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一类新药创新靶点的临床试验、进展速度区分特征及快速性规则

Clinical trials, progression-speed differentiating features and swiftness rule of the innovative targets of first-in-class drugs.

作者信息

Li Ying Hong, Li Xiao Xu, Hong Jia Jun, Wang Yun Xia, Fu Jian Bo, Yang Hong, Yu Chun Yan, Li Feng Cheng, Hu Jie, Xue Wei Wei, Jiang Yu Yang, Chen Yu Zong, Zhu Feng

机构信息

Lab of Innovative Drug Research and Bioinformatics, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.

Innovative Drug Research and Bioinformatics Group, School of Pharmaceutical Sciences and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China.

出版信息

Brief Bioinform. 2020 Mar 23;21(2):649-662. doi: 10.1093/bib/bby130.

Abstract

Drugs produce their therapeutic effects by modulating specific targets, and there are 89 innovative targets of first-in-class drugs approved in 2004-17, each with information about drug clinical trial dated back to 1984. Analysis of the clinical trial timelines of these targets may reveal the trial-speed differentiating features for facilitating target assessment. Here we present a comprehensive analysis of all these 89 targets, following the earlier studies for prospective prediction of clinical success of the targets of clinical trial drugs. Our analysis confirmed the literature-reported common druggability characteristics for clinical success of these innovative targets, exposed trial-speed differentiating features associated to the on-target and off-target collateral effects in humans and further revealed a simple rule for identifying the speedy human targets through clinical trials (from the earliest phase I to the 1st drug approval within 8 years). This simple rule correctly identified 75.0% of the 28 speedy human targets and only unexpectedly misclassified 13.2% of 53 non-speedy human targets. Certain extraordinary circumstances were also discovered to likely contribute to the misclassification of some human targets by this simple rule. Investigation and knowledge of trial-speed differentiating features enable prioritized drug discovery and development.

摘要

药物通过调节特定靶点产生治疗效果,2004年至2017年批准的一类新药有89个创新靶点,每个靶点都有可追溯到1984年的药物临床试验信息。分析这些靶点的临床试验时间表可能会揭示有助于靶点评估的试验速度差异特征。在此,我们对这89个靶点进行了全面分析,遵循早期对临床试验药物靶点临床成功进行前瞻性预测的研究。我们的分析证实了文献报道的这些创新靶点临床成功的常见可成药特征,揭示了与人体中靶点和非靶点附带效应相关的试验速度差异特征,并进一步揭示了一条通过临床试验识别快速人体靶点的简单规则(从最早的I期到8年内首个药物获批)。这条简单规则正确识别了28个快速人体靶点中的75.0%,仅意外地将53个非快速人体靶点中的13.2%误分类。还发现某些特殊情况可能导致该简单规则对一些人体靶点的误分类。对试验速度差异特征的研究和了解有助于进行优先药物发现和开发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c13/7299286/9c4e66b6c63c/bby130f1.jpg

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