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Recent progress in artificial intelligence and machine learning for novel diabetes mellitus medications development
1School of Pharmacy, Heilongjiang University of Chinese Medicine, Harbin, P. R. China.
Current Medical Research and Opinion
|July 31, 2024
Summary
Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing diabetes mellitus drug development. This review explores AI and ML applications across the entire drug lifecycle to improve treatments and reduce healthcare burdens.
Area of Science:
- Pharmacology and Therapeutics
- Computational Biology and Bioinformatics
- Artificial Intelligence in Medicine
Background:
- Diabetes mellitus is a complex metabolic disorder characterized by hyperglycemia, leading to severe complications and significant socio-economic burdens.
- Current novel drug development for diabetes is challenged by high costs, long timelines, and suboptimal efficacy and side effects.
- There is an urgent need for innovative therapeutic strategies to effectively manage diabetes and mitigate its widespread impact.
Purpose of the Study:
- To address the gap in comprehensive reviews on AI and ML applications in diabetes mellitus drug development.
- To evaluate the impact and potential of AI and ML technologies across the entire drug development lifecycle for diabetes.
- To synthesize current research and technological advancements to inform better diabetes management and treatment strategies.
Main Methods:
- Systematic review of current research on Artificial Intelligence (AI) and Machine Learning (ML) applications in pharmaceutical sciences.
- Analysis of AI/ML integration in drug discovery, preclinical studies, clinical trials, and post-market surveillance for diabetes medications.
- Synthesis of recent advances in AI, including data augmentation and interpretable AI, for overcoming drug discovery challenges.
Main Results:
- AI and ML have demonstrated significant acceleration in identifying therapeutic candidates for diabetes.
- These technologies optimize clinical trial designs and enhance post-approval safety monitoring, improving drug development efficiency.
- Recent AI advancements offer promising strategies to overcome inherent challenges in AI-based drug discovery for diabetes.
Conclusions:
- AI and ML integration holds transformative potential for diabetes mellitus drug development, from discovery to post-market surveillance.
- These technologies promise to accelerate the creation of more effective diabetes treatments with fewer adverse effects.
- The application of AI and ML offers hope for improved patient outcomes and reduced global healthcare burdens associated with diabetes.
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