AI-Driven Drug Repurposing: Developing Therapeutics Through Data and Discovery

Abstract

This paper explores the transformative role of artificial intelligence (AI) in drug repurposing, a strategy for identifying new therapeutic uses for existing drugs. By leveraging pre-existing knowledge of drugs, AI enables rapid evaluation of drug efficacy, significantly shortening the drug development timeline compared to traditional methods. AI approaches, including machine learning and deep learning, enhance the identification of suitable biological targets, predict drug-disease associations, and facilitate the analysis of complex biological data and literature. Case studies demonstrate the effectiveness of AI in rapidly repurposing drugs, such as remdesivir during the COVID-19 pandemic. However, challenges remain, including data bias, model interpretability, and ethical considerations. The future of AI-driven drug repurposing holds promise for personalized medicine and collaborative innovations, potentially revolutionizing global healthcare outcomes.