pharmacokinetic (PBPK) models. A lot of progress has been made in developing several in vitro assay systems and mechanistic in silico models to determine kinetic parameters for transporters, which are incorporated into PBPK models. Although, intrinsic clearance and inhibition data from in vitro systems generally tend to underpredict in vivo clearance and magnitude of drug-drug interactions (DDIs), empirical scaling factors derived from a sizable dataset are often used to offset underpredictions. PBPK models are increasing used to predict the impact of transporters on intestinal absorption, clearance, victim and perpetrator DDIs prior to first in human clinical trials. The models are often refined when clinical data is available and are used to predict pharmacokinetics in untested scenarios such as the impact of polymorphisms, ontogeny, ethnicity, disease states and DDIs with other perpetrator drugs. The aim of this review is to provide an overview of (i) regulatory requirements around transporters, (ii) in vitro systems and their limitations in predicting transporter mediated drug disposition and DDIs, (iii) PBPK modelling tactics and case studies used for internal decision making and/or for regulatory submissions.

摘要

膜转运蛋白在药物的肠道吸收、分布和清除中起着重要作用。此外,转运体与酶一起调节组织暴露(如肝脏、肾脏和大脑),这对于安全性和疗效考虑至关重要。早期识别参与的转运体有助于生成体外和体内数据,从而获得对转运体在器官清除、组织暴露中的作用的机制理解,并能够开发基于生理学的药代动力学(PBPK)模型。在开发用于确定转运体动力学参数的几种体外测定系统和机制计算模型方面已经取得了很大进展,这些模型被纳入 PBPK 模型。尽管来自体外系统的内在清除率和抑制数据通常倾向于低估体内清除率和药物相互作用(DDI)的程度,但通常使用来自大量数据集的经验缩放因子来抵消低估。在人体临床试验之前,PBPK 模型越来越多地用于预测转运体对肠道吸收、清除、受害者和肇事者 DDI 的影响。当有临床数据时,这些模型通常会得到改进,并用于预测未经验证的情况下的药代动力学,例如多态性、个体发生、种族、疾病状态和与其他肇事者药物的 DDI 的影响。本综述的目的是概述(i)转运体的监管要求,(ii)体外系统及其在预测转运体介导的药物处置和 DDI 方面的局限性,(iii)用于内部决策和/或监管提交的 PBPK 建模策略和案例研究。

相似文献

1
Physiologically-based Pharmacokinetic (PBPK) Modelling of Transporter Mediated Drug Absorption, Clearance and Drug-drug Interactions.基于生理学的药代动力学(PBPK)模型在药物吸收、清除和药物-药物相互作用中的应用。
Curr Drug Metab. 2021;22(7):523-531. doi: 10.2174/1389200221999210101233340.
2
Dealing with the complex drug-drug interactions: towards mechanistic models.应对复杂的药物相互作用:迈向机制模型。
Biopharm Drug Dispos. 2015 Mar;36(2):71-92. doi: 10.1002/bdd.1934. Epub 2015 Feb 10.
3
Prediction of pharmacokinetics and drug-drug interactions when hepatic transporters are involved.涉及肝脏转运体时的药代动力学及药物-药物相互作用预测
Clin Pharmacokinet. 2014 Aug;53(8):659-78. doi: 10.1007/s40262-014-0156-z.
4
Transporter-Enzyme Interplay: Deconvoluting Effects of Hepatic Transporters and Enzymes on Drug Disposition Using Static and Dynamic Mechanistic Models.转运体-酶相互作用:利用静态和动态机制模型解析肝脏转运体和酶对药物处置的影响
J Clin Pharmacol. 2016 Jul;56 Suppl 7:S99-S109. doi: 10.1002/jcph.695.
5
PBPK modeling of intestinal and liver enzymes and transporters in drug absorption and sequential metabolism.药物吸收和连续代谢中肠道和肝脏酶及转运体的 PBPK 建模。
Curr Drug Metab. 2010 Nov;11(9):743-61. doi: 10.2174/138920010794328931.
6
Transporter-enzyme interplay and the hepatic drug clearance: what have we learned so far?转运体-酶相互作用与肝脏药物清除率:我们目前了解到了什么?
Expert Opin Drug Metab Toxicol. 2020 May;16(5):387-401. doi: 10.1080/17425255.2020.1749595. Epub 2020 Apr 12.
7
In vitro and in vivo approaches to characterize transporter-mediated disposition in drug discovery.在药物发现中,采用体内外方法来表征转运体介导的药物处置。
Expert Opin Drug Discov. 2014 Aug;9(8):873-90. doi: 10.1517/17460441.2014.922540. Epub 2014 May 24.
8
Overcoming the shortcomings of the extended-clearance concept: a framework for developing a physiologically-based pharmacokinetic (PBPK) model to select drug candidates involving transporter-mediated clearance.克服延长清除概念的局限性:开发基于生理的药代动力学 (PBPK) 模型以选择涉及转运体介导清除的药物候选物的框架。
Expert Opin Drug Metab Toxicol. 2021 Aug;17(8):869-886. doi: 10.1080/17425255.2021.1912012. Epub 2021 Jun 15.
9
Absolute abundance and function of intestinal drug transporters: a prerequisite for fully mechanistic in vitro-in vivo extrapolation of oral drug absorption.肠内药物转运体的绝对含量和功能:口服药物吸收的完全机制体外-体内外推的前提条件。
Biopharm Drug Dispos. 2013 Jan;34(1):2-28. doi: 10.1002/bdd.1810. Epub 2012 Oct 8.
10
The Application of Physiologically Based Pharmacokinetic Modeling to Predict the Role of Drug Transporters: Scientific and Regulatory Perspectives.基于生理的药代动力学模型在预测药物转运体作用中的应用:科学与监管视角
J Clin Pharmacol. 2016 Jul;56 Suppl 7:S122-31. doi: 10.1002/jcph.740.

引用本文的文献

1
Dosage Optimization Using Physiologically Based Pharmacokinetic Modeling for Pediatric Patients with Renal Impairment: A Case Study of Meropenem.使用基于生理的药代动力学模型对肾功能不全儿科患者进行剂量优化:美罗培南的案例研究
AAPS PharmSciTech. 2025 Jan 16;26(1):38. doi: 10.1208/s12249-024-03026-y.
2
Computational approach for drug discovery against Gardnerella vaginalis in quest for safer and effective treatments for bacterial vaginosis.针对阴道加德纳菌的药物发现计算方法研究,以寻求更安全有效的细菌性阴道病治疗方法。
Sci Rep. 2024 Jul 29;14(1):17437. doi: 10.1038/s41598-024-68443-2.
3
Safety and Efficacy of Antiviral Drugs and Vaccines in Pregnant Women: Insights from Physiologically Based Pharmacokinetic Modeling and Integration of Viral Infection Dynamics.
抗病毒药物和疫苗在孕妇中的安全性与有效性:基于生理的药代动力学建模及病毒感染动力学整合的见解
Vaccines (Basel). 2024 Jul 16;12(7):782. doi: 10.3390/vaccines12070782.
4
Virus-Induced Epilepsy vs. Epilepsy Patients Acquiring Viral Infection: Unravelling the Complex Relationship for Precision Treatment.病毒诱导性癫痫与癫痫患者获得病毒感染:为精准治疗揭开复杂关系。
Int J Mol Sci. 2024 Mar 27;25(7):3730. doi: 10.3390/ijms25073730.
5
Proposing a framework to quantify the potential impact of pharmacokinetic drug-drug interactions caused by a new drug candidate by using real world data about the target patient population.提出一个框架,通过目标患者人群的真实世界数据来量化新候选药物引起的药物代谢动力学药物相互作用的潜在影响。
Clin Transl Sci. 2024 Mar;17(3):e13741. doi: 10.1111/cts.13741.
6
Emerging mechanisms of the unfolded protein response in therapeutic resistance: from chemotherapy to Immunotherapy.未折叠蛋白反应在治疗抵抗中的新兴机制:从化疗到免疫治疗。
Cell Commun Signal. 2024 Jan 31;22(1):89. doi: 10.1186/s12964-023-01438-0.
7
Prospective approaches to gene therapy computational modeling - spotlight on viral gene therapy.基因治疗计算建模的前瞻性方法——聚焦于病毒基因治疗。
J Pharmacokinet Pharmacodyn. 2024 Oct;51(5):399-416. doi: 10.1007/s10928-023-09889-1. Epub 2023 Oct 17.
8
Utility of Minimal Physiologically Based Pharmacokinetic Models for Assessing Fractional Distribution, Oral Absorption, and Series-Compartment Models of Hepatic Clearance.最小生理基于药代动力学模型在评估分数分布、口服吸收和肝脏清除的串联房室模型中的应用。
Drug Metab Dispos. 2023 Oct;51(10):1403-1418. doi: 10.1124/dmd.123.001403. Epub 2023 Jul 17.
9
Plant vs. Kidney: Evaluating Nephrotoxicity of Botanicals with the Latest Toxicological Tools.植物与肾脏:使用最新毒理学工具评估植物药的肾毒性
Curr Opin Toxicol. 2022 Dec;32. doi: 10.1016/j.cotox.2022.100371. Epub 2022 Aug 31.
10
Drug Disposition Protein Quantification in Matched Human Jejunum and Liver From Donors With Obesity.肥胖供者人空肠和肝中药物处置蛋白的定量分析。
Clin Pharmacol Ther. 2022 May;111(5):1142-1154. doi: 10.1002/cpt.2558. Epub 2022 Mar 6.