Authors: Prabhu Nagrajan
Abstract: Rare diseases, affecting a small percentage of the population, present significant challenges in drug development due to limited patient numbers and scarce resources. Drug repurposing, which identifies new therapeutic uses for existing drugs, offers a promising approach to accelerate treatment availability and reduce costs. Artificial intelligence (AI), with its ability to analyze vast biomedical datasets and uncover hidden patterns, is transforming drug repurposing efforts. This paper explores how AI techniques such as machine learning, natural language processing, and network analysis are utilized to identify repurposing candidates for rare diseases. We discuss data sources, computational strategies, successful case studies, challenges in implementation, and the future outlook of AI-driven drug repurposing to enhance rare disease therapy development.
DOI: http://doi.org/10.61137/ijsret.vol.8.issue6.558
