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Updated: Jun 30, 2026

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
A Narrative Review of Artificial Intelligence for Drug Repurposing: Lessons From COVID-19 and Oncology (2020-2025)
Alaba Bukola Ogungbite1, Malusi Sibiya1
1Department of Computer Science, University of South Africa, Florida, South Africa.
Abstract:
Drug repurposing presents a cost-effective and time-efficient strategy to identify new therapeutic applications for existing drugs. Recent advances in artificial intelligence, including machine learning, deep learning, knowledge graphs, and natural language processing, have revolutionized this field by enabling automated discovery of drug-disease associations. This review examines the role of artificial intelligence in drug repurposing, drawing insights from two critical case areas: Coronavirus disease 2019 and oncology. We explore current trends, methodological frameworks, and technological innovations in artificial intelligence-driven drug repurposing, as well as challenges and emerging future directions. The findings of this paper underscore the transformative potential of artificial intelligence in biomedical research and justify its continued integration in pharmaceutical pipelines.
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