The Transformative Impact of Artificial Intelligence on Drug Discovery: A Technical Review
DOI:
https://doi.org/10.32628/CSEIT251112284Keywords:
Artificial Intelligence in Drug Discovery, Clinical Trial Optimization, Drug Development Automation, Pharmaceutical Research Innovation, Machine Learning ValidationAbstract
This comprehensive article examines the transformative impact of artificial intelligence on drug discovery and development processes. The article explores traditional challenges in pharmaceutical development, including extended timelines, high costs, and low success rates, which have prompted the industry's shift toward AI-driven solutions. The article investigates how AI applications have revolutionized early research stages, clinical trial management, and validation processes. Through a detailed examination of recent implementations, the article demonstrates AI's significant improvements in target identification, molecular screening, and clinical trial optimization. The article also addresses technical considerations, including data quality requirements, algorithm development challenges, and resource implications for successful AI integration in pharmaceutical research. This article provides insights into emerging trends and future directions while highlighting AI's achievements and limitations in drug discovery.
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