Artificial Intelligence in Drug Discovery: A Review

Artificial Intelligence (AI) has emerged as a transformative technology in pharmaceutical research and drug discovery. Traditional drug discovery is a lengthy, expensive, and complex process that often requires more than 10 years and billions of dollars to bring a new drug to market. AI techniques, including machine learning (ML), deep learning (DL), natural language processing (NLP), and neural networks, have significantly accelerated various stages of drug discovery. AI assists in target identification, lead optimization, virtual screening, drug repurposing, toxicity prediction, and clinical trial design. By analyzing large datasets rapidly and accurately, AI reduces research costs, shortens development timelines, and improves success rates. This review discusses the role of AI in modern drug discovery, its applications, advantages, limitations, and future prospects in pharmaceutical sciences.