School of Pharmacy, Heilongjiang University of Chinese Medicine, Harbin, P. R. China.
Curr Med Res Opin. 2024 Sep;40(9):1483-1493. doi: 10.1080/03007995.2024.2387187. Epub 2024 Aug 8.
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.
糖尿病源于胰岛素抵抗或胰岛素分泌不足，是一种复杂的疾病，可导致长期高血糖和严重并发症。患者会承受严重的后果，如肾脏疾病、视力损害、心血管疾病和易感染，导致身体严重不适，并给社会经济带来巨大负担。这种情况已经发展成为日益严重的健康危机。迫切需要开发具有更好疗效和更少不良反应的新疗法来满足临床需求。然而，新药物的开发成本高、耗时且常常伴有副作用和疗效不佳，这是一个主要的挑战。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有前途的治疗候选物的识别速度，优化了试验设计，并增强了上市后安全性监测。最近在 AI 方面的进展，包括数据增强、可解释 AI 和将 AI 与传统实验方法集成，为克服基于 AI 的药物发现所固有的挑战提供了有前途的策略。尽管取得了这些进展，但在全面综述糖尿病药物开发各个阶段的 AI 和 ML 应用方面仍存在显著差距。本综述旨在通过评估 AI 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结果和技术进步，有效控制糖尿病并减轻其深远的社会和经济影响。AI 和 ML 的整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保健负担带来希望。
