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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9391323 | PMC |
| http://dx.doi.org/10.1038/s42003-022-03746-6 | DOI Listing |
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University of Michigan-Ann Arbor, Ann Arbor, MI, United States.
Up to 90% of high-grade serous ovarian cancer (HGSC) patients will develop resistance to platinum-based chemotherapy, posing substantial therapeutic challenges due to a lack of universally druggable targets. Leveraging BenevolentAI's AI-driven approach to target discovery, we screened potential AI-predicted therapeutic targets mapped to unapproved tool compounds in patient-derived 3D models. This identified TNIK, which is modulated by NCB-0846, as a novel target for platinum-resistant HGSC.
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