{"title":"Advances in artificial intelligence-envisioned technologies for protein and nucleic acid research","authors":"Amol D. Gholap , Abdelwahab Omri","doi":"10.1016/j.drudis.2025.104362","DOIUrl":null,"url":null,"abstract":"<div><div>Artificial intelligence (AI) and machine learning (ML) have revolutionized pharmaceutical research, particularly in protein and nucleic acid studies. This review summarizes the current status of AI and ML applications in the pharmaceutical sector, focusing on innovative tools, web servers, and databases. This paper highlights how these technologies address key challenges in drug development including high costs, lengthy timelines, and the complexity of biological systems. Furthermore, the potential of AI in personalized medicine, cancer drug response prediction, and biomarker identification is discussed. The integration of AI and ML in pharmaceutical research promises to accelerate drug discovery, reduce development costs, and ultimately lead to more effective and personalized therapeutic strategies.</div></div>","PeriodicalId":301,"journal":{"name":"Drug Discovery Today","volume":"30 5","pages":"Article 104362"},"PeriodicalIF":6.5000,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Drug Discovery Today","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1359644625000753","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) and machine learning (ML) have revolutionized pharmaceutical research, particularly in protein and nucleic acid studies. This review summarizes the current status of AI and ML applications in the pharmaceutical sector, focusing on innovative tools, web servers, and databases. This paper highlights how these technologies address key challenges in drug development including high costs, lengthy timelines, and the complexity of biological systems. Furthermore, the potential of AI in personalized medicine, cancer drug response prediction, and biomarker identification is discussed. The integration of AI and ML in pharmaceutical research promises to accelerate drug discovery, reduce development costs, and ultimately lead to more effective and personalized therapeutic strategies.
期刊介绍:
Drug Discovery Today delivers informed and highly current reviews for the discovery community. The magazine addresses not only the rapid scientific developments in drug discovery associated technologies but also the management, commercial and regulatory issues that increasingly play a part in how R&D is planned, structured and executed.
Features include comment by international experts, news and analysis of important developments, reviews of key scientific and strategic issues, overviews of recent progress in specific therapeutic areas and conference reports.