Planning for Core Sustainability and Addressing Usage Challenges: Lessons from Core Research Facilities Seeded by NIH IDeA Funding

This panel aims to share strategies and lessons learned related to cores that are both planning for sustainability and addressing usage challenges. Core research facilities seeded by the NIH Institutional Development Award (IDeA) program serve as the ‘model system’ for this exploration, with takeaways expected to be broadly applicable.

Per the NIH, “The IDeA program builds research capacities in states that historically have had low levels of NIH funding by supporting basic, clinical, and translational research; faculty development; and infrastructure improvements.” While NIH IDeA mechanisms are great opportunities for awardee institutions to establish new cores, they can also serve as model systems for exploring how cores–and the institutions in which they are established–think about planning for the sustainable operations of cores after NIH funding while simultaneously addressing nearer-term challenges such as extending core services to potential users with limited funding.

The panel will consist of two parts:
1. Planning for Sustainability – During the first half of the session, panelists from different IDeA awards/institutions will share their experiences as they relate to planning for core sustainability. It is expected that the material will be applicable broadly as the issue of transitioning to core facility sustainability is a commonly observed challenge, whether initial funding comes from competitive external, institutional, philanthropic, or other sources.
2. Addressing Usage Challenges – During the second half of the session, panelists from an IDeA institution will lead discussions on topics related to addressing and overcoming barriers to core facility usage, including voucher programs that fund the use of shared resources to obtain pilot data, best practices for multi-institutional collaborations involving shared resources, and the development of software and data-sharing platforms to support cost efficient bioinformatics.