Prediction of Drug–Drug Interactions Based on Artificial Intelligence: A Systematic Literature Review

The comprehensive knowledge about the simultaneous use of multiple drugs to treat a disease is essential for the medical community to determine the best decisions for patient health. The use of various drugs at the same time to treat a disease can result in drug–drug interaction, raising the possibility of serious side effects. This study conducted a systematic literature review that describes the declarative information about drug–drug interactions, including the research papers from 2019 to 2025. The study focused on significant areas that can enhance modern research in drug–drug interactions, which were not included in previous studies. It is composed of artificial intelligence techniques, particularly those based on machine learning and deep learning for predicting drug–drug interactions. The PRISMA-based flow chart concept is used in the literature review stage. After a thorough review of the research papers, 33 studies were chosen. This work presents four research questions that were addressed and answered by the obtained results. The study found that the drug–drug interaction trend increased starting from 2021. It also found that deep learning models and their hybrid framewo