Objectives/Goals: The purpose of this pilot study is to conduct a survey interview to understand the knowledge and attitudes of people experiencing homelessness (PEH) toward clinical trial participation, provide insights for future engagement strategies, and begin bridging the gap between clinical researchers and this marginalized group. Methods/Study Population: A 14-question survey, developed in collaboration with the street medicine (SM) team at the University of Southern California and other key stakeholders in PEH research, was administered in a survey–interview style to PEH in SM’s East Side Los Angeles area of operations. The questions were designed to assess PEH’s knowledge and attitudes toward the significance of clinical research and their potential participation. No identifying information was collected. To ensure diversity in responses, the surveys were conducted in different SM healthcare providers’ areas of operations. The responses were then analyzed both quantitatively and qualitatively, taking into account the broader perspectives that PEH may have toward clinical trial research. Results/Anticipated Results: A total of 9 PEH were surveyed. When asked to share their thoughts on “clinical trials” (CTs), most described the need to travel on-site to a practitioner to be studied/tested. They indicated that they knew what CTs were and that the FDA’s official definition was easy to understand. Only one respondent reported being part of a diagnostic trial, and one declined to answer. Four respondents indicated a willingness to participate in a CT. Four answered “maybe” and one answered “no.” Of note, most believed that CTs have a positive impact, and only one responded that they think researchers do not maximize health benefits and minimize risk. Outside of the allowed answer choices, respondents also shared that there should be payment for participation in a CT, even if they don’t expect any. Discussion/Significance of Impact: The survey results could significantly influence the future of clinical research, guiding it to be better tailored to PEH’s unique circumstances, thereby potentially improving their participation rates. A key objective for the future will be to increase the sample size of the survey to improve the applicability and impact of the results.

OBJECTIVES/GOALS: We explain our multi-platform, multi-audience approach to stakeholder engagement/communication, discuss KPIs for our Instagram accounts, and highlight five top performing posts. Finally, we provide tips to Hubs who would like to tailor and optimize their social media approach. METHODS/STUDY POPULATION: We employed Uses & Gratifications theory and formative research with stakeholders to inform our social media strategy. We run two Instagram accounts (main CTSI & Community Engagement [CE]), one Facebook page (CE), and one Twitter/X page (main CTSI). To understand impact, we collected social media analytics on both Instagram accounts (main CTSI and Community Engagement-specific accounts) to ascertain four social media-related Key Performance Indicators since the inception of the two accounts: reach, impressions, growth rate, and engagement. Additionally, we examined the five top-performing posts on each account that gave us insights into trending topics and ideas for future content. RESULTS/ANTICIPATED RESULTS: From January 2023 to October 2023, the reach for the main account was 3,578 and 38,235 for CE. The number of profile visits for the main account was 474 and 2,703 for CE. Engagement data on Instagram is only available for the last 90 days. For the main account, the number of post likes, comments and shares was 622 and 2,700 for CE. The views and reach for the five top-performing posts on the main and CE accounts ranged in the thousands. The content of the top-performing posts for the main CTSI account varied between highlighting our KL2 scholars' accomplishments, recap of campus-wide research events, and advertisements for upcoming educational webinars. CE’s top posts varied between highlighting their work in a South LA housing community, recaps of large community health events, and interviews with local key leaders. DISCUSSION/SIGNIFICANCE: CTSA Hubs have an ethical obligation to keep their local academic and community audiences apprised of their activities. Creating a formative research and theoretically-informed social media plan that varies by platform, and regularly evaluating performance insights allows us to track the type of content that appeals to our multiple audiences.

OBJECTIVES/GOALS: This work aims to explore how citizen science serves as a transformative frame work to bridge scientific knowledge, focusing on its potential to enhance transdisciplinary learning in artificial intelligence (AI) biomedical and clinical sciences by facilitating near-peer mentoring. METHODS/STUDY POPULATION: Our group of eight friends comprise a multicultural and multidisciplinary cohort including students from the USA, Philippines, Indonesia, and Guatemala pursuing PhD degrees in electrical and computer engineering, epidemiology, physics, and MD, PharmD, and DMD degrees. We engage in shared online courses, collaborative projects, and abstract submissions. Employing our collective knowledge, we design interactive learning experiences, support each other’s initiatives, and collaboratively develop lectures and presentations. We in tend to expand collaborations in biomedical AI education while fostering principles of experiential and collaborativelearning, constructivism, and authentic inquiry. RESULTS/ANTICIPATED RESULTS: Our recent successes include submittedconference abstracts on data science and AI education in pharmacy and the facilitation of a guest lecture in health informatics. Additionally, we are currently collaborating on seven biomedical machine learning projects in radio frequency engineering, aiming for conference submissions. Moving forward, our goal is to expand our group, support the formation of similar communities, and promote data science and AI literacy in biomedical and clinical contexts. We aspire to extend this knowledge to families, classmates, and eventually patients, facilitating a broader understanding of the role of AI in healthcare. DISCUSSION/SIGNIFICANCE: We believe diverse expertise and pedagogical theories can help demonstrate the potential of citizen science to democratize scientific experience. By nurturing collaborative networks our efforts aim to bridge gaps between disciplines and enhance the broader public’s understanding of AI in healthcare.

Rigorous scientific review of research protocols is critical to making funding decisions, and to the protection of both human and non-human research participants. Given the increasing complexity of research designs and data analysis methods, quantitative experts, such as biostatisticians, play an essential role in evaluating the rigor and reproducibility of proposed methods. However, there is a common misconception that a statistician’s input is relevant only to sample size/power and statistical analysis sections of a protocol. The comprehensive nature of a biostatistical review coupled with limited guidance on key components of protocol review motived this work. Members of the Biostatistics, Epidemiology, and Research Design Special Interest Group of the Association for Clinical and Translational Science used a consensus approach to identify the elements of research protocols that a biostatistician should consider in a review, and provide specific guidance on how each element should be reviewed. We present the resulting review framework as an educational tool and guideline for biostatisticians navigating review boards and panels. We briefly describe the approach to developing the framework, and we provide a comprehensive checklist and guidance on review of each protocol element. We posit that the biostatistical reviewer, through their breadth of engagement across multiple disciplines and experience with a range of research designs, can and should contribute significantly beyond review of the statistical analysis plan and sample size justification. Through careful scientific review, we hope to prevent excess resource expenditure and risk to humans and animals on poorly planned studies.

This paper explores the development of the Dissemination and Implementation Science Collaborative (DISC) at the Medical University of South Carolina, established through the Clinical and Translational Science Award program. DISC aims to accelerate clinical and translational science by providing training, mentorship, and collaboration opportunities in dissemination and implementation (D&I) science. Through DISC, investigators, trainees, and community partners are equipped with the knowledge and skills to conduct D&I research and translate findings into practice, particularly in South Carolina’s public health and healthcare landscape. We describe efforts to achieve the major overarching aims of DISC, which include conducting scientific workforce training, providing mentorship and consultation, and advancing methods and processes for D&I research. By sharing DISC experiences, successes, and challenges, this paper aims to support the growth of D&I research and capacity-building programs, fostering collaboration and shared resources in the field.

Observational studies are notoriously susceptible to bias, and parallel-group randomized trials are important to identify the best overall treatment for eligible patients. Yet, such trials can be expected to be a misleading indicator of the best treatment for some subgroups or individual patients. In selected circumstances, patients can be treated in n-of-1 trials to address the inherent heterogeneity of treatment response in clinical populations. Such trials help to accomplish the ultimate goal of all biomedical research, to optimize the care of individual patients.

Strengthening the research workforce is essential for meeting the evolving needs and challenges in the health and biomedical fields. To do so effectively, it requires an understanding of how the experiences of a researcher shift over time and how one’s research career evolves, particularly as supports are put in place to foster research. This narrative review provides a summary of published individual-level assessment measures and survey tools from 2000–2024. All measures were abstracted, classified, and coded during analyses to describe the areas of focus, and they were organized into one of six research categories. The review identified a range of measures and methods across all categories. However, the measures were often narrow, focused on outputs, and not ideal for assessing the full range of experiences a researcher may have throughout their career. The most common metrics were related to research productivity and bibliometric measures. Our review of survey tools revealed a gap in comprehensive approaches available to assess an individual’s research experience, efforts, supports, and impact. As efforts expand to evaluate and study the research workforce, tools that focus on a broad range of individual-level measures, tied to specific underlying constructs and drawn from the literature, may prove useful.

Objectives/Goals: Our goal is to develop a CRM platform to streamline support for investigators, optimize resource use, and enhance service delivery within a CTSA institution. This platform will measure outcomes, improve transparency, and ensure compliance, creating an efficient, supportive research environment. Methods/Study Population: Beginning with the design concepts and collecting technical requirements, ensuring alignment with the needs of investigators, administrators, and service units. Apply project management methodologies to iteratively design, prototype, and test features. Focus on user-centric interfaces and seamless integration with institutional systems. Incorporate stringent data security protocols in compliance with regulatory standards. Conduct pilot studies to refine functionalities and gather constructive feedback. Facilitate extensive user training programs and offer continuous support. Regularly monitor performance metrics, iterating based on empirical data and user feedback to ensure continuous enhancement and adherence to institutional objectives. Results/Anticipated Results: YCCI successfully designed, developed, and implemented a CRM platform for managing the intake, navigation, consultation, service delivery, and outcomes tracking of the clinical and translational science activities that are supported by and beyond the CTSA-supported infrastructure. The CRM platform has been live in production since roughly July 1, 2024, and YCCI is excited to share data, results, and outcomes with the ACTS community. Discussion/Significance of Impact: YCCI’s CRM platform advances the CTS mission by streamlining PI support, enhancing resource utilization, and fostering inter-team collaboration within the research ops and administration teams. Measuring outcomes and service efficiency enables data-driven decisions, ensuring continuous improvement, and impactful translational science.

OBJECTIVES/GOALS: Hypertension is a major risk factor for coronavirus disease 2019 (COVID-19) severity. Our goal was to determine if hypertension worsens lung pathology induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in hamsters. METHODS/STUDY POPULATION: Male hamsters (7-8 weeks old) were infused with angiotensin II (AII; 200 ng/kg/min via osmotic minipump) for 4 weeks to induce hypertension. During the last week of the infusion, the hamsters were inoculated intranasally with vehicle (V) or SARS-CoV-2 (S; 1 x 105 plaque forming units/ml). Half of the hamsters were sacrificed 1 day post-inoculation (dpi-1) and the other half on dpi-6. Two scoring systems were applied to lung tissue sections stained with hematoxylin and eosin to determine the degree and severity of lung pathology: the first system assessed all pertinent alterations in the lungs, while the second system only assessed the pathology related to the pulmonary vasculature. Lung histopathology scores were calculated as the sum of the airway and lung alveolar scores in arbitrary units (AU). RESULTS/ANTICIPATED RESULTS: Studies revealed that the SARS-CoV-2-infected hamsters exhibited a 76-fold higher total airway score compared to vehicle controls [(AU): V, 0.25 ± 0.1; S, 19.00 ±1.35; p<0.05; n=4]. Total lung alveolar scores (27-fold) [(AU): V, 0.30 ± 0.11; S, 8.0 ± 4.1; p<0.05; n=4] and total vascular scores (17-fold) [(AU): V, 0.35 ± 0.2; S, 6.0 ±1.4; p<0.05; n=4] were also markedly higher compared to controls on dpi-1. AII increased blood pressure, which was sustained through the 4-week infusion period. Under these conditions, body weight slightly dropped by 4.5%. Ongoing studies are assessing the effect of hypertension on the % of airway, alveoli and vessels affected, airway and alveolar severity, and bronchiolar epithelial and type II pneumocyte hyperplasia. DISCUSSION/SIGNIFICANCE: Establishing the hypertensive hamster as a small animal model of COVID-19 will facilitate investigations into why preexisting hypertension is a risk factor for disease severity. These studies could lead to the development of novel therapeuticsfor treating COVID-19 patients with hypertension.

OBJECTIVES/GOALS: We are investigating the role of IL-6 in regulating renal function by measuring mean arterial pressure (MAP), renal plasma flow (RPF) and glomerular filtration rate (GFR) in wild type (WT) and IL-6-knockout (KO) mice in established mouse models of angiotensin II (AII)-dependent- hypertension and -salt-sensitive hypertension. METHODS/STUDY POPULATION: Twelve-week-old male WT and KO mice on the C57BL6 background strain were infused with vehicle (V; saline) or angiotensin II (AII; 200 ng/kg/min) for 12-14 days. Half of the AII-treatment groups were maintained on a high salt (HS; 6% NaCl) diet for the duration of the experiment, while the other half of the AII treatment groups and both vehicle groups were fed normal rat chow. MAP was continuously measured by a fluid filled catheter in conscious mice for the duration of the experiment. RPF and GFR were measured on days 12-14 in anesthetized mice by the para-aminohippurate, and fluorescein isothiocynate-Inulin techniques, respectively. All data were analyzed by 2-way ANOVA; *p<0.05 vs. WT, same treatment; #p<0.05 vs.V, same genotype; ^p<0.05, AII vs. AII+HS, same genotype. RESULTS/ANTICIPATED RESULTS: MAP was 31% lower in KO vs WT mice. AII increased MAP (1.2-fold) in WT but not KO mice. HS diet magnified AII-induced increases in MAP in WT and moderately increased MAP in AII-KO mice: [MAP (mmHg): WT+V, 130±7.0; KO+V, 91.0+4.0*; WT+AII, 153±5.0#; KO+AII, 83.0±4.0*; WT+AII+HS, 150±11#; KO+AII+HS, 93.0±4.0#]. AII infusion reduced RPF in the KO but not WT mice. Addition of HS reduced RPF in WT and exacerbated AII-induced reductions in RPF in KO mice [RPF (ml/min/g): WT+V, 1.82±0.23; KO+V, 1.91+0.40; WT+AII, 3.16±0.75#; KO+AII, 1.65±0.42*; WT+AII+HS, 1.10±0.31#^; KO+AII+HS, 1.13±0.XX#^]. The HS diet reduced GFR in AII-infused KO but not WT mice [GFR (µl/min/g): WT+V, 756±XX; KO+V, 788±XX; WT+AII, 1010±63*#; KO+AII, 756±23*; WT+AII+HS, 1100±150#; KO+AII+HS: 540±210*#^]. DISCUSSION/SIGNIFICANCE: The absence of IL-6 in male mice attenuated AII- and/or AII+HS-induced increases in MAP; however, it exacerbated HS-induced reductions in RPF and GFR. These findings suggest inhibiting IL-6 has therapeutic potential as an antihypertensive but not as a renal protective agent in hypertension and salt-sensitive hypertension disease states.

Objectives/Goals: MyCTSC harmonizes data from many sources into one database for evaluation, marketing, and CTSC member management to address current disparate collection and siloed use of data. It simplifies report creation with real-time dashboards so administrators and leadership can view progress quickly and plan for improvements based on real-time data. Methods/Study Population: MyCTSC is built using open-source software like Python, Django, MariaDB, Bootstrap, and Chart.js, and integrates data from sources such as systems for consult requests, pilot/voucher applications, and REDCap surveys. Each data source is imported into the warehouse either automatically via API, if available, or via manual file upload. De-duplication and other data cleaning are performed as well. Customized, real-time dashboards are developed based on the needs of administrators and leadership. While MyCTSC does not have a study population, it does have the stakeholders mentioned above as well as leadership. The development timeline spans three years: initial development and data warehouse population in Year 1, data cleaning and dashboard creation in Year 2, and full rollout to all CTSC members in Year 3. Results/Anticipated Results: MyCTSC aims to create a seamless data and member management system to resolve issues stemming from multiple data sources. Demographic challenges are addressed by implementing data cleaning and consolidating duplicate identities into a single profile. The initiative will enhance stakeholder buy-in by presenting evaluation use cases that show the impacts of CTSC resources. For example, workforce development needs will be met through surveys and integration of a course catalog. MyCTSC will also facilitate targeted resource and event advertising, and support investigator outreach and collaboration by utilizing dashboards and reports. Furthermore, it will serve as the consolidated data source for all CTSC modules, promoting greater interaction and collaboration across administration and modules. Discussion/Significance of Impact: MyCTSC integrates multiple sources, consolidates identities, and simplifies reporting for outreach and collaboration. It enhances interaction with researchers and community members, advancing translational science by linking projects and publications. MyCTSC, built with open-source software, can be made available to other CTSA hubs.

Objectives/Goals: To explore how generative AI and chatbot technologies can transform clinical research administration by improving operational efficiency, reducing administrative burden, and thereby enhancing overall productivity and accuracy in clinical research environments. Methods/Study Population: This explores AI’s application in enhancing clinical research administration. We specifically address AI’s role in QCT/MCA activities, charge master data cleaning, and generating IRB consent forms from award documents. AI algorithms optimize charge master data for accuracy and compliance. Generative AI models are employed to produce IRB consent forms efficiently, incorporating key grant documents. AI also conducts thematic analyses of historical CTSA aims to identify trends and recurring themes. Furthermore, AI-assisted tools enhance study design through innovative approaches to hypothesis generation, sample size calculation, and protocol development. Integrating these AI methods aims to significantly improve efficiency, accuracy, and overall quality in clinical research administration. Results/Anticipated Results: Incorporating AI into clinical research administration will yield improvements in efficiency and accuracy. AI-driven QCT/MCA steps are expected to reduce human error and enhance data integrity. Chargemaster data cleaning via AI prompts will likely result in optimized, error-free data, ensuring compliance with regulations. The use of genAI for creating IRB consent forms from grant documents should significantly streamline the IRB approval process, reducing preparation time and administrative burdens. Thematic analysis of CTSA aims by AI will provide deep insights into historical trends and recurring themes, aiding in strategic planning. AI-assisted study design tools are anticipated to optimize sample estimation, protocol development, and advance the quality of clinical research administration. Discussion/Significance of Impact: The significance lies in enhancing efficiency, accuracy, and quality in clinical research administration. By streamlining processes, reducing errors, and providing strategic insights, AI supports the CTSA mission to accelerate translational research, thus improving public health outcomes and scientific innovation.

OBJECTIVES/GOALS: Involving community partners in translational research improves impact. Yet, community-engaged research is challenging, and teams vary in their success. This study builds the evidence of key barriers and facilitators to effective community-engaged team science by drawing on the perspectives of seasoned researchers and community partners. METHODS/STUDY POPULATION: We conducted 3 focus groups with academic researchers (n=9) and 2 focus groups with community research partners (n=8). All participants were adults from the Southern California area, and had experience working on research teams that included academics and community partners. The focus group guide included questions about the participant’s experience with community-engaged research, including the value of these partnerships, examples of success and challenges, and opportunities for improvement. Transcriptions of the focus group recordings were analyzed to identify key themes and insights, and to explore similarities and differences between academic and community participant perspectives. RESULTS/ANTICIPATED RESULTS: Both researchers and community partners saw the potential value of participating in community-engaged research. However, they identified challenges to address, including: 1) Community partners should be invited to participate in early stages of the research process as equal partners to help frame the objectives. 2) Community partner’s knowledge should be valued through the use of their ideas and input, and providing monetary compensation for their time. 3) Academic researchers should aim to build long-term meaningful relationships with the community and build cultural competency (language, culture, and trust). 4) Community partners should be closely involved with the interpretation of results to confirm accuracy and identify valuable insights, and these contributions should be acknowledged. DISCUSSION/SIGNIFICANCE: Community partners being undervalued is a central challenge of community-engaged research teams. Greater adoption of best practices in team science could empower community partners and increase the value of this research. Structural barriers related to research funding and academic promotion should align to support these efforts.

Rutgers Health, Clinical Research Management (CRM) program with support from New Jersey Alliance for Clinical and Translational Science (NJ ACTS) provide scholarships to establish a “Clinical Research Experience” (CRE). The CRE focuses on building an entry-level Clinical Research Coordinator (CRC) workforce. The six-month precepted CRE is embedded in an accelerated master’s degree and demonstrates a skill-based approach to developing CRC resources. The CRE structure affiliated site collaboration; competency based curriculum objectives; standardized competency aligned on-boarding; and preceptor-evaluated performance. The experiential education is designed for academic medical centers (AMCs) to foster the development of qualified research coordinators. The CRE model supports “teach one, see one, do one” coupled with preceptor-evaluated feedback to cultivate clinical research competency.

We used a Zoom Un-meeting as an educational approach to provide experienced clinical research professional (CRP) adult learners a collaborative learning space to learn more about current issues for academic medical center (AMC) clinical research workforce development and collaborate on solution finding. CRPs operationalize the conduct of clinical trials and represent a significant brain trust for the Clinical and Translational Science (CTSA) consortium hubs with their vast knowledge base, extensive experience, understanding of relevant institutional policy, organizational culture, and clinical research operations. Un-meetings are an intentionally organized and coordinated group activity that encourages participants to focus on a topic and incorporate an open flow of ideas through brainstorming and an open discussion format, setting the stage for future collaborative action. We divided topics into a series of six consecutive monthly Un-meeting Zoom workshops. Ultimately, one resulting output from the meeting was the Center for Leading Innovation and Collaborations (CLIC) synergy paper award to support continued collaborative work. Currently, work teams have emerged to analyze qualitative data from brainstorming and breakout session recordings and to identify small-group activities. We describe this adult learning tool as valuable for exploring issues of AMC CRP professional development. This approach encouraged creative/critical thinking and opportunities for leadership, team science, and problem-solving among participants.

External advisory committees (EACs) are critical peer-review meetings that drive improvement at Clinical and Translational Science Award Program Hubs. Despite their ubiquity, evaluations of EAC optimization and effective implementation remain scarce. We present a two-tiered approach to optimizing EAC meetings through (1) in-depth, topically focused “pre-review” meetings comprised of external topic experts and at least one standing “full-board” EAC member, followed by (2) a traditional “full-board” EAC meeting. This approach allowed pre-review discussion of program-focused topics and specific recommendations, later delivered to the full-board for review and direction. To evaluate this approach, we interviewed 18 people who planned, administered, or attended pre-review and/or full-board meetings, including internal Hub staff, external topic experts, and standing EAC members. Thematic analysis was used to explore planning, implementation, and value of our two-tiered approach versus the traditional single full-board approach. Interviewees preferred the two-tiered approach, noting benefits including additional time to reflect, shared identification of strengths and challenges, and discussion of solutions to share later with the full-board. Those who attended pre-review meetings described building “transformational,” rather than “transactional,” relationships with invitees through more discussion and inter-hub sharing. That increased sharing invited more exploration, discussion, and planning of next steps toward innovation.

OBJECTIVES/GOALS: Contingency management (CM) procedures yield measurable reductions in cocaine use. This poster describes a trial aimed at using CM as a vehicle to show the biopsychosocial health benefits of reduced use, rather than total abstinence, the currently accepted metric for treatment efficacy. METHODS/STUDY POPULATION: In this 12-week, randomized controlled trial, CM was used to reduce cocaine use and evaluate associated improvements in cardiovascular, immune, and psychosocial well-being. Adults aged 18 and older who sought treatment for cocaine use (N=127) were randomized into three groups in a 1:1:1 ratio: High Value ($55) or Low Value ($13) CM incentives for cocaine-negative urine samples or a non-contingent control group. They completed outpatient sessions three days per week across the 12-week intervention period, totaling 36 clinic visits and four post-treatment follow-up visits. During each visit, participants provided observed urine samples and completed several assays of biopsychosocial health. RESULTS/ANTICIPATED RESULTS: Preliminary findings from generalized linear mixed effect modeling demonstrate the feasibility of the CM platform. Abstinence rates from cocaine use were significantly greater in the High Value group (47% negative; OR = 2.80; p = 0.01) relative to the Low Value (23% negative) and Control groups (24% negative;). In the planned primary analysis, the level of cocaine use reduction based on cocaine-negative urine samples will serve as the primary predictor of cardiovascular (e.g., endothelin-1 levels), immune (e.g., IL-10 levels) and psychosocial (e.g., Addiction Severity Index) outcomes using results from the fitted models. DISCUSSION/SIGNIFICANCE: This research will advance the field by prospectively and comprehensively demonstrating the beneficial effects of reduced cocaine use. These outcomes can, in turn, support the adoption of reduced cocaine use as a viable alternative endpoint in cocaine treatment trials.

Objectives/Goals: Digital recruitment can improve participant engagement in medical research, but its potential to introduce demographic and socioeconomic biases is unclear. This study investigates pathways participants took during a digital recruitment workflow in neurology, examining potential associations with socioeconomic and demographic factors. Methods/Study Population: As part of an ongoing study aiming to remotely capture speech from patients with neurologic disease, most participants seen in neurology on our campus are invited to complete a self-administered speech examination. We exported participant data from Epic (semi-automated identification and invitation), Qualtrics (eligibility screening), the participant tracking database (consent), and the recording platform (completion) for March to July 2024. Data visualization was performed using a Sankey diagram. Socioeconomic status was assessed using the housing-based socioeconomic status (HOUSES) index and area deprivation index (ADI) national rank. Kruskal–Wallis and Wilcoxon rank-sum tests were used to compare the median age, socioeconomic indices, and time taken to reach different steps of the study. Results/Anticipated Results: Of the 5846 invited participants, 57% were from urban areas, 23% from rural areas, and 20% from urban clusters. Most did not read/respond (2739) or declined (1749) the initial invitation via Epic. Of the 1358 interested participants, 415 completed the study. Participants from urban areas completed enrollment steps faster than those from rural areas and urban clusters, though the variance was large (42.6 ± 41.4 days vs. 50.6 ± 42.2 days and 50 ± 43.9 days, respectively; p  =  0.030). Female participants took longer to complete enrollment than males (48.7 ± 44 days vs. 40.5 ± 38.8 days; p  =  0.026). Participants who successfully finished the study had significantly lower ADI national ranks compared to other common pathways (40.6 ± 19; p  =  0.0021). No associations were found with the HOUSES indices. Discussion/Significance of Impact: Our findings support differences in participant engagement, with urban participants and males more likely to complete enrollment steps. Those who finished the study were less disadvantaged suggesting potential bias in digital recruitment. These findings can inform strategies to improve digital recruitment in neurology research.

Objectives/Goals: Conduct an evaluation of the Clinical Research Support Center (CRSC) model using a structured methodology, leverage insights to drive continuous improvement and evolution, and broadly disseminate outcomes to promote knowledge sharing and best practices for similar translational science initiatives. Methods/Study Population: We will utilize a structured case study approach, including adapting a translational science case study evaluation approach to assess impact as well as support practices, barriers, and facilitators that influence research translation. We will collect data from diverse sources. Primary data will come from structured interviews with stakeholders and a survey of a random sample of faculty and research staff. Secondary data includes grant applications, reports, and publications; public stories/media related to research supported by CRSC; scientific publications; and organizational documents. Results/Anticipated Results: The case study will identify the CRSC model’s impact on the research enterprise. Findings will articulate the specific strategies and practices the CRSC implemented to support clinical research; key factors, people, and resources that helped develop, improve, and promote CRSC services; significant milestones in evolution of the CRSC; and specific ways in which support services impact clinical research infrastructure and outcomes. The findings will highlight both strengths and areas for improvement. Early results show historical challenges with operational silos and resource limitations. Findings suggest CRSC facilitators include a team science approach with institutional support. Discussion/Significance of Impact: This case study will provide insights related to benefits, challenges, and facilitators of a translational science support model. Insights will guide the CRSC’s evolution and be broadly disseminated to promote knowledge sharing and best practices for future translational science applications.