OBJECTIVES/GOALS: Nearly 3 million Americans live with arm impairment following stroke. While as many as 20% of patients fully recover, individual differences in recovery make one-size-fits-all rehabilitation approaches suboptimal. The goal of this study was to use our custom rehabilitation platform to identify neuromuscular biomarkers of arm control in stroke. METHODS/STUDY POPULATION: Chronic stroke survivors (N = 10) reached for targets in a virtual reality environment using both hands. They completed 162 reaches divided into 3 blocks. Following baseline, we used our custom exoskeletons to provide 50% arm weight assistance to the impaired limb and 50% arm weight resistance to the non-impaired limb. We removed the exoskeletons during the retention block. We used electromyography to approximate muscle activity in the anterior deltoids. Relative contribution (RC) was calculated as the displacement of the impaired arm divided by the sum of displacements for both arms. Muscle contribution (MC) was calculated as the root mean square of impaired arm muscle activity divided by the sum of activity for both deltoids, normalized to maximum voluntary contraction. RESULTS/ANTICIPATED RESULTS: During baseline, RC of the impaired limb was 43%; patients reached significantly less with their impaired arm compared to their non-impaired arm (p = 0.02). MC of the impaired deltoid was 56% and was similar between arms (p = 0.5). During loading, RC did not change relative to baseline (p = 0.87), but MC tended to decrease by 11% (p = 0.12). These results suggest a tradeoff between kinematic and muscular control of reaching. This new finding closely matches our previous work in 12 healthy controls, where we found a 2% increase in RC and a 11% decrease in MC. Importantly, 4/10 patients exhibited an inverse tradeoff (i.e., decrease in RC and/or increase in MC). We will analyze neuroimaging data to determine the role lesion size and location play in predicting an individual’s response to gravity compensation. DISCUSSION/SIGNIFICANCE: Our tradeoff analysis serves as a potential neuromuscular biomarker of stroke survivors’ responsiveness to gravity compensation. This forms the basis for personalized technologies for stroke rehabilitation. With further development, clinicians can use our platform to fine-tune compensation levels based on the individual needs of the patient.