Recent progress in artificial intelligence and machine learning for novel diabetes mellitus medications development.
Qi GuoBo FuYuan TianShujun XuXin MengPublished in: Current medical research and opinion (2024)
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.
Keyphrases
- artificial intelligence
- machine learning
- big data
- drug discovery
- deep learning
- healthcare
- clinical trial
- glycemic control
- public health
- insulin resistance
- mental health
- end stage renal disease
- type diabetes
- ejection fraction
- chronic kidney disease
- physical activity
- newly diagnosed
- adipose tissue
- early onset
- stem cells
- randomized controlled trial
- climate change
- prognostic factors
- health information
- electronic health record
- skeletal muscle
- metabolic syndrome
- patient reported outcomes
- weight loss
- polycystic ovary syndrome
- bone marrow
- human health
- drug administration