Objectives/Goals: The Michigan Institute for Clinical & Health Research (MICHR) created an eight-phase adaptive Translational Science Framework to guide us in selecting and solving translational science problems. We operationalized the initial problem selection phases and assessed utility of various methods in shaping complex problems for solution design. Methods/Study Population: We identified three high-priority strategic domains where there was potential to improve the efficiency and effectiveness of research and related processes. Starting with broad problem statements, we engaged a wide array of stakeholders and end-users in a sequence of methods to reduce ambiguity, uncover root causes, and clarify actionable challenges. The methods we selected align with the four problem selection/problem analysis phases of our Translational Science Framework: contextualize, frame, map, and craft. Methods used included landscape and workforce assessments; purpose and scoping sessions; design research strategies; systems mapping; quantitative needs assessments; and translational science proposal pitches. Results/Anticipated Results: Across the three strategic domains, we successfully reframed and scaled ill-defined problem statements into translational science questions that are actionable, meaningful, feasible, and relevant. The outputs of each problem selection/problem analysis phase served as critical inputs for subsequent phases; for example, synthesis of landscape and workforce assessments in the contextualize phase provided critical substrate for structuring the design research and broad scale needs assessments in the frame phase. This funneling approach brought continuous focus and clarity to the problem statements. A variety of metrics embedded within the phases informed performance, progress, and decision-making, which enabled rapid adjustments in the face of evolving contexts and unforeseen challenges. Discussion/Significance of Impact: In the absence of translational science problem analysis, we risk not addressing actual needs, duplicating effort, and/or creating unwanted solutions. The methods and metrics within the analysis phases of our Translational Science Framework promote iterative refinement of intractable problems, with the goal of yielding impactful solutions.