{"title":"人工智能和机器学习在新型糖尿病药物开发方面的最新进展。","authors":"Qi Guo, Bo Fu, Yuan Tian, Shujun Xu, Xin Meng","doi":"10.1080/03007995.2024.2387187","DOIUrl":null,"url":null,"abstract":"<p><p>Diabetes mellitus, stemming from either insulin resistance or inadequate insulin secretion, represents a complex ailment that results in prolonged hyperglycemia and severe complications. Patients endure severe ramifications such as kidney disease, vision impairment, cardiovascular disorders, and susceptibility to infections, leading to significant physical suffering and imposing substantial socio-economic burdens. This condition has evolved into an increasingly severe health crisis. There is an urgent need to develop new treatments with improved efficacy and fewer adverse effects to meet clinical demands. However, novel drug development is costly, time-consuming, and often associated with side effects and suboptimal efficacy, making it a major challenge. Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized drug development across its comprehensive lifecycle, spanning drug discovery, preclinical studies, clinical trials, and post-market surveillance. These technologies have significantly accelerated the identification of promising therapeutic candidates, optimized trial designs, and enhanced post-approval safety monitoring. Recent advances in AI, including data augmentation, interpretable AI, and integration of AI with traditional experimental methods, offer promising strategies for overcoming the challenges inherent in AI-based drug discovery. Despite these advancements, there exists a notable gap in comprehensive reviews detailing AI and ML applications throughout the entirety of developing medications for diabetes mellitus. This review aims to fill this gap by evaluating the impact and potential of AI and ML technologies at various stages of diabetes mellitus drug development. It does that by synthesizing current research findings and technological advances so as to effectively control diabetes mellitus and mitigate its far-reaching social and economic impacts. The integration of AI and ML promises to revolutionize diabetes mellitus treatment strategies, offering hope for improved patient outcomes and reduced healthcare burdens worldwide.</p>","PeriodicalId":10814,"journal":{"name":"Current Medical Research and Opinion","volume":" ","pages":"1483-1493"},"PeriodicalIF":2.4000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Recent progress in artificial intelligence and machine learning for novel diabetes mellitus medications development.\",\"authors\":\"Qi Guo, Bo Fu, Yuan Tian, Shujun Xu, Xin Meng\",\"doi\":\"10.1080/03007995.2024.2387187\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Diabetes mellitus, stemming from either insulin resistance or inadequate insulin secretion, represents a complex ailment that results in prolonged hyperglycemia and severe complications. Patients endure severe ramifications such as kidney disease, vision impairment, cardiovascular disorders, and susceptibility to infections, leading to significant physical suffering and imposing substantial socio-economic burdens. This condition has evolved into an increasingly severe health crisis. There is an urgent need to develop new treatments with improved efficacy and fewer adverse effects to meet clinical demands. However, novel drug development is costly, time-consuming, and often associated with side effects and suboptimal efficacy, making it a major challenge. Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized drug development across its comprehensive lifecycle, spanning drug discovery, preclinical studies, clinical trials, and post-market surveillance. These technologies have significantly accelerated the identification of promising therapeutic candidates, optimized trial designs, and enhanced post-approval safety monitoring. Recent advances in AI, including data augmentation, interpretable AI, and integration of AI with traditional experimental methods, offer promising strategies for overcoming the challenges inherent in AI-based drug discovery. Despite these advancements, there exists a notable gap in comprehensive reviews detailing AI and ML applications throughout the entirety of developing medications for diabetes mellitus. This review aims to fill this gap by evaluating the impact and potential of AI and ML technologies at various stages of diabetes mellitus drug development. It does that by synthesizing current research findings and technological advances so as to effectively control diabetes mellitus and mitigate its far-reaching social and economic impacts. The integration of AI and ML promises to revolutionize diabetes mellitus treatment strategies, offering hope for improved patient outcomes and reduced healthcare burdens worldwide.</p>\",\"PeriodicalId\":10814,\"journal\":{\"name\":\"Current Medical Research and Opinion\",\"volume\":\" \",\"pages\":\"1483-1493\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Medical Research and Opinion\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/03007995.2024.2387187\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/8/8 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Medical Research and Opinion","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/03007995.2024.2387187","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/8 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
摘要
由胰岛素抵抗或胰岛素分泌不足引起的糖尿病是一种复杂的疾病,会导致长期高血糖和严重的并发症。患者承受着严重的后果,如肾脏疾病、视力损害、心血管疾病和易受感染等,给患者带来巨大的身体痛苦和沉重的社会经济负担。这种疾病已演变成日益严重的健康危机。目前迫切需要开发疗效更好、不良反应更少的新疗法,以满足临床需求。然而,新药开发成本高、耗时长,而且往往伴有副作用和疗效不佳,因此是一项重大挑战。人工智能(AI)和机器学习(ML)已经彻底改变了药物开发的整个生命周期,包括药物发现、临床前研究、临床试验和上市后监测。这些技术大大加快了发现有潜力的候选疗法、优化试验设计和加强批准后安全监测的速度。人工智能的最新进展,包括数据增强、可解释的人工智能以及人工智能与传统实验方法的整合,为克服基于人工智能的药物发现所固有的挑战提供了前景广阔的战略。尽管取得了这些进步,但在糖尿病药物开发的整个过程中,详细介绍人工智能和 ML 应用的全面综述还存在明显差距。本综述旨在通过评估人工智能和 ML 技术在糖尿病药物开发各个阶段的影响和潜力来填补这一空白。通过综合当前的研究成果和技术进步,从而有效控制糖尿病并减轻其深远的社会和经济影响。人工智能和人工智能的结合有望彻底改变糖尿病治疗策略,为改善患者预后和减轻全球医疗负担带来希望。
Recent progress in artificial intelligence and machine learning for novel diabetes mellitus medications development.
Diabetes mellitus, stemming from either insulin resistance or inadequate insulin secretion, represents a complex ailment that results in prolonged hyperglycemia and severe complications. Patients endure severe ramifications such as kidney disease, vision impairment, cardiovascular disorders, and susceptibility to infections, leading to significant physical suffering and imposing substantial socio-economic burdens. This condition has evolved into an increasingly severe health crisis. There is an urgent need to develop new treatments with improved efficacy and fewer adverse effects to meet clinical demands. However, novel drug development is costly, time-consuming, and often associated with side effects and suboptimal efficacy, making it a major challenge. Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized drug development across its comprehensive lifecycle, spanning drug discovery, preclinical studies, clinical trials, and post-market surveillance. These technologies have significantly accelerated the identification of promising therapeutic candidates, optimized trial designs, and enhanced post-approval safety monitoring. Recent advances in AI, including data augmentation, interpretable AI, and integration of AI with traditional experimental methods, offer promising strategies for overcoming the challenges inherent in AI-based drug discovery. Despite these advancements, there exists a notable gap in comprehensive reviews detailing AI and ML applications throughout the entirety of developing medications for diabetes mellitus. This review aims to fill this gap by evaluating the impact and potential of AI and ML technologies at various stages of diabetes mellitus drug development. It does that by synthesizing current research findings and technological advances so as to effectively control diabetes mellitus and mitigate its far-reaching social and economic impacts. The integration of AI and ML promises to revolutionize diabetes mellitus treatment strategies, offering hope for improved patient outcomes and reduced healthcare burdens worldwide.
期刊介绍:
Current Medical Research and Opinion is a MEDLINE-indexed, peer-reviewed, international journal for the rapid publication of original research on new and existing drugs and therapies, Phase II-IV studies, and post-marketing investigations. Equivalence, safety and efficacy/effectiveness studies are especially encouraged. Preclinical, Phase I, pharmacoeconomic, outcomes and quality of life studies may also be considered if there is clear clinical relevance