22/05/2026
High failure rates for cancer drugs stem from early-stage biological data that lacks predictive power, often due to incomplete datasets or models that fail to capture complex human tumor biology.
Researchers are working to integrate high-quality multi-omics data and advanced AI tools to build more translatable models that better reflect real-world patient responses.
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