Machine Learning Applications for Drug Repurposing

Machine learning (ML) is transforming drug repurposing by efficiently identifying new therapeutic uses for existing drugs, thus accelerating drug discovery and reducing costs. ML algorithms analyze large biomedical datasets to uncover hidden patterns, linking drugs to diseases and predicting side effects, which is crucial for precision medicine and personalized healthcare. The chapter reviews various case studies demonstrating ML's role in identifying drug-disease connections and predicting adverse reactions, while also addressing the ethical and privacy concerns of using patient data. It highlights the successes and challenges in this emerging field, advocating for the integration of pharmaceutical research, clinical practice, and computer sciences to advance healthcare.