{"url":"/dataset/gdscv2","name":"GDSC","full_name":"Genomics of Drug Sensitivity in Cancer","description_markdown":"We have characterized 1000 human cancer cell lines and screened them with 100s of compounds.\r\nOn this website, you will find drug response data and genomic markers of sensitivity.\r\n\r\nThe Genomics of Drug Sensitivity in Cancer Project - http://www.cancerrxgene.org/ - was part of a Wellcome Trust-funded collaboration between The Cancer Genome Project at the Wellcome Sanger Institute (UK) and the Center for Molecular Therapeutics, Massachusetts General Hospital Cancer Center (USA). This collaboration integrated the expertise at both sites toward the goal of identifying cancer biomarkers that can be used to identify genetically defined subsets of patients most likely to respond to cancer therapies.\r\n\r\nWe screened >1000 genetically characterized human cancer cell lines with a wide range of anti-cancer therapeutics. These compounds included cytotoxic chemotherapeutics as well as targeted therapeutics from commercial sources, academic collaborators, and the biotech and pharmaceutical industries.\r\n\r\nThe sensitivity patterns of the cell lines were correlated with extensive genomic and expression data to identify genetic features that are predictive of sensitivity. This large collection of cell lines enabled us to capture much of the genomic heterogeneity that underlies human cancer, and which appears to play a critical role in determining the variable response of patients to treatment with specific agents.","description_withheld":null,"homepage":"https://www.cancerrxgene.org/","introduced_date":"2015-01-01","introduced_date_note":null,"introduced_by":null,"license":{"name":"The data files are experimental and academic in nature and are not licensed or certified by any regulatory body. Genome Research Limited provides access to data files on an “as is” basis and excludes all warranties of any kind (express or implied).","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"},{"name":"Graphs","url":"/datasets/modality/graphs"}],"tasks":[{"name":"Drug Response Prediction","url":"/task/drug-response-prediction","datasets_with_task":"/datasets/task/drug-response-prediction"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["GDSC"],"data_loaders":[],"num_papers_in_archive":4,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/drug-response-prediction-on-gdsc","task":"Drug Response Prediction","dataset_variant":"GDSC","rows":1,"metrics":["Pearson correlation coefficient (PCC)"],"first_row_in_archive_order":{"model":"CLDR","paper":"/paper/cldr-contrastive-learning-drug-response","metrics":{"Pearson correlation coefficient (PCC)":"0.5360"},"code_links":[{"title":"xiaoyibang/clipdrug","url":"https://gitee.com/xiaoyibang/clipdrug"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/cldr-contrastive-learning-drug-response","title":"CLDR: Contrastive Learning Drug Response Models from Natural Language Supervision","date":"2023-12-17","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}