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  "author": {
    "name": "Matthew McDowell-Sweet",
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  "created": "2026-09-29T04:57:31Z",
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  "content_md": "> The relevant success metrics for AI in drug discovery need to be numbers that matter, rather than contrived proxy measures that primarily optimize for scientific publications rather than actual R&D progress. Ultimately, what truly matters is increasing clinical approval rates, as well as novelty in both modality and mode of action space.\n\n[Artificial intelligence in drug discovery — what it is, where we stand and the path forward | Nature Reviews Drug Discovery ↗](https://nature.com/articles/s41573-026-01496-2)",
  "content_html": "<blockquote><p>The relevant success metrics for AI in drug discovery need to be numbers that matter, rather than contrived proxy measures that primarily optimize for scientific publications rather than actual R&amp;D progress. Ultimately, what truly matters is increasing clinical approval rates, as well as novelty in both modality and mode of action space.</p></blockquote>\n<p class=\"source\"><a href=\"https://nature.com/articles/s41573-026-01496-2\">Artificial intelligence in drug discovery — what it is, where we stand and the path forward | Nature Reviews Drug Discovery ↗</a></p>",
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