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• CrossADR achieves state-of-the-art performance in predicting adverse drug reactions for combination pharmacotherapy.result 95%
• CrossADR utilizes a gated-residual-flow graph neural network to integrate multi-scale molecular features.method 95%
• CrossADR employs a learnable ADR embedding space to dynamically capture latent biological correlations across 15 organ systems.method 95%
• The CrossADR framework is evaluated on a dataset covering 1,376 drugs and 946,000 unique combinations.technical 95%
• CrossADR provides high-resolution insights into drug-related protein-protein interactions and pathways.result 90%
• Current graph-based architectures for ADR prediction struggle to effectively integrate multi-scale biological information.limitation 85%
• CrossADR can be utilized to prevent ADRs in clinical decision-making.market 80%

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