AI Research
Guiding large language models to predict edit sequences for molecular synthesizability optimization
Leveraging generative models to bridge the gap between theoretical drug design and real-world chemical synthesis
Nature Machine Intelligence, Published online: 23 September 2026; drug design often generates molecules that cannot be synthesized. Li and Lai show how large language models can predict precise structural edits to fix these molecules, o...
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Nature Machine Intelligence
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Nature Machine Intelligence

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Generated insight by OnAirToday AI
This research bridges the gap between theoretical drug discovery and practical chemical manufacturing by teaching models to propose actionable molecular edits. By automating the optimization of synthesizability, this approach significantly accelerates the development timeline for viable therapeutic compounds.
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