Integrating data science into the translational science research spectrum: A substance use disorder case study

Emily 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, Emily Slade

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

The 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.

Original languageEnglish
Article numbere29
JournalJournal of Clinical and Translational Science
Volume5
Issue number1
DOIs
StatePublished - 2021

Bibliographical note

Funding Information:
The project described was supported by the NIH National Center for Advancing Translational Sciences through grant number UL1TR001998 and by the NIH National Institute on Drug Abuse through grant number F32DA045483. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Funding Information:
Acknowledgments. The project described was supported by the NIH National Center for Advancing Translational Sciences through grant number UL1TR001998 and by the NIH National Institute on Drug Abuse through grant number F32DA045483. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Publisher Copyright:
© 2021 Cambridge University Press. All rights reserved.

Keywords

  • Data science
  • healthcare big data
  • substance use disorder
  • team science
  • translational science research spectrum

ASJC Scopus subject areas

  • Medicine (all)

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