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相关概念视频

Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance01:07

Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance

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Drug transporters are critical in drug absorption, distribution, and excretion processes. They should be included in physiological-based pharmacokinetic (PBPK) models, which help predict human drug disposition. However, predicting this is challenging during drug development, especially when liver transport is involved. However, with a realistic representation of body transport processes, an accurate model may be possible.
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Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

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Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
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Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

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Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
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Physiological Pharmacokinetic Models: Assumption with Protein Binding01:13

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Physiological models with protein binding in pharmacokinetics offer a sophisticated approach to understanding drug disposition. These models consider drug-protein interactions, enabling them to effectively predict drug concentrations in different organs and tissues. This precision aids in accurate drug dosing, providing a significant advantage over conventional models. A key process within these models is equilibration, which ensures that drug concentrations achieve a steady state within the...
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Pharmacokinetic–Pharmacodynamic Relationship: Model Components01:14

Pharmacokinetic–Pharmacodynamic Relationship: Model Components

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Pharmacokinetic-pharmacodynamic (PK–PD) modeling is essential in drug development and clinical pharmacology. It provides a quantitative framework to predict drug behavior and response over time. This approach integrates pharmacokinetics (PK), which describes the drug's absorption, distribution, metabolism, and excretion, with pharmacodynamics (PD), which characterizes the drug’s biological effects and mechanisms of action.The disposition kinetics of a drug determine its plasma...
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Pharmacokinetic Models: Comparison and Selection Criterion01:26

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Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
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相关实验视频

Updated: Mar 9, 2026

Investigating Long-Distance Transport of Perfluoroalkyl Acids in Wheat via a Split-Root Exposure Technique
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一个人类下一代PBK模型用于PFOA.

Chrysanthi Pachoulide1, Carolina Vogs2, Aude Ratier3

  • 1Wageningen University and Research, Division of Toxicology, Wageningen, Netherlands.

Environment international
|March 7, 2026
PubMed
概括

下一代生理基动力学 (NG-PBK) 模型提供了一种解决方案,用于评估和多基物质 (PFAS) 对人类健康的风险. 这项研究开发了一种新的NG-PBK模型,用于仅使用体外和体内数据的 perfluorooctanoic acid (PFOA).

关键词:
全球敏感性分析人类生物监测 人类生物监测下一代风险评估新一代风险评估perfluorooctanoic 酸 的含量是多少基于生理学的运动模型.阅读横向的阅读.

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科学领域:

  • 环境毒理学和风险评估
  • 计算机毒理学和建模
  • 人类健康风险评估评估 人类健康风险评估

背景情况:

  • 由于它们的数量庞大,结构多样化和毒性数据有限,评估对人体健康的风险是复杂的.
  • 下一代生理基动力学 (NG-PBK) 模型提供了一种机制方法来弥补数据缺口并促进风险评估.
  • 现有的模型通常依赖于动物或人类数据校准,限制了它们的机械应用.

研究的目的:

  • 开发和验证下一代基于生理的动力学 (NG-PBK) 模型,用于人类的 perfluorooctanoic acid (PFOA).
  • 仅使用 in vitro 和 in silico 数据进行模型参数化,避免使用 in vivo 观察进行校准.
  • 为了证明该模型的实用性,将其推断到数据较差的PFAS,并将其与人类生物监测 (HBM) 数据集成为下一代风险评估 (NGRA).

主要方法:

  • 开发一个NG-PBK模型,结合关键的毒动力学过程:蛋白分离,脂分离,肠肝循环,排泄和月经.
  • 模型的参数化,仅使用 in vitro 和 in silico 衍生数据.
  • 全球灵敏度分析以确定关键模型参数.

主要成果:

  • 为PFOA开发的NG-PBK模型对未结合的血分数,活性运输和组织-血分区系数高度敏感.
  • 血清度和半衰期的模型预测与人类志愿者和生物监测研究结果保持一致.
  • 该模型表现出机械稳定性,与现有验证的PFOA-PBK模型达到同等性,而无需进行体内校准.

结论:

  • 该研究成功开发了PFOA的机械NG-PBK模型,仅依赖于体外和体内数据.
  • 这个模型准确地预测了PFOA的毒动力学,并作为将其推断到其他PFAS的基础.
  • 与HBM数据的整合将增强PFAS的NGRA,通过减少对体内研究的依赖来支持3R原则.