Artificial Intelligence in Accelerating Drug Discovery and Development

药物发现 计算机科学 风险分析(工程) 药物开发 多样性(控制论) 数据科学 人工智能 药品 生物信息学 医学 生物 药理学
作者
Anushree Tripathi,Krishna Misra,Richa Dhanuka,Jyoti Prakash Singh
出处
期刊:Recent Patents on Biotechnology [Bentham Science]
卷期号:17 (1): 9-23 被引量:26
标识
DOI:10.2174/1872208316666220802151129
摘要

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.
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