{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T14:56:20Z","timestamp":1775919380197,"version":"3.50.1"},"reference-count":23,"publisher":"Oxford University Press (OUP)","issue":"Supplement_1","license":[{"start":{"date-parts":[[2023,6,30]],"date-time":"2023-06-30T00:00:00Z","timestamp":1688083200000},"content-version":"vor","delay-in-days":29,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100023699","name":"Health Data Research UK","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100023699","id-type":"DOI","asserted-by":"publisher"}]},{"name":"The Alan Turing Institute Wellcome PhD Programme in Health Data Science","award":["218529\/Z\/19\/Z"],"award-info":[{"award-number":["218529\/Z\/19\/Z"]}]},{"name":"Wellcome Cambridge Trust Scholarship"},{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["204832\/B\/16\/Z"],"award-info":[{"award-number":["204832\/B\/16\/Z"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,6,30]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>There exists a range of different quantification frameworks to estimate the synergistic effect of drug combinations. The diversity and disagreement in estimates make it challenging to determine which combinations from a large drug screening should be proceeded with. Furthermore, the lack of accurate uncertainty quantification for those estimates precludes the choice of optimal drug combinations based on the most favourable synergistic effect.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In this work, we propose SynBa, a flexible Bayesian approach to estimate the uncertainty of the synergistic efficacy and potency of drug combinations, so that actionable decisions can be derived from the model outputs. The actionability is enabled by incorporating the Hill equation into SynBa, so that the parameters representing the potency and the efficacy can be preserved. Existing knowledge may be conveniently inserted due to the flexibility of the prior, as shown by the empirical Beta prior defined for the normalized maximal inhibition. Through experiments on large combination screenings and comparison against benchmark methods, we show that SynBa provides improved accuracy of dose\u2013response predictions and better-calibrated uncertainty estimation for the parameters and the predictions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The code for SynBa is available at https:\/\/github.com\/HaotingZhang1\/SynBa. The datasets are publicly available (DOI of DREAM: 10.7303\/syn4231880; DOI of the NCI-ALMANAC subset: 10.5281\/zenodo.4135059).<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btad240","type":"journal-article","created":{"date-parts":[[2023,5,24]],"date-time":"2023-05-24T20:28:40Z","timestamp":1684960120000},"page":"i121-i130","source":"Crossref","is-referenced-by-count":4,"title":["SynBa: improved estimation of drug combination synergies with uncertainty quantification"],"prefix":"10.1093","volume":"39","author":[{"given":"Haoting","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, University of Cambridge , Cambridge CB3 0FD, United Kingdom"},{"name":"Health Data Research UK , London NW1 2BE, United Kingdom"}]},{"given":"Carl Henrik","family":"Ek","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, University of Cambridge , Cambridge CB3 0FD, United Kingdom"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8196-5565","authenticated-orcid":false,"given":"Magnus","family":"Rattray","sequence":"additional","affiliation":[{"name":"Division of Informatics, Imaging and Data Sciences, University of Manchester , Manchester M13 9PL, United Kingdom"},{"name":"Alan Turing Institute , London NW1 2DB, United Kingdom"}]},{"given":"Marta","family":"Milo","sequence":"additional","affiliation":[{"name":"Oncology Data Science, Oncology R&D AstraZeneca , Cambridge CB2 8PA, United Kingdom"}]}],"member":"286","published-online":{"date-parts":[[2023,6,30]]},"reference":[{"key":"2023063008154546500_btad240-B1","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1111\/j.1744-7348.1939.tb06990.x","article-title":"The toxicity of poisons applied jointly","volume":"26","author":"Bliss","year":"1939","journal-title":"Ann Appl Biol"},{"key":"2023063008154546500_btad240-B2","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.drudis.2015.09.003","article-title":"Modelling of compound combination effects and applications to efficacy and toxicity: state-of-the-art, challenges and perspectives","volume":"21","author":"Bulusu","year":"2016","journal-title":"Drug Discov Today"},{"key":"2023063008154546500_btad240-B3","first-page":"331","article-title":"The search for synergy: a critical review from a response surface perspective","volume":"47","author":"Greco","year":"1995","journal-title":"Pharmacol Rev"},{"key":"2023063008154546500_btad240-B4","first-page":"4","article-title":"The possible effects of the aggregation of the molecules of haemoglobin on its dissociation curves","volume":"40","author":"Hill","year":"1910","journal-title":"J. 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