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

Drug Discovery: Overview01:26

Drug Discovery: Overview

10.9K
Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
10.9K
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

5.8K
Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
5.8K

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

Bridging the Gap: Consensus-Based Considerations for AI Usefulness in Healthcare.

The American journal of bioethics : AJOB·2026
Same author

Leveraging Artificial Intelligence in Drug and Biological Product Development: An FDA and Clinical Trial Transformation Initiative Workshop Report.

NEJM AI·2025
Same author

Artificial Intelligence in Clinical and Translational Science: From Bench Insights to Bedside Impact.

Clinical and translational science·2025
Same author

Out-of-Distribution Detection as a Risk-Control Strategy for Medical Classification Machine Learning Models.

Clinical and translational science·2025
Same author

US Food and Drug Administration Approval Summary: Ribociclib With an Aromatase Inhibitor in the Adjuvant Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Stage II and III High-Risk Early Breast Cancer Treatment Setting.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology·2025
Same author

Using Quantitative Approaches to Optimize Dosages for New Combinations and Subsequent Indications for Oncology Drugs.

Clinical pharmacology and therapeutics·2025

相关实验视频

Updated: Jan 8, 2026

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
08:46

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms

Published on: December 9, 2015

11.1K

缓解有限数据挑战,以改善人工智能在罕见疾病药物开发中的整合.

Atasi Poddar1, Gabriel K Innes1, Qi Liu2

  • 1Office of Medical Policy, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.

NEJM AI
|December 12, 2025
PubMed
概括

开发用于罕见和超罕见疾病的药物面临着挑战,原因是患者人数较少和数据有限. 像人工智能,先进分析和数据共享等策略可以克服药物开发的这些障碍.

更多相关视频

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

10.1K
In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
06:41

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Published on: August 20, 2019

14.2K

相关实验视频

Last Updated: Jan 8, 2026

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
08:46

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms

Published on: December 9, 2015

11.1K
Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

10.1K
In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
06:41

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Published on: August 20, 2019

14.2K

科学领域:

  • 医学科学 医学科学 医学科学
  • 药理学 药理学是指药理学的学科.
  • 生物技术是生物技术.

背景情况:

  • 罕见疾病在美国影响不到20万人,而超罕见疾病在全球影响不到100人.
  • 针对罕见疾病的药物开发受到小,分散的患者群体,稀缺的自然史数据和疾病特征的不良表征的阻碍.

研究的目的:

  • 探索克服罕见病药物开发挑战的策略.
  • 确定解决患者数量少和数据稀缺造成的局限性的方法.

主要方法:

  • 使用人工智能和先进的分析技术.
  • 利用详细的个体级患者数据.
  • 探索合成数据生成以增强小型数据集.
  • 建立中央数据库,促进公私合作伙伴关系.

主要成果:

  • 建议的策略为罕见病研究中的数据限制提供解决方案.
  • 人工智能和先进的分析可以增强对罕见疾病的理解和药物开发.
  • 协作数据共享倡议可以创建全面的数据存储库.

结论:

  • 创新方法对于推进罕见和超罕见疾病的药物开发至关重要.
  • 通过技术和协作策略解决数据稀缺问题是改善罕见病患者治疗结果的关键.