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

244
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...
244
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

54
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
54
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

66
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...
66
Nonlinear Pharmacokinetics: Overview01:19

Nonlinear Pharmacokinetics: Overview

330
Nonlinear or dose-dependent pharmacokinetics is a phenomenon that occurs when the pharmacokinetic parameters of certain drugs deviate from linear pharmacokinetics at higher doses. These drugs do not follow the expected first-order kinetics, where the rate of drug elimination is directly proportional to the drug concentration. Instead, they exhibit a nonlinear relationship, which can be attributed to several factors.
Nonlinearity can arise due to the saturation of plasma protein-binding or...
330
Drug Dosage Regimen: Overview01:15

Drug Dosage Regimen: Overview

3.5K
A drug dosage regimen describes the specific instructions and schedule for administering a drug to a patient. It considers factors such as drug dosage, frequency, route of administration, and duration of treatment. Designing an appropriate dosage regimen for a patient aims to achieve a target drug concentration at the site of action.
Typically, the starting dose and dosing interval are guided by the manufacturer's recommendations based on clinical trials conducted during and after drug...
3.5K
Dosage Regimen: Fixed Dose01:01

Dosage Regimen: Fixed Dose

1.9K
Fixed-dose regimens are a common approach to administer drugs to achieve and maintain desired levels of the drug in the body. In this dosing strategy, a specific amount of medication is given at regular intervals, often multiple times a day, to ensure a consistent drug concentration in the bloodstream.
Fixed-dose regimens can be used for various routes of administration, including intravenous (IV) injections and oral medications. For IV administration, a predetermined amount of the drug is...
1.9K

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

LI-RADS v2018 versus KLCA-NCC v2022: comparison of probability-based HCC categories.

European radiology·2026
Same author

Additional Dose Reduction Potential of Vendor-Agnostic Deep Learning Model: A Phantom Study.

Journal of the Korean Society of Radiology·2026
Same author

Protective Effectiveness of Sars-Cov-2 Infection Risk Among Hybrid, Vaccine, and Infection-induced Immunity Against the Omicron Variant, K-Serosmart.

Open forum infectious diseases·2026
Same author

Multicentre prospective trial of abbreviated MRI using gadoxetic acid versus CT for detection of late recurrent HCC (AMRICT): study protocol.

BMJ open·2026
Same author

Improving prediction of ypT0-1N0 response in rectal cancer: the added value of gross tumor type to magnetic resonance tumor regression grade after chemoradiotherapy in a retrospective cohort study.

Annals of surgical treatment and research·2026
Same author

ESPLSM: An Efficient and Interpretable Mediation Analysis Framework Using Sparse Envelopes.

Statistics in medicine·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 17, 2025

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

15.7K

一个基于自适应高斯过程回归的个性化剂量查找算法.

Yeonhee Park1, Won Chang2

  • 1Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, USA.

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

这项研究引入了针对药物开发的个性化剂量查找算法. 它为个别患者确定最佳的药物剂量,提高治疗疗效,减少试验失败.

关键词:
第一个/第二个阶段.确定剂量的方法.最好的生物剂量是最佳的.精准医学是一门精准医学.

更多相关视频

Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform
07:57

Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform

Published on: March 24, 2022

2.8K
Stepwise Dosing Protocol for Increased Throughput in Label-Free Impedance-Based GPCR Assays
06:13

Stepwise Dosing Protocol for Increased Throughput in Label-Free Impedance-Based GPCR Assays

Published on: February 21, 2020

6.5K

相关实验视频

Last Updated: Jun 17, 2025

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

15.7K
Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform
07:57

Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform

Published on: March 24, 2022

2.8K
Stepwise Dosing Protocol for Increased Throughput in Label-Free Impedance-Based GPCR Assays
06:13

Stepwise Dosing Protocol for Increased Throughput in Label-Free Impedance-Based GPCR Assays

Published on: February 21, 2020

6.5K

科学领域:

  • 临床试验 临床试验
  • 药理学 药理学是指药理学的学科.
  • 生物统计学 生物统计学

背景情况:

  • 剂量检测研究对于药物开发至关重要,旨在确定最佳剂量,同时管理耐受性.
  • 患者异质性需要个性化方法,超越临床试验中统一反应的假设.

研究的目的:

  • 为药物开发提出一种新的,两阶段的个性化剂量查找算法.
  • 通过考虑患者特异性反应和生物标志物来优化个性化的生物剂量.

主要方法:

  • 第1阶段:广泛招募患者,并将毒性/疗效结果与剂量和生物标志物的回归模型相匹配.
  • 第二阶段:将试验人群限制在已识别的敏感患者中,并应用个性化剂量分配算法.

主要成果:

  • 拟议的设计有效地将试验人群与对治疗敏感的个体进行丰富.
  • 与现有设计相比,模拟显示出更高的性能,最大限度地减少故障并最大限度地选择正确的剂量.

结论:

  • 个性化剂量查找算法通过量身定制药物剂量以满足个体患者的个人资料来提高精准医学.
  • 这种方法提高了临床试验的效率和成功率,重点关注患者特异性的疗效和耐受性.