Artificial Intelligence in Drug Discovery: Transforming the Future of Medicine

Artificial intelligence (AI) is one of the important tools in modern drug development processes, which can work through large bodies of data and build predictive models. This aids in identifying suitable drug candidates and predicting possible interactions between drugs and specific targets as well as exploratory therapeutic areas—all of which lead to a simpler and more efficient drug development cycle at minimal cost. In this review article, we examine the state of AI in drug discovery and discuss its applications where it provides support during target identification, validation stages including the drug-designing stage, as well as clinical research. This paper also discusses challenges associated with using AI in drug discovery, such as problems with the quality and interpretability of data/models or regulatory concerns. The review also considers the future of AI-driven drug discovery, with far-reaching implications for personalized medicine, and the expansion of therapeutic repertoire in recalcitrant diseases.