药物发现中数据驱动的毒性预测:现状与未来方向。

IF 6.5 2区 医学 Q1 PHARMACOLOGY & PHARMACY
Ningning Wang , Xinliang Li , Jing Xiao , Shao Liu , Dongsheng Cao
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引用次数: 0

摘要

早期毒性评估对候选药物的损耗率有着重要影响,因此在药物发现过程中发挥着至关重要的作用。近年来,信息技术的不断升级极大地推动了毒性预测的不断发展。为了概述数据驱动毒性预测的现状,我们回顾了相关研究,并从毒性预测的特点和难点、建模方法的演变以及可用的毒性预测工具三个主要方面进行了总结。针对每种方法,我们阐述了研究现状、现有挑战和可行的解决方案。最后,还提出了毒性预测的几个新方向和建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data-driven toxicity prediction in drug discovery: Current status and future directions
Early toxicity assessment plays a vital role in the drug discovery process on account of its significant influence on the attrition rate of candidates. Recently, constant upgrading of information technology has greatly promoted the continuous development of toxicity prediction. To give an overview of the current state of data-driven toxicity prediction, we reviewed relevant studies and summarized them in three main respects: the features and difficulties of toxicity prediction, the evolution of modeling approaches, and the available tools for toxicity prediction. For each part, we expound the research status, existing challenges, and feasible solutions. Finally, several new directions and suggestions for toxicity prediction are also put forward.
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来源期刊
Drug Discovery Today
Drug Discovery Today 医学-药学
CiteScore
14.80
自引率
2.70%
发文量
293
审稿时长
6 months
期刊介绍: Drug Discovery Today delivers informed and highly current reviews for the discovery community. The magazine addresses not only the rapid scientific developments in drug discovery associated technologies but also the management, commercial and regulatory issues that increasingly play a part in how R&D is planned, structured and executed. Features include comment by international experts, news and analysis of important developments, reviews of key scientific and strategic issues, overviews of recent progress in specific therapeutic areas and conference reports.
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