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This presentation explores challenges in drug discovery, emphasizing safer drug predictions through toxicity modelling. It introduces graph-based molecular representations, leveraging Graph Neural Networks and the Tox21 dataset for analysis. Key methodologies include feature extraction using RDKit, processing via GCN layers, and constructing toxicity network architectures. Practical examples demonstrate predictions using SMILES, evaluation with PyTorch Geometric, and UI implementation with...