AΙ-Driven Drug Repurposing: Applications and Challenges
Abstract
Drug repurposing is the process of discovering new therapeutic indications for already existing drugs. By using already approved molecules with known safety profiles, this approach reduces the time, costs, and failure rates associated with traditional drug development, accelerating the availability of new treatments to patients. Artificial Intelligence (AI) plays a crucial role in drug repurposing by exploiting various computational techniques to analyze and process big datasets of biological and medical information, predict similarities between biomolecules, and identify disease mechanisms. The purpose of this review is to explore the role of AI tools in drug repurposing and underline their applications across various medical domains, mainly in oncology, neurodegenerative disorders, and rare diseases. However, several challenges remain to be addressed. These include the need for a deeper understanding of molecular mechanisms, ethical concerns, regulatory requirements, and issues related to data quality and interpretability. Overall, AI-driven drug repurposing is an innovative and promising field that can transform medical research and drug development, covering unmet medical needs efficiently and cost-effectively.
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