Optimizing drug design by merging generative AI with a physics-based active learning framework
Abstract Machine learning is transforming drug discovery, with generative models (GMs) gaining attention for their ability to design molecules with specific properties. However, GMs often struggle with target engagement, synthetic accessibility, or generalization. To address these, we developed a GM...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | Communications Chemistry |
| Online Access: | https://doi.org/10.1038/s42004-025-01635-7 |
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