We hail individual geniuses, but success in science comes through collaboration
(Farrar, 2017)." Biomedical breakthroughs come from collaboration that crosses boundaries. Boundaries created by
disciplines, organizations, cultures, professions, and demographics. While cross-boundary collaboration in team
science has demonstrated benefits, research also suggests they are unlikely to form, and when they do, are prone to
coordination costs (Cooke & Hilton, 2015). This research project advances the Science of Team Science by
"understanding" and "assembling" cross-boundary teams to conduct clinical and translational science. This research
enables scholars and policymakers to design and assess "dream teams." Toward the aim of understanding, we
conduct archival studies of NIH's Clinical & Translational Science Pilot Grant programs at two institutions to reveal
the team assembly factors that drive formation and success. Toward the aim of assembling, we leverage a newly
developed team recommender system. The fundamental goal is to generate recommendations to shift the composition
of teams submitting Pilot Grant applications in particular and cross-boundary scientific teams in general.
Insights from this project come at a critical point in time, when cross-boundary science is essential for biomedical
research. Toward that aim, this project has two key sources of intellectual merit. First, the research advances the
science of team science (Cooke & Hilton, 2015), answering calls to better understand the multilevel determinants of
science team success. How are they forming and which ones are performing? Following teams from formation to
maturity provide a holistic understanding of the factors driving team formation and performance. Knowing how to
better assemble scientific teams has the potential to improve the career productivity of a major source of human
capital, and to hasten breakthroughs in biomedical research. Furthermore, not all cross-boundary teams are
successful. Previous research provides competing advice for those assembling teams. On the one hand, cross-
boundary teams are most likely to produce novel insights (Stvilia et al., 2011; Uzzi et al., 2013), but they are also
most likely to suffer process losses from their coordination costs (Cummings & Kiesler, 2007; Cummings et al.,
2013). This large scale analysis will allow us to discover patterns that differentiate the kinds of cross-boundary teams
who are ultimately successful from those who are not. The second source of intellectual merit is the development of a
team recommender system for biomedical scientists to use to assemble cross-boundary teams for Pilot Projects. The
Dream Team Builder was specifically mentioned in the NAS report as it builds on NIH-funded VIVO's ontology. We
extend this tool to provide team recommendations, and study their effects on team assembly and future performance.