Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

267
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
267
Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance01:07

Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance

42
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.
A recent model describes pravastatin's hepatobiliary excretion,...
42
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

74
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
74
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

91
Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
91
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

720
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.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
720
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

79
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.
79

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Cohort population analysis of sparse data: Dexamethasone pharmacokinetics in mother and fetus based on blood sampling at birth.

Journal of pharmacokinetics and pharmacodynamics·2026
Same author

Cardiovascular Disease Risk Prediction in Patients With Metabolic Dysfunction-Associated Steatohepatitis.

Diabetes, obesity & metabolism·2026
Same author

Validation and Reliability of the Spanish Internet Addiction Test-7 (IAT-7) for Adolescents.

European journal of investigation in health, psychology and education·2026
Same author

Smartphone and Social Network Addiction, Physical Activity, and Self-Esteem Among Spanish Adolescents: A Cross-Sectional Study of Associations and Gender Differences.

Psychological reports·2026
Same author

Pore-collapse in amorphous solid water: A dynamics study.

The Journal of chemical physics·2026
Same author

Physical activity, sports participation, and sustainable development in the Ibero-American region: a pilot implementation of indicators in Chile, Costa Rica, and Ecuador.

Frontiers in sports and active living·2025

相关实验视频

Updated: Jul 11, 2025

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis
07:48

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis

Published on: July 3, 2015

8.8K

药理动力学年龄结构化人口模型用于细胞贩运.

Wojciech Krzyzanski1, Robert Bauer2

  • 1Department of Pharmaceutical Sciences, University at Buffalo, 370 Pharmacy Building, Buffalo, NY 14214, USA.

Journal of pharmaceutical sciences
|November 5, 2023
PubMed
概括

这项研究开发了一种年龄结构化的细胞种群模型,以量化药物对免疫细胞贩运的影响. 该模型成功地解释了皮质类固醇管理后血细胞计数的反弹,验证了其在药量分析中的使用.

科学领域:

  • 药学指标 (Pharmacometrics) 是一个指标.
  • 免疫学 免疫学 免疫学
  • 数学建模的数学建模

背景情况:

  • 细胞贩运对免疫系统功能至关重要,涉及血液和组织之间的免疫细胞运动.
  • 已知皮质类固醇可以抑制免疫细胞的贩运,从而影响免疫反应.
  • 年龄结构模型量化免疫细胞在血液和血管外组织中的传输时间.

研究的目的:

  • 开发一个年龄结构化的细胞种群模型,以量化药物对细胞贩运的影响.
  • 将该模型应用于用于参数估计和模拟的药量计软件中.
  • 研究药物诱导的细胞贩运变化对免疫细胞动态的影响.

主要方法:

  • 采用麦肯德里克年龄结构人口模型,用于血液和血管外细胞群.
  • 模拟使用韦布尔函数的年龄依赖细胞循环.
  • 在NONMEM中实现的血度的Emax函数通过细胞贩运的内置药物影响.

主要成果:

  • 年龄结构对于解释药物管理后血细胞计数反弹 (ν > 1) 是必不可少的.
  • 模型参数估计包括ν=3.02,β=0.00863 1/h,以及IC50=7.47 ng/mL.
  • 基细胞的计算基线平均传输时间为7.2小时 (血液) 和104.9小时 (血管外组织).
关键词:
皮质类固醇 (皮质类固醇)免疫反应 (Immune Response) 是一种免疫反应.数学模型 (((s) 的使用.药理动力学/药理动力学 (PK/PD) 建模人口的药学动力学.

更多相关视频

Probing Structural and Dynamic Properties of Trafficking Subcellular Nanostructures by Spatiotemporal Fluctuation Spectroscopy
08:17

Probing Structural and Dynamic Properties of Trafficking Subcellular Nanostructures by Spatiotemporal Fluctuation Spectroscopy

Published on: August 16, 2021

1.9K
Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation
10:24

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation

Published on: September 19, 2019

6.4K

相关实验视频

Last Updated: Jul 11, 2025

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis
07:48

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis

Published on: July 3, 2015

8.8K
Probing Structural and Dynamic Properties of Trafficking Subcellular Nanostructures by Spatiotemporal Fluctuation Spectroscopy
08:17

Probing Structural and Dynamic Properties of Trafficking Subcellular Nanostructures by Spatiotemporal Fluctuation Spectroscopy

Published on: August 16, 2021

1.9K
Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation
10:24

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation

Published on: September 19, 2019

6.4K

结论:

  • 开发了一种年龄结构人口模型来描述血液和组织之间药物调节的细胞贩运.
  • 该模型成功地解释了抑制药物对细胞循环的作用.
  • 该模型解释反弹现象的能力通过使用基细胞对甲治疗的反应来验证.