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Data-driven toxicity prediction in drug discovery: Current status and future directions
Ningning Wang1, Xinliang Li1, Jing Xiao2
1Department of Pharmacy, Xiangya Hospital, Central South University, Changsha 410008 Hunan, PR China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008 Hunan, PR China; The Hunan Institute of Pharmacy Practice and Clinical Research, Changsha 410008 Hunan, PR China.
Abstract:
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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