The Recent Advances in the Approach of Artificial Intelligencetowards Medicine Discovery

Artificial intelligence (AI) has recently emerged as a transformative force in the field of medicine, playing a pivotal role in advancing drug discovery. AI offers groundbreaking opportunities for improving accuracy, efficiency, and innovation in this domain. With its integration into drug development processes, AI has the potential to revolutionize how new treatments are discovered and designed. Over recent years, the use of AI techniques in drug discovery has significantly expanded. Tools like combinatorial QSAR and QSPR models, virtual screening, and de novo drug design are gaining traction for their ability to analyze and predict complex molecular interactions. These advancements not only streamline research processes but also enhance precision in identifying promising drug candidates.This review aims to provide a comprehensive overview of AI-driven drug discovery and its various applications. It also sheds light on the limitations of traditional drug design methods and identifies key gaps that AI can address. Additionally, we discuss current challenges, such as ethical concerns and limited access to quality data, and propose potential strategies to overcome these obstacles. By exploring the transformative potential of AI in this field, we hope to foster a deeper understanding of its capabilities and inspire further innovation in drug discovery processes briefly outlined in this article.