• A novel graph neural network with attention mechanism achieves 0.95 AUC for drug-drug interaction prediction.
• The model outperforms traditional machine learning baselines by 15% in precision.
• Case study on cardiovascular drugs identifies 20 high-risk combinations not previously flagged.
• The framework can be integrated into clinical decision support systems to enhance patient safety.