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These interactions often overlap, forming a complex, interconnected landscape that necessitates accurate prediction to improve patient outcomes and support evidence-based care. Recent advances in artificial intelligence (AI), powered by large-scale datasets (e.g., DrugBank, TWOSIDES, SIDER), have significantly enhanced interaction prediction. Machine learning, deep learning, and graph-based models show great promise, but challenges persist, including data imbalance, noisy sources, Limited explainability, and underrepresentation of certain types of interactions. This systematic review of 147 studies (2018\u20132024) is the first to comprehensively map AI applications across major interaction types. We present a detailed taxonomy of models and datasets, emphasizing the growing roles of large language models and knowledge graphs in overcoming key limitations. Their integration\u2014alongside explainable AI tools\u2014enhances transparency, paving the way for AI-driven systems that proactively mitigate adverse interactions. By identifying the most promising approaches and critical research gaps, this review lays the groundwork for advancing more robust, interpretable, and personalized models for drug interaction prediction.<\/jats:p>","DOI":"10.1186\/s13321-025-01093-2","type":"journal-article","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T08:14:56Z","timestamp":1758269696000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A comprehensive landscape of AI applications in broad-spectrum drug interaction prediction: a systematic review"],"prefix":"10.1186","volume":"17","author":[{"given":"Nour H.","family":"Marzouk","sequence":"first","affiliation":[]},{"given":"Sahar","family":"Selim","sequence":"additional","affiliation":[]},{"given":"Mustafa","family":"Elattar","sequence":"additional","affiliation":[]},{"given":"Mai S.","family":"Mabrouk","sequence":"additional","affiliation":[]},{"given":"Mohamed","family":"Mysara","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,9,19]]},"reference":[{"issue":"04","key":"1093_CR1","first-page":"2585","volume":"29","author":"FHM Al-Anazi","year":"2022","unstructured":"Al-Anazi FHM, Talhah AFMB, Al-Anazi YAM, Alanazi NKA, Almubarak AAS, Almutairi AQK (2022) Drug interactions and their implications for patient safety. 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