MoltiTox: a multimodal fusion model for molecular toxicity prediction

These findings highlight that integrating diverse molecular representations enhances both the robustness and generalizability of toxicity prediction models. Beyond predictive performance, the inclusion of ¹³C NMR data offers complementary chemical insights that are not fully captured by structure or language-based representations, suggesting its potential contribution to mechanistic understanding of molecular toxicity. By demonstrating how multimodal integration enriches molecular representations and enhances the interpretability of toxicity mechanisms, MoltiTox provides an extensible framework for developing more reliable models in computational toxicology.