{"title":"药物开发和药物输送系统中的人工智能驱动创新。","authors":"Ting Zhu, Bing Liu, Ning Chen, Yuchen Liu, Zixuan Wang, Xue Tian","doi":"10.2174/0115680266373236250411060857","DOIUrl":null,"url":null,"abstract":"<p><p>As Artificial Intelligence (AI) technology rapidly advances, its application in pharmaceutical formulation design and Drug Delivery Systems (DDS) is expanding, revealing significant potential. AI technology has played a role in optimizing drug design, enhancing research and development efficiency, and improving the safety profiles of pharmaceutical products, thereby supporting the realization of personalized medicine. This article systematically examines the foundational applications and principles of AI in pharmaceutical formulation, while also evaluating its role in key areas such as drug development, manufacturing, quality control, and ADME/T (absorption, distribution, metabolism, excretion, and toxicity) prediction. In particular, AI can enhance prediction accuracy for drug solubility, stability, and bioavailability, while optimizing novel DDS through Machine Learning (ML) models, such as nanocarrier design and personalized drug release control. Furthermore, AI has been pivotal in advancing intelligent manufacturing technologies, including three-dimensional printing (3D printing) and continuous manufacturing. Finally, the article explores the opportunities and challenges presented by AI in drug development, regulation, and policymaking. Overall, AI's integration promises to revolutionize pharmaceutical development and regulatory practices.</p>","PeriodicalId":11076,"journal":{"name":"Current topics in medicinal chemistry","volume":" ","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence-Driven Innovations in Pharmaceutical Development and Drug Delivery Systems.\",\"authors\":\"Ting Zhu, Bing Liu, Ning Chen, Yuchen Liu, Zixuan Wang, Xue Tian\",\"doi\":\"10.2174/0115680266373236250411060857\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>As Artificial Intelligence (AI) technology rapidly advances, its application in pharmaceutical formulation design and Drug Delivery Systems (DDS) is expanding, revealing significant potential. AI technology has played a role in optimizing drug design, enhancing research and development efficiency, and improving the safety profiles of pharmaceutical products, thereby supporting the realization of personalized medicine. This article systematically examines the foundational applications and principles of AI in pharmaceutical formulation, while also evaluating its role in key areas such as drug development, manufacturing, quality control, and ADME/T (absorption, distribution, metabolism, excretion, and toxicity) prediction. In particular, AI can enhance prediction accuracy for drug solubility, stability, and bioavailability, while optimizing novel DDS through Machine Learning (ML) models, such as nanocarrier design and personalized drug release control. Furthermore, AI has been pivotal in advancing intelligent manufacturing technologies, including three-dimensional printing (3D printing) and continuous manufacturing. Finally, the article explores the opportunities and challenges presented by AI in drug development, regulation, and policymaking. Overall, AI's integration promises to revolutionize pharmaceutical development and regulatory practices.</p>\",\"PeriodicalId\":11076,\"journal\":{\"name\":\"Current topics in medicinal chemistry\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current topics in medicinal chemistry\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2174/0115680266373236250411060857\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CHEMISTRY, MEDICINAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current topics in medicinal chemistry","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/0115680266373236250411060857","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
Artificial Intelligence-Driven Innovations in Pharmaceutical Development and Drug Delivery Systems.
As Artificial Intelligence (AI) technology rapidly advances, its application in pharmaceutical formulation design and Drug Delivery Systems (DDS) is expanding, revealing significant potential. AI technology has played a role in optimizing drug design, enhancing research and development efficiency, and improving the safety profiles of pharmaceutical products, thereby supporting the realization of personalized medicine. This article systematically examines the foundational applications and principles of AI in pharmaceutical formulation, while also evaluating its role in key areas such as drug development, manufacturing, quality control, and ADME/T (absorption, distribution, metabolism, excretion, and toxicity) prediction. In particular, AI can enhance prediction accuracy for drug solubility, stability, and bioavailability, while optimizing novel DDS through Machine Learning (ML) models, such as nanocarrier design and personalized drug release control. Furthermore, AI has been pivotal in advancing intelligent manufacturing technologies, including three-dimensional printing (3D printing) and continuous manufacturing. Finally, the article explores the opportunities and challenges presented by AI in drug development, regulation, and policymaking. Overall, AI's integration promises to revolutionize pharmaceutical development and regulatory practices.
期刊介绍:
Current Topics in Medicinal Chemistry is a forum for the review of areas of keen and topical interest to medicinal chemists and others in the allied disciplines. Each issue is solely devoted to a specific topic, containing six to nine reviews, which provide the reader a comprehensive survey of that area. A Guest Editor who is an expert in the topic under review, will assemble each issue. The scope of Current Topics in Medicinal Chemistry will cover all areas of medicinal chemistry, including current developments in rational drug design, synthetic chemistry, bioorganic chemistry, high-throughput screening, combinatorial chemistry, compound diversity measurements, drug absorption, drug distribution, metabolism, new and emerging drug targets, natural products, pharmacogenomics, and structure-activity relationships. Medicinal chemistry is a rapidly maturing discipline. The study of how structure and function are related is absolutely essential to understanding the molecular basis of life. Current Topics in Medicinal Chemistry aims to contribute to the growth of scientific knowledge and insight, and facilitate the discovery and development of new therapeutic agents to treat debilitating human disorders. The journal is essential for every medicinal chemist who wishes to be kept informed and up-to-date with the latest and most important advances.