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    "story_id": "mp-2026-11-12-011",
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    "headline": "A Promising Molecule Can Fail at the Required Dose",
    "slug": "a-promising-molecule-can-fail-at-the-required-dose",
    "dek": "Exposure-aware simulation reshuffles candidates that static potency and toxicity screens had placed near the top.",
    "summary": "Exposure-aware simulation reshuffles candidates that static potency and toxicity screens had placed near the top.",
    "body_text": "Researchers re-evaluated 60 molecules selected by three generative drug-design pipelines using physiologically based pharmacokinetic simulations. Seven failed to reach sufficient target exposure, and 28% of the remaining candidates showed predicted safety risks at the required dose. Among candidates with an achievable dose, 85% were outperformed by molecules that the static selection had overlooked. The result is computational and target-specific, but it shows why potency and toxicity predictions alone can rank the wrong candidates.",
    "why_it_matters": "Exposure-aware simulation reshuffles candidates that static potency and toxicity screens had placed near the top.",
    "limitations": [],
    "importance": 8,
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    "first_published_at": "2026-11-12T09:00:00.000-05:00",
    "modified_at": "2026-11-12T09:00:00.000-05:00",
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    "tags": [
      "drug-design",
      "dose",
      "exposure",
      "simulation"
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  "sources": [
    {
      "source_id": "source-2026-11-12-011",
      "title": "arXiv:2611.13398v1",
      "publisher": "arXiv / Cornell University",
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      "published_at": "2026-11-09T19:20:01.000-05:00",
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  "publisher": {
    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
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  "cite_this_report": {
    "title": "A Promising Molecule Can Fail at the Required Dose",
    "publisher": "The Machine Press",
    "published_at": "2026-11-12T09:00:00.000-05:00",
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