Automating Drug Discovery using Machine Learning

Author:

Abdul Raheem Ali K.12,Dhannoon Ban N.3

Affiliation:

1. College of Information Technology, University of Babylon, Hillah, Babil, Iraq

2. University of Warith Al-Anbiyaa, Kerbala,

3. Department of Computer Science, College of Science, Al-Nahrain University, Baghdad, Iraq

Abstract

Abstract: Drug discovery and development have been sped up because of the advances in computational science. In both industry and academics, artificial intelligence (AI) has been widely used. Machine learning (ML), an important component of AI, has been used in a variety of domains, including data production and analytics. One area that stands to gain significantly from this achievement of machine learning is drug discovery. The process of bringing a new drug to market is complicated and time-consuming. Traditional drug research takes a long time, costs a lot of money, and has a high failure rate. Scientists test millions of compounds, but only a small number make it to preclinical or clinical testing. It is crucial to embrace innovation, especially automated technologies, to lessen the complexity involved in drug research and avoid the high cost and lengthy process of bringing a medicine to the market. A rapidly developing field, a branch of artificial intelligence called machine learning (ML), is being used by numerous pharmaceutical businesses. Automating repetitive data processing and analysis processes can be achieved by incorporating ML methods into the drug development process. ML techniques can be used at numerous stages of the drug discovery process. In this study, we will discuss the steps of drug discovery and methods of machine learning that can be applied in these steps, as well as give an overview of each of the research works in this field.

Publisher

Bentham Science Publishers Ltd.

Subject

Drug Discovery

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An Optimization Method for Drug Design Based on Molecular Features;Lecture Notes in Computer Science;2024

2. A Novel Deep Learning Model for Drug-drug Interactions;Current Computer-Aided Drug Design;2023-11-03

3. COVID-19 Detection Based on Chest X-Rays and CT Scans Using Inception v3 Deep Learning Algorithm;2023 International Conference on Engineering, Science and Advanced Technology (ICESAT);2023-06-21

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3