AI-Powered Revolution: Transforming Drug Discovery and Development

Abstract

With its creative answers to enduring problems in drug discovery, artificial intelligence (AI) is quickly changing the field of pharmaceutical research and development. Beginning with an analysis of the shortcomings of conventional drug development paradigms and an introduction to AI's transformational potential, this review delves into the complex effects of AI. Data-driven target identification, network intelligence for therapeutic intervention, and predictive binding evaluations are some of the ways AI is helping to shed light on medication targets. With an emphasis on intelligent molecule production, ADMET property prediction, and structure-activity relationship decoding, the use of AI in engineering lead compounds is investigated. With insights into AI-enhanced preclinical investigations, streamlined clinical trial design, and the development of precision therapies through biomarker discovery, the paper also explores how AI is revolutionizing clinical translation. The paper concludes by discussing the difficulties and potential directions of AI in drug development, such as the need for openness, data accessibility and quality, ethical and regulatory issues, synergistic innovation, and the long-term effects of AI on the pharmaceutical research ecosystem.