The Historical Context of Drugs and the Role of Artificial Intelligence (AI) in It: An Overview

Drug discovery has undergone a remarkable transformation over the centuries, evolving from empirical observations and natural product isolation to high-throughput screening and molecular design. This review provides a historical overview of key milestones in drug development, tracing the journey from traditional practices to modern computational techniques. Emphasizing the increasing role of Artificial Intelligence (AI), the review explores how machine learning, deep learning, and generative algorithms are revolutionizing the field of drug discovery and development. AI's ability to analyze complex datasets, predict drug-target interactions, and optimize lead compounds has accelerated the drug discovery pipeline and personalized medicine and drug repurposing efforts. While the advantages of AI include cost-effectiveness, enhanced efficiency, and expanded chemical space exploration, its limitations, such as data dependency and interpretability, are also discussed. This review aims to contextualize the evolution of drug discovery while highlighting AI's transformative potential in addressing contemporary challenges in healthcare.