{"title":"Harnessing the power of artificial intelligence in pharmaceuticals: Current trends and future prospects","authors":"Saha Aritra , Chauhan Baghel Shikha , Singh Indu","doi":"10.1016/j.ipha.2024.12.001","DOIUrl":null,"url":null,"abstract":"<div><div>Introduction of artificial intelligence (AI) technology in the field of pharmaceutical industry has been driven to discovery and development of drugs, also personalized medicine. In this article The review investigates systematic trends facing AI-powered transformation. AI has improved efficiency by reducing the drug development time, costs and success rates due to machine learning (ML), deep learning (DL) and natural language processing (NLP). The literature search was conducted systematically, using core scientific databases to source data-mining research studies on predictive modelling, virtual screening, and automation in AI applications. Findings here underscore the critical role that AI plays in precision medicine, as well as process optimization in manufacture, but ethical issues and privacy of data and regulations add significantly to hurdles. The study confirms that AI presents unique opportunities for developing personalized healthcare and answering global health challenges, nonetheless its adoption involves overcoming ethical and regulatory issues beautiful collaboration and agreeing to industry wide standards. The next-generation products bring hope for low-cost, patient-centric solutions indicating pharmaceutical landscape phases of the paradigm.</div></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"3 3","pages":"Pages 181-192"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligent Pharmacy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949866X24001217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction of artificial intelligence (AI) technology in the field of pharmaceutical industry has been driven to discovery and development of drugs, also personalized medicine. In this article The review investigates systematic trends facing AI-powered transformation. AI has improved efficiency by reducing the drug development time, costs and success rates due to machine learning (ML), deep learning (DL) and natural language processing (NLP). The literature search was conducted systematically, using core scientific databases to source data-mining research studies on predictive modelling, virtual screening, and automation in AI applications. Findings here underscore the critical role that AI plays in precision medicine, as well as process optimization in manufacture, but ethical issues and privacy of data and regulations add significantly to hurdles. The study confirms that AI presents unique opportunities for developing personalized healthcare and answering global health challenges, nonetheless its adoption involves overcoming ethical and regulatory issues beautiful collaboration and agreeing to industry wide standards. The next-generation products bring hope for low-cost, patient-centric solutions indicating pharmaceutical landscape phases of the paradigm.