Applications of Artificial Intelligence Techniques in Medical Drug Discovery and Precision Treatment

Abstract

Artificial intelligence (AI) has revolutionized various facets of medical drug discovery and precision treatment. This review paper provides a comprehensive overview of AI techniques applied in these domains, encompassing historical developments, core applications, comparative analyses, existing challenges, and future perspectives. The review begins with a historical overview of AI in medicine, charting its evolution from expert systems to deep learning. Core applications are then explored, including AI-driven drug target identification, de novo drug design, prediction of drug efficacy and toxicity, and patient stratification for precision treatment. Specific AI techniques such as machine learning, deep learning, and natural language processing are examined in the context of each application. A critical comparison of different AI approaches highlights their strengths and limitations. The review also addresses challenges in the field, such as data biases, lack of interpretability, and regulatory hurdles. Finally, future directions are discussed, emphasizing the potential of AI to transform drug discovery and personalized medicine. This review aims to serve as essential reference for researchers and practitioners in the intersection of AI and medicine, inspiring future advancements in the field.