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

Targets for Drug Action: Overview01:26

Targets for Drug Action: Overview

Drugs target macromolecules to modify ongoing cellular processes. Primary drug targets include receptors, ion channels, transporters, and enzymes.
Receptors are either membrane-spanning or intracellular proteins, which upon binding a ligand, get activated and transmit the signal downstream to elicit a response. Drugs bind receptors, either mimicking the action of endogenous ligands or blocking the receptor activity to bring about a modified response. Nearly 35% of approved drugs target the G...
Therapeutic Drug Monitoring: Overview and Classification01:16

Therapeutic Drug Monitoring: Overview and Classification

Therapeutic Drug Monitoring (TDM) is a clinical practice that measures specific drug levels in a patient's blood at designated intervals to ensure the drug concentration stays within a therapeutic range. This monitoring is crucial for optimizing individual dosage regimens, enhancing therapeutic efficacy, and minimizing drug-related toxicity. TDM is vital for drugs with narrow therapeutic windows, significant variability in pharmacokinetics, and a clear correlation between plasma levels and...
Pharmacogenetics of Drug Targets: β₂-Adrenergic Receptors, Apo E, Thymidylate Synthase01:11

Pharmacogenetics of Drug Targets: β₂-Adrenergic Receptors, Apo E, Thymidylate Synthase

Genetic polymorphisms in drug targets have emerged as critical determinants of interindividual variability in drug response and toxicity. Pharmacogenomic investigations increasingly focus on identifying these variations to personalize and optimize therapeutic interventions. A drug target may be a receptor, enzyme, or signaling protein involved in pharmacologic responses or disease-related pathways. While early pharmacogenetic studies focused primarily on drug metabolism, current research...
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
Pharmacodynamic Models: Direct Effect Model and Indirect Response Model01:29

Pharmacodynamic Models: Direct Effect Model and Indirect Response Model

Pharmacodynamic models are essential tools in understanding the relationship between drug concentrations and their effects on biological systems. By characterizing the dynamics of drug action, these models guide dose selection, optimize therapeutic efficacy, and inform the development of new drugs. Two major classes of pharmacodynamic models include direct effect and indirect response models.Direct Effect ModelsDirect effect models describe the immediate relationship between drug concentration...
Modified-Release Drug Delivery Systems: Site-Targeted01:24

Modified-Release Drug Delivery Systems: Site-Targeted

Site-targeted drug delivery systems enhance therapeutic efficacy while minimizing systemic toxicity and treatment costs. Unlike conventional methods, these systems ensure precise drug delivery, improving bioavailability and reducing side effects. Targeted drug delivery is classified into three levels. First-order targeting directs drugs to the capillary beds of specific organs or tissues. Second-order targets specific cell types, such as tumor cells, using receptor-mediated interactions.

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

Implementing generative pretrained transformer models for text recognition tasks in safety data sheets.

Annals of work exposures and health·2025
Same author

Improved Translational Relevance of In Vitro Fibrosis Models by Integrating IOX2-Mediated Hypoxia-Mimicking Pathways.

Biomedicines·2025
Same author

A 360° Approach to Personalize Lifestyle Treatment in Primary Care for People With Type 2 Diabetes: Feasibility Study.

JMIR formative research·2024
Same author

Integrating text mining with network models for successful target identification: <i>in vitro</i> validation in MASH-induced liver fibrosis.

Frontiers in pharmacology·2024
Same author

360° Diagnostic Tool to Personalize Lifestyle Advice in Primary Care for People With Type 2 Diabetes: Development and Usability Study.

JMIR formative research·2023
Same author

Development of the gut microbiota in early life: The impact of cystic fibrosis and antibiotic treatment.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society·2020

相关实验视频

Updated: May 11, 2026

Diagonal Method to Measure Synergy Among Any Number of Drugs
12:08

Diagonal Method to Measure Synergy Among Any Number of Drugs

Published on: June 21, 2018

18.4K

药物标评估:使用基于BERT的多级分类模型对标调制和相关健康影响进行分类.

Jennifer Venhorst1, Gino Kalkman1

  • 1Biomedical and Digital Health, The Netherlands Organization for Applied Scientific Research (TNO), Utrecht 3584 CB, The Netherlands.

Bioinformatics advances
|March 20, 2025
PubMed
概括

大型语言模型从文献中系统地分析药物向健康影响. 这种人工智能方法通过提供有效性和安全性的机制性见解来加速药物发现,优于手工方法.

科学领域:

  • 生物医学信息学 生物医学信息学
  • 计算生物学 计算生物学
  • 药物发现 药物发现 药物发现

背景情况:

  • 药物标选择对于成功的药物开发至关重要.
  • 手动风险/收益分析耗时且容易产生偏见.
  • 大型语言模型 (LLM) 为文学策划提供了一个系统和高效的替代方案.

研究的目的:

  • 开发和评估基于BERT的LLMs来分类药物标与健康影响的关系.
  • 提供对目标调制对健康和疾病影响的机制性见解.
  • 创建一个人工智能辅助的工具,用于有效的药物标识别和评估.

主要方法:

  • 开发了BERT模型,用于PubMed索引关系的多层次分类.
  • 基于因果关系,目标调制和健康影响方向的分类关系.
  • 已验证的模型性能,F1得分从0.86到0.92.9不等.

主要成果:

  • 取得了竞争性表现,F1得分为0.86-0.92.2.
  • 通过案例研究证明了适用性 (ADAM33,OSM).
  • 开发的管道是第一个提供这些关系的详细分类的管道.

更多相关视频

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.4K
Network Pharmacology Prediction and Experimental Validation of Trichosanthes-Fritillaria thunbergii Action Mechanism Against Lung Adenocarcinoma
13:18

Network Pharmacology Prediction and Experimental Validation of Trichosanthes-Fritillaria thunbergii Action Mechanism Against Lung Adenocarcinoma

Published on: March 3, 2023

1.2K

相关实验视频

Last Updated: May 11, 2026

Diagonal Method to Measure Synergy Among Any Number of Drugs
12:08

Diagonal Method to Measure Synergy Among Any Number of Drugs

Published on: June 21, 2018

18.4K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.4K
Network Pharmacology Prediction and Experimental Validation of Trichosanthes-Fritillaria thunbergii Action Mechanism Against Lung Adenocarcinoma
13:18

Network Pharmacology Prediction and Experimental Validation of Trichosanthes-Fritillaria thunbergii Action Mechanism Against Lung Adenocarcinoma

Published on: March 3, 2023

1.2K

结论:

  • 该LLMs提供了对药物目标健康影响的机制性见解.
  • 这种人工智能驱动的方法提高了药物标识别和评估效率.
  • 目标Tri平台为人工智能辅助的药物发现提供了一个新的资源.