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早期药物发现与上市后药物评估中基于人工智能的计算方法:一项综述。

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

作者信息

Rajaei Flora, Minoccheri Cristian, Wittrup Emily, Wilson Richard C, Athey Brian D, Omenn Gilbert S, Najarian Kayvan

出版信息

IEEE Trans Comput Biol Bioinform. 2025 Jan-Feb;22(1):97-115. doi: 10.1109/TCBB.2024.3492708.

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.

摘要

在过去几年中,人工智能(AI)已成为药物发现与开发(DDD)领域的变革力量,彻底改变了这一过程的许多方面。本综述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的最新进展。它涉及新治疗靶点的识别与优先级确定、药物-靶点相互作用(DTI)预测、新型类药物分子设计以及新药物临床疗效评估。通过整合人工智能技术,制药公司可以加速新疗法的发现,提高药物开发的精准度,并将更有效的疗法推向市场。这一转变标志着在DDD领域朝着更高效、更具成本效益的方法迈出了重要一步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b0e/12395280/51661e0fa53f/nihms-2054936-f0001.jpg

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