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

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

71
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...
71
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

43
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
43
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

134
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
134
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

74
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.
74
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

445
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
445
Dose-Response Relationship: Overview01:03

Dose-Response Relationship: Overview

3.2K
Agonists can bind with and activate receptors, resulting in the formation of drug-receptor complexes. Once formed, these complexes catalyze many biochemical processes at the cellular level and subsequently induce a pharmacologic response. The degree of response is directly proportional to the fraction of activated receptors, which in turn, depends on the concentration of the drug at the receptor site as well as the sensitivity of the receptor. An increase in the administered dose contributes to...
3.2K

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

Real-world management patterns and outcomes in normal-tension glaucoma.

Indian journal of ophthalmology·2026
Same author

A Bayesian survival treed hazards model using latent Gaussian processes.

Biometrics·2024
Same author

Two-Stage Metropolis-Hastings for Tall Data.

Journal of classification·2018
Same author

On the Reproducibility of Psychological Science.

Journal of the American Statistical Association·2018
Same author

Selected Insecticide Delivery Devices for Management of Horn Flies (Haematobia irritans) (Diptera: Muscidae) on Beef Cattle.

Journal of medical entomology·2017
Same author

Adaptive designs for comparative effectiveness research trials.

Clinical research and regulatory affairs·2015

相关实验视频

Updated: Jul 8, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K

贝叶斯模型是对纵向剂量反应模型的平均值.

Richard D Payne1, Pallavi Ray1, Mitchell A Thomann2

  • 1Global Statistical Sciences, Eli Lilly & Company, Indianapolis, IN, USA.

Journal of biopharmaceutical statistics
|December 18, 2023
PubMed
概括

这项研究引入了灵活的贝叶斯纵向剂量反应模型,以改善药物开发. 这种新方法提高了试验的效率,并准确地模拟了复杂的非单调的剂量反应概况.

科学领域:

  • 制药指标 (Pharmacometrics) 是一个指标.
  • 生物统计学 生物统计学
  • 药物开发 药物开发

背景情况:

  • 在药物开发中,剂量证明是具有挑战性的.
  • 传统的剂量反应模型依赖于潜在不充分的参数假设.
  • 纵向剂量反应建模引入了额外的假设带来的进一步复杂性.

研究的目的:

  • 在贝叶斯模型平均化框架内提出灵活的纵向剂量反应模型.
  • 引入一个新的纵向模型,用于非单调的剂量反应概况.
  • 提高临床试验的运行特性,同时保持先验灵活性.

主要方法:

  • 开发了一类纵向剂量反应模型.
  • 将这些模型集成到贝叶斯模型平均范式中.
  • 专门为非单调的纵向配置文件提出了一个新模型.

主要成果:

  • 提出的贝叶斯方法改善了试验的运行特性.
  • 新模型有效地捕捉了非单调的纵向剂量反应概况.
  • 案例研究和模拟证明了该方法的好处和权衡.

结论:

关键词:
贝叶斯模型的平均值是贝叶斯的模型.临床试验是指临床试验中的临床试验.剂量响应剂量响应.选择剂量选择剂量选择纵向建模 纵向建模 纵向建模

更多相关视频

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.7K
Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation
10:33

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

Published on: September 4, 2017

15.8K

相关实验视频

Last Updated: Jul 8, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.7K
Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation
10:33

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

Published on: September 4, 2017

15.8K
  • 灵活的贝叶斯纵向剂量反应模型比传统方法提供了改进.
  • 拟议的模型提高了药物开发中的剂量证明.
  • 对于非单调配置文件的新型模型为复杂的数据提供了更大的适应性.