探索NCATS内部生物医学数据以基于证据的药物重定位
Fang Liu1, Andrew Patt2, Chloe Chen1
1Division of Rare Diseases Research Innovation, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Bethesda, MD.
bioRxiv : the preprint server for biology
|August 7, 2023
概括
药物再利用利用生物医学数据用于新的药物用途. 研究人员结合了21世纪毒理学 (Tox21) 和生物医学数据翻译器 (翻译器) 的数据来识别潜在的候选药物,产生了129个化学.
科学领域:
- 生物医学信息学 生物医学信息学
- 药物发现 药物发现 药物发现
- 翻译科学 翻译科学
背景情况:
- 药物再利用为现有药物确定新的治疗指示.
- 从历史上看,药物重新定位是偶然的,现在从大规模的生物医学数据中获益.
- 系统性,数据驱动的方法提高了药物候选者的识别.
研究的目的:
- 为了证明NCATS生成的数据对药物重新用途的有用性.
- 整合来自21世纪毒理学 (Tox21) 和生物医学数据翻译 (翻译) 程序的数据.
- 通过数据分析识别新型药物重用候选药物.
主要方法:
- 利用Tox21的生物试验选数据进行化学聚类.
- 从翻译器挖掘的科学证据丰富化学集群.
- 采用数据驱动的方法来发现生物机制和潜在的药物使用.
主要成果:
- 产生了129个不同的化学集群.
- 确定了三个化学集群进行深入调查,作为药物重定向候选人.
- 通过结合Tox21和翻译器数据,展示了一种协同方法.
结论:
- 整合Tox21和Translator数据为药物重用提供了一个强大的框架.
- 这一数据驱动的战略促进了对现有化合物的新疗法应用的系统识别.
- 进一步的案例研究详细说明了这种方法的实际应用.
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