Holbrook Joanna D, Sanseau Philippe
GlaxoSmithKline, Molecular Discovery Research, Bioinformatics Analysis, Stevenage SG1 2NY, United Kingdom.
Drug Discov Today. 2007 Oct;12(19-20):826-32. doi: 10.1016/j.drudis.2007.08.015. Epub 2007 Sep 27.
Drug discovery remains a difficult business with a very high level of attrition. Many steps in this long process use data generated from various species. One key challenge is to successfully translate the pre-clinical findings of target validation and safety studies in animal models to diverse human beings in the clinic. Advanced computational evolutionary analysis techniques combined with the increasing availability of sequence information enable the application of systematic evolutionary approaches to targets and pathways of interest to drug discovery. These analyses have the potential to increase our understanding of experimental differences observed between species.
药物研发仍然是一项困难重重且损耗率极高的工作。在这个漫长过程中的许多步骤都使用了来自不同物种的数据。一个关键挑战是要成功地将动物模型中靶点验证和安全性研究的临床前结果转化到临床中形形色色的人类身上。先进的计算进化分析技术,再加上序列信息越来越容易获取,使得系统进化方法能够应用于药物研发感兴趣的靶点和途径。这些分析有可能增进我们对物种间观察到的实验差异的理解。