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Anveshar is a reproducible research workbench for rare cancers, built to run from inside Claude Science. Rare cancers are individually rare but collectively common, and each is underserved: too few patients for a dedicated trial or model. Anveshar catalogs 504 rare cancers (743 conditions), each with driver genes, potential causes, and cited cross-condition therapies scored by confidence, and presents them in an interactive Atlas Explorer that links every cancer to its genes, the analyses you can run, and the runnable foundation models. Its pipeline is reproducible and provenance tracked, pulling live data from Open Targets, DepMap, cBioPortal, ClinicalTrials, and PubMed. On top of retrieval it runs and trains sequence models on rare tumors: ESM-2 scores driver variants zero shot (pathogenic VHL R167W reads as damaging; the SF3B1 K700E change of function hotspot correctly reads as tolerated), and a trained ESM-2 head lifts missense pathogenicity from AUC 0.912 to 0.983 on 588 real ClinVar-labeled variants across twelve driver genes. Two findings are reproducible from public data: rectal neuroendocrine tumors are molecularly distinct from colorectal cancer, and in uveal melanoma an integrated multi-omic class predicts survival where a BAP1 mutation call does not. Because Anveshar makes existing knowledge and foundation models transferable, cited, and reproducible for the cancers that lack their own resources, it provides a personalized platform for tailored investigation of rare cancers.

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digvijayky

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