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Personalized drug response has received public awareness in recent years. Howto combine gene test result and drug sensitivity records is regarded asessential in the real-world implementation. Research articles are good sourcesto train machine predicting, inference, reasoning, etc. In this project, wecombine the patterns mined from biological research articles and categoricaldata to construct a drug-gene interaction network. Then we use the cell lineexperimental records on gene and drug sensitivity to estimate the edgeembeddings in the network. Our model provides white-box explainable predictionsof drug response based on gene records, which achieves 94.74% accuracy inbinary drug sensitivity prediction task.

Predicting Drug Responses by Propagating Interactions through Text-Enhanced Drug-Gene Networks