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Computational models offer significant benefits by accelerating drug evaluation, reducing complexity, and lowering costs; however, challenges persist in the drug classification system. To address this, a literature survey of computational models used for predicting ATC classes was conducted, covering research from 2008 to 2024. This study reviews numerous research articles on drug classification, focusing on drug descriptors, data sources, tasks, computational methods, model performance, and challenges in predicting ATC classes. It also examines the evolution of computational techniques and their application in identifying ATC classes. 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