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Discussion and conclusions This work establishes a comprehensive computational framework for drug solubility prediction in binary solvent mixtures, demonstrating that thoughtful integration and domain-specific optimization of established graph neural network techniques can achieve substantial improvements over traditional descriptor-based approaches

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