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临床试验难题:网络效应如何限制药物发现
Kishore Vasan1, Deisy Morselli Gysi1,2,3,4, Albert-László Barabási1,3,5
1Network Science Institute, Northeastern University, Boston, MA, USA.
iScience
|December 26, 2023
概括
药物发现创新是有限的,大多数临床试验专注于旧的目标. 需要新的基于网络的模型来探索新的可药性蛋白质并加速治疗.
科学领域:
- 生物医学研究的研究.
- 药理学 药理学是指药理学的学科.
- 基因组学就是基因组学.
背景情况:
- 后基因组医学为新疗法提供了潜力.
- 将基因组洞察力转化为药物发现面临着挑战.
研究的目的:
- 用临床试验数据分析药物发现的创新趋势.
- 确定基于网络的机制,限制对新药点的探索.
主要方法:
- 从40年来356,403项临床试验中提取的元数据.
- 分析试验数据以评估药物标的新性和探索范围.
- 确定了影响药物标选择的网络属性.
主要成果:
- 超过96%的试验集中在之前测试过的药物标上.
- 只有12%的人类互动组是被测试药物所准的.
- 优先附加和局部网络效应阻碍了新目标的发现.
结论:
- 目前,药物发现创新主要由传统方法主导.
- 目前的模式表明,需要170年才能准所有可药物治疗的蛋白质.
- 基于网络的定量模型可以通过促进对新目标的探索来增强药物发现.
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