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dc.contributor.authorSlade, Emilyen_US
dc.contributor.authorDwoskin, Linda P.en_US
dc.contributor.authorZhang, Guo-Qiangen_US
dc.contributor.authorTalbert, Jeffery C.en_US
dc.contributor.authorChen, Jinen_US
dc.contributor.authorFreeman, Patricia R.en_US
dc.contributor.authorKantak, Kathleen M.en_US
dc.contributor.authorHankosky, Emily R.en_US
dc.contributor.authorFouladvand, Sajjaden_US
dc.contributor.authorMeadows, Amy L.en_US
dc.contributor.authorBush, Heather M.en_US
dc.date.accessioned2021-03-24T14:04:10Z
dc.date.available2021-03-24T14:04:10Z
dc.identifier.citationEmily Slade, Linda P Dwoskin, Guo-Qiang Zhang, Jeffery C Talbert, Jin Chen, Patricia R Freeman, Kathleen M Kantak, Emily R Hankosky, Sajjad Fouladvand, Amy L Meadows, Heather M Bush. "Integrating data science into the translational science research spectrum: A substance use disorder case study." Journal of Clinical and Translational Science, pp. 1 - 6. https://doi.org/10.1017/cts.2020.521
dc.identifier.issn2059-8661
dc.identifier.urihttps://hdl.handle.net/2144/42313
dc.description.abstractThe availability of large healthcare datasets offers the opportunity for researchers to navigate the traditional clinical and translational science research stages in a nonlinear manner. In particular, data scientists can harness the power of large healthcare datasets to bridge from preclinical discoveries (T0) directly to assessing population-level health impact (T4). A successful bridge from T0 to T4 does not bypass the other stages entirely; rather, effective team science makes a direct progression from T0 to T4 impactful by incorporating the perspectives of researchers from every stage of the clinical and translational science research spectrum. In this exemplar, we demonstrate how effective team science overcame challenges and, ultimately, ensured success when a diverse team of researchers worked together, using healthcare big data to test population-level substance use disorder (SUD) hypotheses generated from preclinical rodent studies. This project, called Advancing Substance use disorder Knowledge using Big Data (ASK Big Data), highlights the critical roles that data science expertise and effective team science play in quickly translating preclinical research into public health impact.en_US
dc.format.extentp. 1 - 6en_US
dc.languageen
dc.language.isoen_US
dc.publisherCambridge University Press (CUP)en_US
dc.relation.ispartofJournal of Clinical and Translational Science
dc.rights© The Association for Clinical and Translational Science 2020. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectData scienceen_US
dc.subjectTeam scienceen_US
dc.subjectTranslational science research spectrumen_US
dc.subjectSubstance use disorderen_US
dc.subjectHealthcare big dataen_US
dc.titleIntegrating data science into the translational science research spectrum: a substance use disorder case studyen_US
dc.typeArticleen_US
dc.description.versionPublished versionen_US
dc.identifier.doi10.1017/cts.2020.521
pubs.elements-sourcecrossrefen_US
pubs.notesEmbargo: Not knownen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Arts & Sciencesen_US
pubs.organisational-groupBoston University, College of Arts & Sciences, Department of Psychological & Brain Sciencesen_US
pubs.publication-statusPublished onlineen_US
dc.date.online2020-08-19
dc.identifier.orcid0000-0003-1866-9485 (Kantak, Kathleen M)
dc.identifier.mycv590982


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© The Association for Clinical and Translational Science 2020. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as © The Association for Clinical and Translational Science 2020. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.