OBJECTIVES/GOALS: Securing seed funding and external support can be a daunting process. Institutions are increasingly looks for quantitative assurance of impact and accountability. This study investigates factors predictive of seed funding selection, including pace of submissions as well as external support. METHODS/STUDY POPULATION: Using Generalized Logistic Mixed Models (GLMMs), we model factors found to be predictive of researcher success, and model demographic factors as well, to understand the complex interplay of researcher background, professional networks and preparation, and researcher persistence. The following factors were modeled as potentially predictive of researcher success: faculty rank; co-PI; h-index; rate of application; prior award funding amounts; and research-focused social media posts. RESULTS/ANTICIPATED RESULTS: After effects are finalized, we expect that pace of seed fund applications and the strength co-PIs, as measured by h-indices, to be significant predictors of researcher success for both securing seed funding and external support. DISCUSSION/SIGNIFICANCE: This study identifies features associated with eventual research program success and can be used to support accountability and impact efforts at an institutional level. Research institutes strive to ensure equal access to these opportunities and train applicants to produce improved project proposals. Results from this study inform these efforts.