Abstract

Abstract: The integration of artificial intelligence (AI) into drug discovery is revolutionizing the pharmaceutical industry by accelerating the development of novel therapeutics. AI-powered tools enable researchers to process vast datasets, identify drug candidates, and predict their efficacy and safety with unprecedented speed and accuracy. This paper explores the transformative impact of AI on drug discovery, highlighting key advancements in machine learning algorithms, deep learning, and predictive modeling. Additionally, it addresses the challenges associated with AI implementation, including data quality, regulatory hurdles, and ethical considerations. By analyzing case studies of AI-driven pharmaceutical breakthroughs, this paper underscores AI's potential to streamline drug development, reduce costs, and address unmet medical needs. The future of drug discovery is poised to shift dramatically as AI continues to advance, offering promising solutions for improving human health.