OBJECTIVES/GOALS: Our objective is to develop a patient-friendly application addressing the progression of cognitive impairments in multiple sclerosis (MS) patients. This initiative aims to augment individualized care and precision management of a major MS comorbidity by generating a cognitive health brain map for each patient. METHODS/STUDY POPULATION: Using the UAMS COMS Database, featuring high-resolution multi-contrast MRIs, and a comprehensive clinical, behavioral, and demographic dataset, we are developing a hierarchical learning-based software tool to compute maps correlating brain structure-function and individual cognitive function. Our MRI analysis employs a three-compartment model (NNLS>0.96). Functional scores are defined by individualized accuracy during the modified information processing speed task (e.g., m-SDMT). We utilize a Bayesian classifier with explicit Pearson’s correlation for tissue classification (BF10>100) to compute an index of the likelihood of correlation with cognitive impairment throughout brain tissue. RESULTS/ANTICIPATED RESULTS: This approach allows us to reveal subtle cognitive changes and their potential links to myelin integrity, offering vital insights into disease progression and management. The m-SDMT strongly correlates with the standard SDMT (r=0.79, p<0.001), confirming reliability as a cognitive assessment tool in clinical and research contexts. Analysis of the COMS dataset emphasized insights into the role of fine myelin structure in MS patients' cognitive functionality. Our findings heightened the pivotal significance of myelin integrity in preserving cognitive abilities and identify disruptions in myelin synthesis and homeostasis as primary contributors to cognitive decline. This discovery stresses the critical role that specialized brain pathways, influenced by myelin integrity, play in the pathology of MS. DISCUSSION/SIGNIFICANCE: This development bridges advanced neuroimaging techniques with practical clinical applications, emphasizing the nuanced role of myelin integrity in MS-related cognitive deficits. Our findings advocate for a multidisciplinary approach to MS management, demanding collaborative workforce development and education in translational science.