AI-Driven Drug Discovery and Repurposing for Neurodegenerative Disorders
Bancha Yingngam · 2025
The escalating prevalence of neurodegenerative disorders poses a significant public health challenge. Traditional methods of drug discovery and repurposing are often labor intensive, costly, and time consuming. This chapter aims to provide comprehensive insights into the innovative role of artificial intelligence (AI) in the domain of drug discovery and repurposing for neurodegenerative conditions. This chapter begins with an overview of neurodegenerative disorders, highlighting the urgent need for more effective therapeutic strategies. It then explores the foundations of AI and machine learning (ML) technologies. This exploration includes an examination of how these technologies are revolutionizing drug discovery processes, such as data collection, drug target identification, molecular docking, and in silico screening. Special attention has been given to AI-driven drug repurposing. This section details the algorithms, data sources, and case studies that exemplify its potential. The applications of AI across various neurodegenerative diseases are highlighted, providing a comprehensive view of its current and potential impacts. The discussion also addresses current challenges, including concerns about data privacy, ethical considerations, and computational limitations. Finally, the chapter concludes by outlining future directions in this rapidly evolving field. Interdisciplinary efforts and supportive policies are needed to harness the full potential of AI in healthcare. In summary, this chapter illustrates the role of AI in enhancing drug discovery and repurposing for the treatment of neurodegenerative disorders. This highlights how advancements in AI algorithms could enable more precise treatments, emphasizing the need for interdisciplinary collaboration and responsible use in leveraging AI as a key asset in combating these diseases.