Advances in artificial intelligence-based technologies for increasing the quality of medical products.

IF 2.5 4区 医学 Q3 PHARMACOLOGY & PHARMACY
Nidhi Srivastava, Sneha Verma, Anupama Singh, Pranki Shukla, Yashvardhan Singh, Ankit D Oza, Tanvir Kaur, Sohini Chowdhury, Monit Kapoor, Ajar Nath Yadav
{"title":"Advances in artificial intelligence-based technologies for increasing the quality of medical products.","authors":"Nidhi Srivastava, Sneha Verma, Anupama Singh, Pranki Shukla, Yashvardhan Singh, Ankit D Oza, Tanvir Kaur, Sohini Chowdhury, Monit Kapoor, Ajar Nath Yadav","doi":"10.1007/s40199-024-00548-5","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) is a technology that combines machine learning (ML) and deep learning. It has numerous usages in the domains of medicine and other sciences. Artificial intelligence can forecast the behavior of a drug's target protein and predict its desired physicochemical qualities. AI's potential to enhance healthcare services offerings formerly unheard-of opportunities for cost reserves, enhanced overall clinical and patient outcomes. The recent development of research in the biomedical field, encompassing fields such as genomics, computational medicine, AI, and algorithms for learning, has led to the demand for novel technology, a fresh workforce, and new standards of practice set the stage for the revolution in healthcare. By connecting these health statistics with cutting-edge AI technologies, precise insights into patient treatment can be obtained. Moreover, AI can aid in the search for new drugs by foretelling the target protein's two-dimensional structure. In the current review, an overview of the latest AI-based technologies and how they may be employed to reduce product development time to market and snowballing product quality, cost-effectiveness, as well as security throughout the manufacturing process is detailed.</p>","PeriodicalId":10888,"journal":{"name":"DARU Journal of Pharmaceutical Sciences","volume":"33 1","pages":"1"},"PeriodicalIF":2.5000,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11607247/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"DARU Journal of Pharmaceutical Sciences","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s40199-024-00548-5","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0

Abstract

Artificial intelligence (AI) is a technology that combines machine learning (ML) and deep learning. It has numerous usages in the domains of medicine and other sciences. Artificial intelligence can forecast the behavior of a drug's target protein and predict its desired physicochemical qualities. AI's potential to enhance healthcare services offerings formerly unheard-of opportunities for cost reserves, enhanced overall clinical and patient outcomes. The recent development of research in the biomedical field, encompassing fields such as genomics, computational medicine, AI, and algorithms for learning, has led to the demand for novel technology, a fresh workforce, and new standards of practice set the stage for the revolution in healthcare. By connecting these health statistics with cutting-edge AI technologies, precise insights into patient treatment can be obtained. Moreover, AI can aid in the search for new drugs by foretelling the target protein's two-dimensional structure. In the current review, an overview of the latest AI-based technologies and how they may be employed to reduce product development time to market and snowballing product quality, cost-effectiveness, as well as security throughout the manufacturing process is detailed.

提高医疗产品质量的人工智能技术取得进展。
人工智能(AI)是机器学习(ML)和深度学习相结合的技术。它在医学和其他科学领域有许多用途。人工智能可以预测药物靶蛋白的行为,并预测其所需的物理化学性质。人工智能有潜力增强医疗保健服务,提供前所未有的成本储备机会,提高整体临床和患者的治疗效果。生物医学领域的最新研究发展,包括基因组学、计算医学、人工智能和学习算法等领域,导致了对新技术、新劳动力和新实践标准的需求,为医疗保健革命奠定了基础。通过将这些卫生统计数据与尖端人工智能技术相结合,可以获得对患者治疗的精确见解。此外,人工智能可以通过预测目标蛋白质的二维结构来帮助寻找新药。在当前的综述中,详细介绍了最新的基于人工智能的技术,以及如何利用它们来缩短产品开发上市时间,并在整个制造过程中提高产品质量、成本效益和安全性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
DARU Journal of Pharmaceutical Sciences
DARU Journal of Pharmaceutical Sciences PHARMACOLOGY & PHARMACY-
自引率
0.00%
发文量
0
期刊介绍: DARU Journal of Pharmaceutical Sciences is a peer-reviewed journal published on behalf of Tehran University of Medical Sciences. The journal encompasses all fields of the pharmaceutical sciences and presents timely research on all areas of drug conception, design, manufacture, classification and assessment. The term DARU is derived from the Persian name meaning drug or medicine. This journal is a unique platform to improve the knowledge of researchers and scientists by publishing novel articles including basic and clinical investigations from members of the global scientific community in the forms of original articles, systematic or narrative reviews, meta-analyses, letters, and short communications.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信