翻译信息学驱动神经退行性疾病的药物重新定位
Xin Zheng1, Jing Chen2, Yuxin Zhang1
1Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Current neuropharmacology
|February 12, 2025
概括
药物重新定位利用人工智能和大数据,为治疗神经退行性疾病的现有药物找到新的用途. 这种方法为患者提供了更快,更具成本效益的治疗选择.
科学领域:
- 神经科学是一个神经科学.
- 药理学 药理学是指药理学的学科.
- 计算生物学 计算生物学
- 翻译信息学 翻译信息学
背景情况:
- 神经退行性疾病是越来越多的公共卫生问题,因为增加寿命.
- 目前的治疗方法只能提供症状缓解,这凸显了新型治疗干预措施的必要性.
- 现有的药物对许多神经退行性疾病缺乏有效性,需要创新的药物发现方法.
研究的目的:
- 通过翻译信息学,审查神经退行性疾病的药物重新定位策略.
- 系统化药物重新定位的数据源和计算模型.
- 确定当前和未来的计算模型和数据库,用于神经退行性疾病的药物发现.
主要方法:
- 系统化药物重新定位数据库和在线平台.
- 基于药物 - 药物,药物 - 目标和药物 - 疾病相互作用的分类计算模型 (例如机器学习,深度学习,基于网络的方法).
- 突出了与神经退行性疾病研究相关的计算模型和数据库.
主要成果:
- 确定并组织用于药物重新定位的关键数据资源.
- 分类了各种适用于药物重新定位的计算模型.
- 展示了目前在神经退行性疾病研究中的人工智能驱动方法.
结论:
- 由人工智能和大数据驱动的药物重新定位是开发复杂神经退行性疾病治疗方法的有希望的策略.
- 这种数据驱动的方法可以加速发现快速且具有成本效益的治疗方案.
- 翻译信息学为推进神经退行性疾病研究中的药物重新定位提供了一个强大的框架.
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