{"entity": "researcher", "timestamp": "2026-08-25T09:31:58.396Z", "family": "Mason", "given": "Mike J", "initials": "MJ", "orcid": "0000-0002-5652-7739", "affiliations": ["Sage Bionetworks, Seattle, WA, 98121, USA."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/ed07e0a5353c4b58861c2accaa6c378a.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/ed07e0a5353c4b58861c2accaa6c378a"}}, "publications": [{"entity": "publication", "iuid": "ffbc55b0f6ac4dc3bd6c0644e53e26b4", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/ffbc55b0f6ac4dc3bd6c0644e53e26b4.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/ffbc55b0f6ac4dc3bd6c0644e53e26b4"}}, "title": "Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen.", "authors": [{"family": "Menden", "given": "Michael P", "initials": "MP", "orcid": "0000-0003-0267-5792", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/907d386ca4114274babf4703c976ecbe.json"}}, {"family": "Wang", "given": "Dennis", "initials": "D"}, {"family": "Mason", "given": "Mike J", "initials": "MJ", "orcid": "0000-0002-5652-7739", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/ed07e0a5353c4b58861c2accaa6c378a.json"}}, {"family": "Szalai", "given": "Bence", "initials": "B"}, {"family": "Bulusu", "given": "Krishna C", "initials": "KC"}, {"family": "Guan", "given": "Yuanfang", "initials": "Y"}, {"family": "Yu", "given": "Thomas", "initials": "T", "orcid": "0000-0002-5841-0198", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/305ebda510824746b8063342f6282da9.json"}}, {"family": "Kang", "given": "Jaewoo", "initials": "J", "orcid": "0000-0001-6798-9106", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3fe9dbeb9c1f42c89f33b06c78ba6e5f.json"}}, {"family": "Jeon", "given": "Minji", "initials": "M"}, {"family": "Wolfinger", "given": "Russ", "initials": "R"}, {"family": "Nguyen", "given": "Tin", "initials": "T", "orcid": "0000-0001-8001-9470", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1ea1a8c04dbf457991d78978bec654ed.json"}}, {"family": "Zaslavskiy", "given": "Mikhail", "initials": "M"}, {"family": "AstraZeneca-Sanger Drug Combination DREAM Consortium", "given": "", "initials": ""}, {"family": "Jang", "given": "In Sock", "initials": "IS"}, {"family": "Ghazoui", "given": "Zara", "initials": "Z"}, {"family": "Ahsen", "given": "Mehmet Eren", "initials": "ME", "orcid": "0000-0002-4907-0427", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d158b38689c04eb588da2787e9d51878.json"}}, {"family": "Vogel", "given": "Robert", "initials": "R"}, {"family": "Neto", "given": "Elias Chaibub", "initials": "EC"}, {"family": "Norman", "given": "Thea", "initials": "T"}, {"family": "Tang", "given": "Eric K Y", "initials": "EKY"}, {"family": "Garnett", "given": "Mathew J", "initials": "MJ"}, {"family": "Veroli", "given": "Giovanni Y Di", "initials": "GYD"}, {"family": "Fawell", "given": "Stephen", "initials": "S"}, {"family": "Stolovitzky", "given": "Gustavo", "initials": "G", "orcid": "0000-0002-9618-2819", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/453df82ed4764a8684b238f4468e97d4.json"}}, {"family": "Guinney", "given": "Justin", "initials": "J", "orcid": "0000-0003-1477-1888", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/36c238ff55884b1ab1de6533012d26b7.json"}}, {"family": "Dry", "given": "Jonathan R", "initials": "JR"}, {"family": "Saez-Rodriguez", "given": "Julio", "initials": "J", "orcid": "0000-0002-8552-8976", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/504df2e61c124714b9afecf767798a00.json"}}], "type": "journal article", "published": "2019-06-17", "journal": {"title": "Nat Commun", "issn": "2041-1723", "volume": "10", "issue": "1", "pages": "2674", "issn-l": "2041-1723"}, "abstract": "The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.", "doi": "10.1038/s41467-019-09799-2", "pmid": "31209238", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC6572829"}, {"db": "pii", "key": "10.1038/s41467-019-09799-2"}], "notes": [], "created": "2026-08-21T11:48:18.156Z", "modified": "2026-08-21T11:48:18.496Z"}]}