Network-based discovery through mechanistic systems biology. Implications for applications--SMEs and drug discovery: where the action is.
Network-based discovery through mechanistic systems biology. Implications for applications--SMEs and drug discovery: where the action is.
复制标题
DOI：
10.1016/j.ddtec.2015.07.003
复制
发表时间：
2015-08-01
期刊：
影响因子：
--
通讯作者：
Benson, Neil
中科院分区：
文献类型：
--
作者：
Benson, Neil
二期耗损仍然是药物发现最重要的挑战。解决这个问题需要提高对疾病生物学复杂性的理解。从原则上讲，系统生物学解决这个问题的方法可以做到这一点。本文综述了机械系统模型在药物发现问题中的应用报道，并讨论了其附加值。尽管我们正在迈向虚拟人类，但从中学习的长度、路径和速度仍然是一个悬而未决的问题。成功将取决于投资的意愿，并充分利用在此过程中产生的洞察力。
Phase II attrition remains the most important challenge for drug discovery. Tackling the problem requires improved understanding of the complexity of disease biology. Systems biology approaches to this problem can, in principle, deliver this. This article reviews the reports of the application of mechanistic systems models to drug discovery questions and discusses the added value. Although we are on the journey to the virtual human, the length, path and rate of learning from this remain an open question. Success will be dependent on the will to invest and make the most of the insight generated along the way.