Jove
Visualize
联系我们

相关概念视频

Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

4.9K
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...
4.9K
Targeted Cancer Therapies02:57

Targeted Cancer Therapies

7.6K
The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against...
7.6K
Tumor Immunotherapy01:27

Tumor Immunotherapy

524
Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.
524
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

720
Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
720
Treatment Resistant Cancers02:56

Treatment Resistant Cancers

3.3K
Cancer is the second leading cause of death in the United States. A cancer cell is genetically unstable and hence can mutate faster. They can also modify their microenvironment and escape immune surveillance. The difficulties in treating cancer are further compounded by the emergence of rapid resistance to anticancer drugs. The most common ways to attain resistance in cancer cells include alteration in drug transport and metabolism, modification of drug target, elevated DNA damage response, or...
3.3K

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

Comprehensive mapping of identical sequences across human proteins emphasizes the widespread issue of shared epitopes in self-antigens.

NAR genomics and bioinformatics·2026
Same author

Rethinking EPO: A Paradigm Shift in Oncology?

Cancers·2025
Same author

Dihydropyrimidine Dehydrogenase-Guided Dosing of 5-Fluorouracil: Prioritizing Precision Over Dose Reduction.

JCO precision oncology·2025
Same author

PROTACs and Glues: Striking Perspectives for Engineering Cancer Therapy À La Carte.

Pharmaceuticals (Basel, Switzerland)·2025
Same author

De-Escalating Anticancer Treatment: Watch Your Step.

Cancers·2025
Same author

Long-Term Adverse Events Following Early Breast Cancer Treatment with a Focus on the <i>BRCA</i>-Mutated Population.

Cancers·2025
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

相关实验视频

Updated: Jul 2, 2025

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments
07:46

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Published on: April 30, 2021

4.7K

人工智能和抗癌药物开发-保持冷静

Caroline Bailleux1, Jocelyn Gal2, Emmanuel Chamorey2

  • 1Centre Antoine Lacassagne, Oncology Departement Unit, University Côte d'Azur, 06000 Nice, France.

Pharmaceutics
|February 24, 2024
PubMed
概括
此摘要是机器生成的。

人工智能 (AI) 正通过预测药物的毒性和疗效来改变瘤药物开发. 人工智能驱动的in silico临床试验有望减少试验时间和成本,彻底改变癌症研究.

关键词:
人工智能的人工智能是人工智能.新药的发现新药的发现瘤学 在瘤学方面.这是一种serendipity.

更多相关视频

A Flow Cytometry-Based Cell Surface Protein Binding Assay for Assessing Selectivity and Specificity of an Anticancer Aptamer
10:46

A Flow Cytometry-Based Cell Surface Protein Binding Assay for Assessing Selectivity and Specificity of an Anticancer Aptamer

Published on: September 13, 2022

3.6K
Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo
09:19

Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo

Published on: February 6, 2015

8.7K

相关实验视频

Last Updated: Jul 2, 2025

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments
07:46

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Published on: April 30, 2021

4.7K
A Flow Cytometry-Based Cell Surface Protein Binding Assay for Assessing Selectivity and Specificity of an Anticancer Aptamer
10:46

A Flow Cytometry-Based Cell Surface Protein Binding Assay for Assessing Selectivity and Specificity of an Anticancer Aptamer

Published on: September 13, 2022

3.6K
Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo
09:19

Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo

Published on: February 6, 2015

8.7K

科学领域:

  • 在瘤学瘤学.
  • 计算化学计算化学
  • 生物信息学是一种生物信息学.

背景情况:

  • 人工智能 (AI) 越来越多地被整合到医疗保健中,特别是在瘤学中.
  • 人工智能能够使用计算机设计的分子结构来预测药物毒性和疗效.

研究的目的:

  • 突出AI在瘤学药物开发中的潜力.
  • 强调基于人工智能的临床试验的重要性.

主要方法:

  • 利用人工智能预测基于分子结构的药物毒性和疗效.
  • 探索AI在瘤学临床试验中的应用.

主要成果:

  • 人工智能为预测药物特性提供了新的方法,有可能简化开发.
  • 基于人工智能的in silico试验正在出现,预计将减少持续时间和成本.

结论:

  • 人工智能为瘤学药物开发提供了一个新的范式.
  • 卫生当局应该将人工智能视为未来瘤学临床研究的基本要素.