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Drug interactions

Predicting emerging drug interactions using GNNs

Nature Computational Science volume 3, pages 1007–1008 (2023)Cite this article

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EmerGNN is a flow-based graph neural network (GNN) approach that advances on conventional methodologies for predicting drug–drug interactions in emerging drugs by effectively leveraging biomedical networks.

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Fig. 1: Drug–drug interaction (DDI) prediction architecture using graph neural networks (GNNs).

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Authors and Affiliations

  1. Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan

    Nguyen Quoc Khanh Le

  2. AIBioMed Research Group, Taipei Medical University, Taipei, Taiwan

    Nguyen Quoc Khanh Le

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  1. Nguyen Quoc Khanh Le
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Correspondence to Nguyen Quoc Khanh Le.

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Le, N.Q.K. Predicting emerging drug interactions using GNNs. Nat Comput Sci 3, 1007–1008 (2023). https://doi.org/10.1038/s43588-023-00555-7

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