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The Optimizing I.C.E. module will build upon an existing foundation of efforts to develop a new, dynamic, data-driven, multi-stakeholder framework for studying, implementing, and sustaining translational research. We will leverage recent developments in methods and complementary investments to develop data for frontier research on two important translational pathways: workforce development and technology transfer/commercialization. Aim 1 is to develop a database to understand barriers, best practices, and outcomes of ICE. This information will inform Aim 2, which is the creation and implementation of an improvement model and intervention strategies to optimize ICE with the help of a multisector task force and a multisite Learning Collaborative.