AI-based Computational Methods in Early Drug Discovery and Post Market Drug Assessment: A Survey.

IF 3.6 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS IEEE/ACM Transactions on Computational Biology and Bioinformatics Pub Date : 2024-11-06 DOI:10.1109/TCBB.2024.3492708
Flora Rajaei, Cristian Minoccheri, Emily Wittrup, Richard C Wilson, Brian D Athey, Gilbert S Omenn, Kayvan Najarian
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Abstract

Over the past few years, artificial intelligence (AI) has emerged as a transformative force in drug discovery and development (DDD), revolutionizing many aspects of the process. This survey provides a comprehensive review of recent advancements in AI applications within early drug discovery and post-market drug assessment. It addresses the identification and prioritization of new therapeutic targets, prediction of drug-target interaction (DTI), design of novel drug-like molecules, and assessment of the clinical efficacy of new medications. By integrating AI technologies, pharmaceutical companies can accelerate the discovery of new treatments, enhance the precision of drug development, and bring more effective therapies to market. This shift represents a significant move towards more efficient and cost-effective methodologies in the DDD landscape.

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基于人工智能的计算方法在早期药物发现和上市后药物评估中的应用:调查。
在过去几年中,人工智能(AI)已成为药物发现与开发(DDD)领域的一股变革性力量,彻底改变了药物发现与开发过程的许多方面。本调查全面回顾了人工智能在早期药物发现和上市后药物评估中应用的最新进展。它涉及新治疗靶点的识别和优先排序、药物-靶点相互作用(DTI)预测、新型类药物分子设计以及新药临床疗效评估。通过整合人工智能技术,制药公司可以加快新疗法的发现,提高药物开发的精准度,并将更有效的疗法推向市场。这一转变标志着 DDD 领域正朝着更高效、更具成本效益的方法迈出重要一步。
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来源期刊
CiteScore
7.50
自引率
6.70%
发文量
479
审稿时长
3 months
期刊介绍: IEEE/ACM Transactions on Computational Biology and Bioinformatics emphasizes the algorithmic, mathematical, statistical and computational methods that are central in bioinformatics and computational biology; the development and testing of effective computer programs in bioinformatics; the development of biological databases; and important biological results that are obtained from the use of these methods, programs and databases; the emerging field of Systems Biology, where many forms of data are used to create a computer-based model of a complex biological system
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