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

Variability: Analysis01:11

Variability: Analysis

137
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
137
Data Validation01:15

Data Validation

160
Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
160
Dose-Response Relationship: Potency and Efficacy01:22

Dose-Response Relationship: Potency and Efficacy

4.3K
The potency of a drug is the measure of its ability to produce a biological response and can be compared by looking at the half-maximum effective concentration or EC50 values of different drugs. A lower EC50 value indicates higher potency of the drug. In the dose–response curve of two antihypertensive drugs, candesartan and irbesartan, a significant difference is observed in their EC50 values. A lower EC50 value for candesartan indicates that it is more potent than irbesartan, as it...
4.3K
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

252
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...
252

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

Discovery of a mutation-containing circRNA in polyglutamine disease through systematic analysis of RNAs with CAG repeats.

RNA biology·2026
Same author

Comparative evaluation of dose accumulation strategies in the clinical reirradiation setting.

Physics and imaging in radiation oncology·2026
Same author

Automated Referral Prompts Reveal Lack of Equitable Access to Care in Patients With Aortic Stenosis.

Structural heart : the journal of the Heart Team·2026
Same author

Treatment planning for lung cancer reirradiation accounting for previously delivered dose.

Physics and imaging in radiation oncology·2026
Same author

Impact of Improvisation Training on Medical Students' Experience with Medical Communication in Clinical Rotations-A Single-Center Mixed-Methods Study.

Medical science educator·2026
Same author

Robust organ mapped dose: using multiple image registrations to identify deformation uncertainty in radiation dose mapping.

Physics in medicine and biology·2026
Same journal

Impact of Information Leakage in Platform Trials With Survival Endpoints on Type I Error Control.

Pharmaceutical statistics·2026
Same journal

Harmonic Fowlkes-Mallows Index for Medical Diagnostics Tests and Optimal Cut-Off Point Selection of Binary Diseases.

Pharmaceutical statistics·2026
Same journal

Early Phase Dose-Finding Designs for CAR-T Cell Therapies.

Pharmaceutical statistics·2026
Same journal

Optimizing Randomization Ratios in Clinical Trials With Survival Endpoints.

Pharmaceutical statistics·2026
Same journal

CUI-MET: A Clinical Utility Index Based Analysis and Decision Framework for Dose Optimization in Multiple-Dose, Multiple-Outcome Randomized Trials.

Pharmaceutical statistics·2026
Same journal

Will the Pharmaceutical Industry Need Statisticians in an AI World?

Pharmaceutical statistics·2026
查看所有相关文章

相关实验视频

Updated: Jun 21, 2025

Author Spotlight: Biological Standardization to Ensure Reproducibility and Harmonization in Research
04:50

Author Spotlight: Biological Standardization to Ensure Reproducibility and Harmonization in Research

Published on: August 4, 2023

1.0K

实践中的功效测试可变性估计

Hang Li1, Tomasz M Witkos2, Scott Umlauf3

  • 1Data Science & Modelling, Biopharmaceutical Development, AstraZeneca, Gaithersburg, Maryland, USA.

Pharmaceutical statistics
|July 9, 2024
PubMed
概括
此摘要是机器生成的。

这项研究探讨了生物药物强度生物试验的变异性,这对于质量评估至关重要. 它提出了一个统计算法来估计制造业的变化率和规范外率.

关键词:
在CMC的统计数据中.生物测试生物测试线性混合模型线性混合模型方法的可变性方法的可变性.强度强度强度是什么意思

更多相关视频

Viability Assays for Cells in Culture
12:03

Viability Assays for Cells in Culture

Published on: January 20, 2014

46.2K
A Small-Scale Setup for Algal Toxicity Testing of Nanomaterials and Other Difficult Substances
08:18

A Small-Scale Setup for Algal Toxicity Testing of Nanomaterials and Other Difficult Substances

Published on: October 10, 2020

5.7K

相关实验视频

Last Updated: Jun 21, 2025

Author Spotlight: Biological Standardization to Ensure Reproducibility and Harmonization in Research
04:50

Author Spotlight: Biological Standardization to Ensure Reproducibility and Harmonization in Research

Published on: August 4, 2023

1.0K
Viability Assays for Cells in Culture
12:03

Viability Assays for Cells in Culture

Published on: January 20, 2014

46.2K
A Small-Scale Setup for Algal Toxicity Testing of Nanomaterials and Other Difficult Substances
08:18

A Small-Scale Setup for Algal Toxicity Testing of Nanomaterials and Other Difficult Substances

Published on: October 10, 2020

5.7K

科学领域:

  • 生物制药品质量控制的质量控制
  • 分析化学是一种分析化学.
  • 生物技术是生物技术.

背景情况:

  • 在开发过程中对生物药物质量进行评估,实力测试至关重要.
  • 由于操作和生物因素,生物测试比物理化学方法具有更高的可变性.

研究的目的:

  • 讨论生物试验变异性来源和统计估计方法.
  • 提出一个算法来估计可报告结果的变化率和超标率.

主要方法:

  • 对生物试验可变性来源的统计分析.
  • 开发和应用一种用于估计变量的新算法.
  • 在多种测试格式的数值实验.

主要成果:

  • 确定和讨论导致生物试验变异性的关键因素.
  • 通过数值实验阐明的生物试验变异性的经验分布.
  • 算法提供了基于运行和OOS速率的变化估计.

结论:

  • 了解和统计估计生物试验变异性对于可靠的生物制造至关重要.
  • 拟议的算法有助于评估波动对产品质量和OOS率的影响.
  • 这项工作有助于生物制药行业的强有力的质量控制策略.