AI-Based Computational Methods in Early Drug Discovery and Post Market Drug Assessment: A Survey
Flora Rajaei, Cristian Minoccheri, Emily Wittrup, Richard Wilson, Brian D. Athey, Gilbert S. Omenn, Kayvan Najarian
Abstract
Over the past few years, artificial intelligence (AI) has emerged as a transformative force in drug discovery and development (DDD), revolutionizing many aspects of the process. This survey provides a comprehensive review of recent advancements in AI applications within early drug discovery and post-market drug assessment. It addresses the identification and prioritization of new therapeutic targets, prediction of drug-target interaction (DTI), design of novel drug-like molecules, and assessment of the clinical efficacy of new medications. By integrating AI technologies, pharmaceutical companies can accelerate the discovery of new treatments, enhance the precision of drug development, and bring more effective therapies to market. This shift represents a significant move towards more efficient and cost-effective methodologies in the DDD landscape.