Applications of AI in Drug Discovery

Abstract

This study conducts a critical analysis of the state of artificial intelligence uses for drug discovery, highlighting important obstacles, unrealized potential, and tactical routes for successful adoption. The chapter emphasizes the noteworthy advancements in target identification, compound screening, and molecule design using AI-driven algorithms. It also covers the ethical ramifications that arise from the combination of AI and drug discovery, as well as the accessibility of AI models and regulatory issues. The significance of interdisciplinary collaborations, advances in computational power, and the creation of strong validation frameworks are emphasized as key strategies to address these problems. This study sheds light on the complex environment of AI in drug discovery by offering a thorough summary of the difficulties encountered, the opportunities that arise, and the strategic frameworks that are necessary to fully utilize AI's potential to transform the pharmaceutical sector.