OBJECTIVES/GOALS: Clonal hematopoiesis of indeterminate potential (CHIP) is a common age-related condition that confers an increased risk of blood cancer, cardiovascular disease, and overall mortality. Larger proportions of blood cells with the CHIP mutation (clones) lead to worse outcomes. The goal of this study was to characterize CHIP clonal behavior over time. METHODS/STUDY POPULATION: While DNA biobanks have the ability to identify large cohorts of individuals with CHIP, they typically only contain blood from a single timepoint, limiting the ability to infer how CHIP clones change over time. In this preliminary study, we utilized multi-timepoint blood samples from 101 individuals with CHIP in Vanderbilt’s biobank (BioVU) to characterize clonal behavior over time. Using a CHIP gene-specific sequencing pipeline, we were able to characterize each individual’s CHIP mutation(s) and how the fraction of cells with the CHIP mutation expanded/reduced over time. By Spring 2023, we will also include ~300 additional individuals with CHIP in this study. RESULTS/ANTICIPATED RESULTS: CHIP mutations occurred 48% of the time in DNMT3A and 23% of the time in TET2, consistent with previous studies. 21% of individuals had more than one CHIP mutation. The mean difference in time between the two timepoints was 5.2 years (SD=2.9). Surprisingly, we observed both clonal expansion and clonal reduction across timepoints with 30% of DNMT3A, 0.6% of TET2, and 46% of JAK2 clones shrinking over time. The fastest average expansion was seen in TET2 clones (2% growth/year) and the slowest in DNMT3A clones (0.4% growth/year), but there was a significant amount of variation between individuals. In DNMT3A clones, there were no differences observed between loss of function mutations, missense mutations or DNMT3A R882 hotspot mutations. Clonal competition was observed in individuals with multiple driver mutations. DISCUSSION/SIGNIFICANCE: We used multi-timepoint blood samples to quantify the change in CHIP cell fraction over time on a per individual basis and observed novel clonal behavior and competition. Understanding the factors that influence the rate of CHIP progression can lead to personalized disease risk assessment for individuals with CHIP.