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Proposes DDIAgents, a mechanism-conditioned multi-agent framework for drug-drug interaction prediction that dynamically routes relevant biomedical knowledge to specialized expert agents and aggregates their analyses, outperforming existing feature-based, graph-based, and LLM-based methods.