Precision oncology in the age of AI: lessons from AI-driven drug discovery and clinical translation
Abstract Drug discovery has been constrained by extended timelines and high costs, as the cumulative requirements of preclinical validation, multi-phase clinical trials, and regulatory approval have been imposed. Recently, computational modeling has been explored as a supportive approach to accelera...
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| Format: | Artigo |
| Sprache: | Inglês |
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Nature Portfolio
2026-04-01
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| Schriftenreihe: | BJC Reports |
| Online-Zugang: | https://doi.org/10.1038/s44276-026-00221-1 |
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