Artificial Intelligence in Accelerating Drug Discovery and Development.

Q3 Biochemistry, Genetics and Molecular Biology
Anushree Tripathi, Krishna Misra, Richa Dhanuka, Jyoti Prakash Singh
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引用次数: 5

Abstract

Drug discovery and development are critical processes that enable the treatment of wide variety of health-related problems. These are time-consuming, tedious, complicated, and costly processes. Numerous difficulties arise throughout the entire process of drug discovery, from design to testing. Corona Virus Disease 2019 (COVID-19) has recently posed a significant threat to global public health. SARS-Cov-2 and its variants are rapidly spreading in humans due to their high transmission rate. To effectively treat COVID-19, potential drugs and vaccines must be developed quickly. The advancement of artificial intelligence has shifted the focus of drug development away from traditional methods and toward bioinformatics tools. Computer-aided drug design techniques have demonstrated tremendous utility in dealing with massive amounts of biological data and developing efficient algorithms. Artificial intelligence enables more effective approaches to complex problems associated with drug discovery and development through the use of machine learning. Artificial intelligence-based technologies improve the pharmaceutical industry's ability to discover effective drugs. This review summarizes significant challenges encountered during the drug discovery and development processes, as well as the applications of artificial intelligence-based methods to overcome those obstacles in order to provide effective solutions to health problems. This may provide additional insight into the mechanism of action, resulting in the development of vaccines and potent substitutes for repurposed drugs that can be used to treat not only COVID-19 but also other ailments.

人工智能在加速药物发现和开发中的应用。
药物发现和开发是能够治疗各种与健康有关的问题的关键过程。这些都是耗时、乏味、复杂和昂贵的过程。从设计到测试,在药物发现的整个过程中会出现许多困难。2019冠状病毒病(COVID-19)最近对全球公共卫生构成重大威胁。由于SARS-Cov-2及其变体的高传播率,它们正在人类中迅速传播。为了有效治疗COVID-19,必须迅速开发潜在的药物和疫苗。人工智能的进步使药物开发的重点从传统方法转向生物信息学工具。计算机辅助药物设计技术在处理大量生物数据和开发高效算法方面显示出巨大的效用。通过使用机器学习,人工智能能够更有效地解决与药物发现和开发相关的复杂问题。基于人工智能的技术提高了制药行业发现有效药物的能力。本综述总结了在药物发现和开发过程中遇到的重大挑战,以及基于人工智能的方法的应用,以克服这些障碍,以便为健康问题提供有效的解决方案。这可能会对作用机制提供更多的了解,从而开发出疫苗和有效的替代药物,不仅可用于治疗COVID-19,还可用于治疗其他疾病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Recent patents on biotechnology
Recent patents on biotechnology Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
2.90
自引率
0.00%
发文量
51
期刊介绍: Recent Patents on Biotechnology publishes review articles by experts on recent patents on biotechnology. A selection of important and recent patents on biotechnology is also included in the journal. The journal is essential reading for all researchers involved in all fields of biotechnology.
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