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计算机药物重定位:从大规模转录组数据到治疗学。

In silico drug repositioning: from large-scale transcriptome data to therapeutics.

机构信息

Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, 08826, Republic of Korea.

College of Pharmacy, Seoul National University, Seoul, 08826, Republic of Korea.

出版信息

Arch Pharm Res. 2019 Oct;42(10):879-889. doi: 10.1007/s12272-019-01176-3. Epub 2019 Sep 3.

Abstract

Drug repositioning is an attractive alternative to conventional drug development when new beneficial effects of old drugs are clinically validated because pharmacokinetic and safety profiles are generally already available. Since ~ 30% of drugs newly approved by the US food and drug administration (FDA) are developed through drug repositioning, identifying novel usage for existing drugs is an emerging strategy for developing disease treatments. With advances in next-generation sequencing technologies, available transcriptome data related to diseases have expanded rapidly. Harnessing these resources enables a better understanding of disease mechanisms and drug mode of action (MOA), and moves toward personalized pharmacotherapy. In this review, we briefly outline publicly available large-scale transcriptome databases and tools for drug repositioning. We also highlight recent approaches leading to the discovery of novel drug targets, drug response biomarkers, drug indications, and drug MOA.

摘要

药物重定位是一种有吸引力的替代传统药物开发的方法,当旧药物的新的有益效果在临床上得到验证时,因为药代动力学和安全性概况通常已经可用。由于美国食品和药物管理局 (FDA) 批准的新药约有 30%是通过药物重定位开发的,因此为现有药物确定新的用途是开发疾病治疗方法的一种新兴策略。随着下一代测序技术的进步,与疾病相关的可用转录组数据迅速增加。利用这些资源可以更好地了解疾病机制和药物作用模式 (MOA),并朝着个性化药物治疗的方向发展。在这篇综述中,我们简要概述了可公开获得的大规模转录组数据库和药物重定位工具。我们还强调了最近发现新的药物靶点、药物反应生物标志物、药物适应症和药物作用模式的方法。

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