TY - JOUR
T1 - Integrating data science into the translational science research spectrum
T2 - A substance use disorder case study
AU - Slade, Emily
AU - Dwoskin, Linda P.
AU - Zhang, Guo Qiang
AU - Talbert, Jeffery C.
AU - Chen, Jin
AU - Freeman, Patricia R.
AU - Kantak, Kathleen M.
AU - Hankosky, Emily R.
AU - Fouladvand, Sajjad
AU - Meadows, Amy L.
AU - Bush, Heather M.
AU - Slade, Emily
N1 - Publisher Copyright:
© 2021 Cambridge University Press. All rights reserved.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Data science
KW - healthcare big data
KW - substance use disorder
KW - team science
KW - translational science research spectrum
UR - http://www.scopus.com/inward/record.url?scp=85103385113&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85103385113&partnerID=8YFLogxK
U2 - 10.1017/cts.2020.521
DO - 10.1017/cts.2020.521
M3 - Article
AN - SCOPUS:85103385113
VL - 5
JO - Journal of Clinical and Translational Science
JF - Journal of Clinical and Translational Science
IS - 1
M1 - e29
ER -