OBJECTIVES/GOALS: The CDC estimates that Influenza infections account for an average of 420,000 hospitalizations and 34,700 deaths in the U.S. each year. This project explores the underlying mechanisms of the infectious process of Influenza A in human lung organoids by examining the differential transcriptomic expression compared to uninfected controls. METHODS/STUDY POPULATION: Lung organoids were cultured from differentiated human bronchial epithelial cells from lung transplant donors on an air-liquid interface until they were confirmed to contain both mucous producing and ciliated cells. Lung organoids are ideal models in translational science due to their structural and functional characteristics which closely mimic those of in vivo human epithelial tissue. Half the organoids were exposed to Influenza A pH1N1 for 72h; the other half served as uninfected controls. RNA was isolated from both groups and sequenced using the Oxford Nanopore MinION which generates full length reads. Reads were aligned to the human reference genome (GRCh38.p14) using Minimap2. RESULTS/ANTICIPATED RESULTS: The MinION sequenced an average of 3.24m reads per sample and a total of 13,128 genes were relevantly expressed (defined as greater than 1 read per million in at least half the samples). ANOVA with a 5% false discovery rate (Benjamini and Hochberg correction) revealed 5,417 differentially expressed genes between infected and control groups. Within this subset, we identified downregulation of mucociliary clearance, mitochondrial and ß-oxidation, peroxisome, and glutathione replenishment genes. We further identified upregulation in inflammatory markers, lactate dehydrogenase enzymes, and several s100 proteins. The downregulation of mitochondrial and β-oxidation markers and the upregulation of lactate dehydrogenase enzymes revealed a Warburg-like phenotype which has not previously been reported. DISCUSSION/SIGNIFICANCE: This study reveals a novel Warburg-like phenotype in Influenza A infection alongside downregulated mucociliary clearance and upregulated inflammatory processes. These findings improve our understanding of Influenza A infection and point to potential therapeutic targets to advance precision medicine approaches to treatment.

OBJECTIVES/GOALS: Familial Hypercholesterolemia (FH) is a common disorder that is vastly underdiagnosed and causes an increased risk for sudden cardiac death. Cardiology providers (CHCPs) are in an ideal position to care for patients with FH. This research aimed to assess the knowledge of CHCPs in the screening, diagnosis, and management of FH. METHODS/STUDY POPULATION: Adaptation of an existing knowledge tool guided survey development. FH knowledge domains included description of FH, prognosis, prevalence, inheritance, diagnostic criteria, and management options. CHCPs were asked to select their provider type (MD, PA, NP, RN) and years in clinical practice (less than 1-5 years, 6-10 years, 11-20 years, and greater than 20 years).Convenience and snowball sampling recruited CHCPs in the Division of Cardiology at Columbia University Irving Medical Center (CUIMC). Descriptive statistical analysis was performed on quantitative survey data using R. Frequency counts of provider type and years in clinical practice were calculated. Comparisons of scores between provider types and years in clinical practice were made using ANOVA. RESULTS/ANTICIPATED RESULTS: 70 surveys were analyzed (30.2% response rate). 50% of CHCPs identified as MDs, 24.2% as RNs, 12.9% as NPs, and 12.9% as PAs. With regards to clinical experience, 21.4% of CHCPs had 1-5 years, 25.7% had 6-10 years, 24.3% had 11-20 years, and 28.6% had greater than 20 years. The average overall score across all CHCPs was 55.4%, with the highest on the description knowledge domain (81.4% correct), followed by management (61.8%), diagnostic criteria (60.6%), inheritance (58.6%), prevalence (44.3%), and prognosis (25.2%). Physicians had the highest average score of 66.0%, followed by NPs (50.3%), PAs (49.7%), and RNs (39.3%). There was no significant difference in scores across experience levels, provider types, and knowledge domains based on experience levels. DISCUSSION/SIGNIFICANCE: CHCPs across all provider types and years of experience had limited FH knowledge. There exists an opportunity to improve CHCPs’ knowledge of FH through education (didactic knowledge) or practice (experiential knowledge). Future interventions should aim to increase didactic and experiential knowledge of CHCPs through a variety of methods.

OBJECTIVES/GOALS: Community-based participatory research is a “gold standard” methodology, yet many researchers lack the experience or resources to implement this approach. To make engagement more accessible, we developed and implemented a 3-part training series highlighting engagement as a spectrum with many options to meaningfully engage partners. METHODS/STUDY POPULATION: Staff at UNC-Chapel Hill’s CTSA and Cancer Center collaborated with patient and community partners to co-develop training content, structure, and delivery. Sessions were free and open to the public and covered key components of research engagement and its benefits, debunked common myths and misconceptions about engagement, outlined specific methods along the spectrum of engagement (from low to high touch), and described nuances of building and maintaining partnerships. Partners determined how to best incorporate their perspectives, developed content (including videos, audio clips, and quotes), and co-presented with UNC staff. Evaluations were collected after each session and feedback was incorporated into future iterations. RESULTS/ANTICIPATED RESULTS: 194 individuals from over 20 institutions have participated in the training. Of all survey respondents to date (n=74), 93% were very or extremely satisfied, 77% felt the training was very or extremely relevant to their work, and 76% were very or extremely likely to use information learned in the next year. Most helpful parts of the training were differentiating research engagement from participation; explaining engagement as a spectrum with varied methodologies; providing tools and resources to implement different approaches; and hearing directly from community co-presenters about their experiences engaging in research. Based on feedback, we created a workshop for researchers to develop engagement plans and an additional training for partners to build capacity and knowledge about engaging in research. DISCUSSION/SIGNIFICANCE: Engaging partners who are impacted by research can be instrumental to the success of a study. This training can help researchers identify engagement approaches that align with their goals, experience, and resources, as well as the interests and capacity of potential partners, and can serve as a model for those interested in training co-development.

OBJECTIVES/GOALS: To identify empiric neuropsychiatric symptom (NPS) clusters in behavioral variant frontotemporal dementia and to determine the role of early anxiety/depression on functional progression. METHODS/STUDY POPULATION: Analyses were conducted using data from the ARTFL-LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) study, an established consortium with an ongoing cohort study of FTD patients across 18 clinical sites which includes comprehensive cognitive, neuropsychiatric, and structural neuroimaging data. A polychoric cluster analysis was performed on subjects from the ALLFTD cohort [applewebdata%3A//044E463E-34DA-4677-9EDC-B8309D14C337#_msocom_1] with early-stage disease (N=145, male 61%, median age 62 years) in order to identify empiric NPS clusters. Cox proportional hazard regression was then used to examine the association between early affective symptoms in bvFTD and subsequent functional disabilities adjusted for age, sex, level of education, and FTLD CDR global score. RESULTS/ANTICIPATED RESULTS: We identified a four-factor model as the best fit for the data: (1) an affective cluster with prominent depression, anxiety, agitation, and irritability, (2) a disinhibited symptom cluster with prominent elation and disinhibition, (3) an obsessive symptom cluster with prominent obsessive/ritualistic behavior and hyperorality, and (4) a psychotic symptom cluster with prominent delusions and hallucinations. The hazard of developing impairments in transactions, language, self-care, meal preparation, and incontinence was significantly elevated in those with early affective symptoms (depression/anxiety). DISCUSSION/SIGNIFICANCE: In this study we show that, NPS cluster into four discrete groups: (1) affective symptoms, (2) disinhibited symptoms, (3) obsessive symptoms, and (4) psychotic symptoms. Anxiety and depression are prominent within the affective symptom cluster and are associated with accelerated functional decline in a number of domains.

OBJECTIVES/GOALS: Venous thromboembolism (VTE) is a major cause of morbidity and mortality. Due to its relatively low incidence, prospective studies are limited. This makes administrative claims a promising data source to study VTE. We sought to examine the reproducibility of results using different VTE definitions from the published literature. METHODS/STUDY POPULATION: We conducted a retrospective analysis of a random 10% sample of the 2010-2022 IQVIA LifeLink PharMetrics Plus™ database, an administrative claims database representative of the commercially insured population of the United States. We selected cancer patients undergoing major gastrointestinal surgery, who have a higher risk for postoperative VTE (deep venous thrombosis [DVT] and/or pulmonary embolism [PE]). VTE was defined using ICD-9-CM and ICD-10-CM codes using definitions from 4 individual published studies. We compared the 4 definitions with respect to the incidence of VTE and factors associated with post-discharge VTE using standard univariate and multivariable logistic regression models. The same logistic regression models were used for each of the 4 definitions. RESULTS/ANTICIPATED RESULTS: There were substantial differences in VTE coding among the 4 definitions (range 107 to 225 ICD-9/10 codes for DVT and 12 to 24 codes for PE). The eligible population comprised 2,360 patients (49% female) with a median age of 49 years (interquartile range 47-52 years). During the index surgery hospitalization, a total of 58, 62, 63, and 83 patients developed VTE using the 4 definitions. In the 2,126 patients eligible for VTE prophylaxis, a total of 108, 68, 73, and 107 patients developed post-discharge VTE (range for DVT 35 to 81, range for PE 39 to 76). On multivariable analysis, factors independently associated with VTE included age using 1 of 4 definitions, esophageal surgery type using 3 of 4 definitions, and liver surgery type and Elixhauser score using all 4 definitions. DISCUSSION/SIGNIFICANCE: The incidence of VTE is directly affected by differences in ICD-9/10 codes used. Definitions for important clinical outcomes should be standardized when using administrative claims data in order to improve reproducibility of findings.

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.

OBJECTIVES/GOALS: Policy makers are interested in understanding scientific collaborations that translate knowledge into population health. The objective of this study is to compare the translational research collaboration of the Hispanic Alliance of Clinical and Translational Research in 2020 and 2023 by using Social Network Analysis (SNA). METHODS/STUDY POPULATION: We conducted a systematic document review of all the Hispanic Alliance Calls for Pilot Projects from 2020 to 2023 including key attributes of the investigators and collaborators such as academic institution, highest degree, and collaborator type. Scientific collaboration was defined as two or more researchers working together in grant proposal for a pilot project application. Study data was recorded and tracked using an Excel spreadsheet. R Statistical software was used to analyze and map the networks resulting from collaboration interactions comparing the 2020 Call and 2023 Call. Network statistics were performed including nodes, isolates, edges, components, density, diameter, average degree, and the size of the main component. RESULTS/ANTICIPATED RESULTS: A total of 134 investigators comprised the overall network. The network are predominantly clinician (49.3%) and basic researchers (25.4%). Preliminary results shows that diversity of disciplines and affiliations in the collaborative relationships increased across time. Findings demonstrated that the number of nodes/actors increased from 16 to 65 comparing 2020 to 2023 and the edges/relationships from 12 to 53. The number of translational research cluster increased from 4 to 13 comparing 2020 to 2023. More extensive collaborative cluster occurred across time with over 15 researchers collaborating. A mentor was the key player connecting these research clusters. DISCUSSION/SIGNIFICANCE: This study provides critical data to mapping the IDeA CTR translational research collaboration patterns. Research collaboration increased across time. This innovative approach serves to foster data-driven decision-making to enhance collaboration, diversity, and program outcomes. It offers valuable insights for policy and practice.

OBJECTIVES/GOALS: Mayo Clinic (MC) launched the Rapid Activation Trial (RAT) pilot program in 2022 to expedite the activation of high priority and high impact clinical trials. The objective was to develop a process for rapid activation through robust screening, prioritization, and project management (PM) support. METHODS/STUDY POPULATION: The project team developed a robust screening and approval process for the RAT program using a combination of an objective scoring tool (based on strategic priorities) and a diverse selection committee to screen and approve eligible trials. Sponsors had to commit to RAT program timelines. Upon approval, trials were prioritized at the highest level within each business unit involved in the activation process. The number of trials approved annually were limited to 8 to manage volume and facilitate seamless prioritization with an activation timeline goal of 6 weeks. Project management support for RAT program focused on financial, regulatory, logistical, and operational elements to open trials expeditiously. RESULTS/ANTICIPATED RESULTS: In 2022, thirteen (13) applications were received and eight (8) were approved by the RAT selection committee. The approved trials activated with a median open to enrollment time of 6.4 weeks from engaging with business units. They also aligned closely with organization’s strategic priorities, including but not limited to Investigator Initiated Trials, Multi-Site protocols, IND/IDE protocols, Rare Diseases, First in Human and Commercialization potential trials. PI and study team feedback was positive. In 2023, the RAT program was renewed due to the pilot’s significant success in 2022. The goal is to open 10 trials and 5 have been activated by the end of Q3, 2023 with a median timeline of 6 weeks. DISCUSSION/SIGNIFICANCE: Rapid activation of high priority and high impact clinical trials enables an organization to strategically prioritize and open complex clinical trials. This allows the delivery of innovative, timely cures to patients in an expeditious timeline.

OBJECTIVES/GOALS: Compiling information about characteristics and progress of scholars is required for career development applications and progress reports. The range of information is substantial, and preparation is onerous. We sought to create a tool to facilitate gathering key data about trainees and mentors who participate in programs like NIH K- and T-awards. METHODS/STUDY POPULATION: Using the REDCap platform, we developed forms and surveys to support intake of applicants, updates from scholars, and information about their participation in activities and use of resources. We deployed application programming interfaces (APIs) to automate capture of publicly available data about publications, impact metrics, and federal grant funding. Similar tools capture descriptions of mentor expertise including grant funding, prior trainees, and publications with mentees We also built modules to 1) allow connection to institutional grant and contract data to capture foundation and other funding; 2) pre-populate follow-up surveys to update information about career trajectories with minimal scholar effort; and 3) support mentee-mentor agreements as living documents. RESULTS/ANTICIPATED RESULTS: After a pilot period at our institution, we disseminated Flight Tracker to more than 50 academic institutions, most of whom are CTSA hubs. They track scholars in TL1/T32s, KL2/K12s, MSTP programs, and academic groups. Beyond federal reporting, uses now include publication impact factors (relative citation ratios, Altmetrics scores), grant funding of groups, maps of network relationships among investigators, scholar receipt of internal pilot awards, and statistics about transition to independence and time-to-promotion. Scholars can be separated into smaller cohorts by demographics, training dates, and funding dates. Over 34,000 scholars are tracked nationally among over 260 programs. Having structured data supports program evaluation, continuous improvements, and documents program strengths. DISCUSSION/SIGNIFICANCE: We informally estimate Flight Tracker reduces staff and leadership effort in preparation of program data by 75%, preserving time to focus on service to scholars. Ready access to data over time and within and across institutions creates new opportunities for collaborative data analysis to support evidence-based career development.

OBJECTIVES/GOALS: Our overarching aim is to examine, in an African American population, cognitive, affective, and neurophysiological processes, as well as risk-taking behavior, in response to racial stigma cues. While accounting for individual differences, we aim to see how these processes and drug-cue reactivity are impacted or altered by exposure to racial cues. METHODS/STUDY POPULATION: Participants will be African Americans between 18 and 25 years of age, equally distributed across genders. We will recruit 75 participants in order to have adequate power to conduct our intended analyses—particularly pertaining to individual differences in risk behavior outcomes. Participants will be asked to complete demographic and self-report questionnaires. Participants will also be asked to complete computerized tasks while their physiological responses (heart rate, skin conductance, and electroencephalographic (EEG) data) are recorded. The tasks are as follow: resting, gambling, go/no-go, picture viewing (positive, negative, and neutral images), and a drug cue image set. These tasks will be repeated after the participant views a racial stigma image set to evaluate the impact of discrimination. RESULTS/ANTICIPATED RESULTS: Data from 18 participants has been collected. Data will be periodically preprocessed and validated (e.g., 1 participant was removed due to data recording errors, so the current valid Nis 17). Generally, we anticipate that behaviors and neural activity will be modulated across all tasks after viewing the racial stigma image set. Specifically, (a) cognitive and affective processing of singular events of racial stigma may indicate a stress response, (b) modulation from chronic experiences of racial stigma render neural systems increasingly sensitive to stigma cues, and thereby less equipped to regulate stress response, (c) the impact of these processes on altering risk behavior (may increase such behaviors), and (d) the impact of these modulations on altering drug-cue reactivity (may amplify reactivity). DISCUSSION/SIGNIFICANCE: The study will identify factors that contribute to stress and risk behavior among African Americans. A substantial gap continues to exist regarding the nature of risk behavior among African Americans, despite the fact that African Americans represent a health disparity population with unique vulnerabilities to health-relevant risk behavior.

OBJECTIVES/GOALS: Using biomarkers to identify vulnerabilities from cocaine use disorder (CUD) is a focus of recent investigations. Current clinical efforts focus on psychiatric recovery in CUD, however other body systems are missed. Applying blood-based transcriptomics to investigate how clinical conditions relate to CUD can alter current treatment approaches. METHODS/STUDY POPULATION: We conducted a comprehensive longitudinal study of 12 individuals (mean 53 yrs.; M/F ratio 9: 3) with CUD abstinent from cocaine. 44 blood samples collected repeatedly every 3 months for 9 months were bulk RNA sequenced. We began with phenotype harmonization grouping individuals with the following metrics; cocaine withdrawal, cue craving, generalized craving, perceived stress, and days of abstinence. We ran differential gene and transcript expression with time across grouping of metrics using the dream software and used the multivariate test to examine their associations. We used the association of gene-transcripts to determine genetic predispositions with clinical traits using the Multi-marker Analysis of GenoMic Annotation assessing their overlap to a reference GWAS database. RESULTS/ANTICIPATED RESULTS: Individuals were grouped in 2 clusters based on scores of cue craving, generalized craving, cocaine withdrawal, and 3 clusters based on days of abstinence from cocaine use. Gene-transcript(s) associationsrevealed genetic predisposition towards certain clinical conditions and substance use traits. Cannabis use disorder showed significant enrichment between the greater vs. lesser abstinent days, and lesser vs. least abstinent days at 9 months. The “drinks per week” trait showed significant gene enrichment between greater vs. lesser abstinent days at 9 months. Coronary artery disease was also enriched with greater vs. least abstinent days at 3 months. Lastly, significant baseline differences in predisposition to small vessel ischemic stroke were seen in responders with high vs low perceived stress. DISCUSSION/SIGNIFICANCE: These results from a robust and feasible pipeline suggest genetic predisposition in CUD for other substances and cardio-neurovascular diseases. This pilot study may lead to larger studies into whole genome-based blood biomarker approaches for monitoring abstinence and other clinical co-morbidities to be addressed in cocaine addiction recovery.

OBJECTIVES/GOALS: To describe the impact of Trial-CARE (Coordination, Acceleration, and Recruitment Enhancement), a centralized service core at Washington University (WU), aimed at enhancing the capability of investigator-initiated multi-site clinical trials at WU and partner CTSA institutions. METHODS/STUDY POPULATION: Through review of our marketing materials and service tracking system we defined the following Trial-CARE offerings: Infrastructure: Trial-CARE is a centralized service core at WU. Whereby, a team member is sourced to an investigator-initiated multi-site clinical trial (II-MCT) to ensure the achievement of study milestones across any phase of the clinical trial life cycle. Team: Our team consists of research professionals with expertise in II-MCT project management, data management, and administrative/regulatory management. Services: * One free 60-minute case consultation * Tiers of Service * Academic Research Organization (ARO) support * Clinical Coordinating Center * Data Coordinating Center * II-MCT project management support * Time-limited targeted support RESULTS/ANTICIPATED RESULTS: Trial-CARE has completed 94 consultations in support of WU and partner CTSA institutions enabling the streamlining of study start-up; guidance for study recruitment, implementation, and operations; and offering resources to foster career development. Consultations can be completed at any phase in the clinical trial lifecycle, with Trial-CARE completing: * 12% in the idea phase * 45% in the grant development and submission stage * 28% after funding has been awarded Top reasons researchers connect with Trial-CARE about II-MCTs: * regulatory guidance (40%) * general information about Trial-CARE Services and II-MCTs (35%) * protocol development (21%) * data management (20%) * study budgeting (20%) DISCUSSION/SIGNIFICANCE: In response to a WU wide survey, Trial-CARE plans to generate informational webinars and is creating a clinical trial tracking dashboard, to pro-actively offer support services to researchers prior to grant funding. The goal is also to increase the percentage of consultations completed in the idea phase and the grant development and submission stage.

OBJECTIVES/GOALS: We designed the Biocascade Exhaled Breath Sampler (BEBS) to characterize viral aerosol shedding among individuals with influenza and other respiratory virus infections. We first aimed to test the BEBS on volunteer COVID-19 cases and report the aerodynamic size distribution of exhaled breath aerosol particles carrying SARS-CoV-2 RNA. METHODS/STUDY POPULATION: From June 15 through December 15, 2022, we recruited 27 PCR-confirmed COVID-19 cases from a college campus and the surrounding community to provide 30-minute breath samples into a well-validated Gesundheit-II (G-II) exhaled breath aerosol sampler. Among these individuals, 17 provided an additional exhaled breath sample into the newly designed BEBS. We quantified samples for viral RNA using reverse transcription digital polymerase chain reaction (RT-dPCR) and determined the viral RNA copies collected within two aerosol size fractions (≤5 µm and >5 µm in diameter) from the G-II, and four aerosol size fractions (<1.15 µm, 1.15–3.2 µm, 3.3–8.2 µm, and >8.2 µm) from the BEBS. RESULTS/ANTICIPATED RESULTS: Individuals with a SARS-CoV-2 Omicron BA.4 or BA.5 infection shed virus in aerosols at an average rate of 7.5x103 RNA copies per 30-minute G-II sample, with 78% of the total RNA in aerosols ≤5 µm in diameter. Among the BEBS samples, 10% of the total viral RNA was detected in aerosols <1.15 µm, 43% in 1.15–3.2 µm, 37% in 3.3–8.2 µm, and 10% in the >8.2 µm size fraction. Based on viral RNA loads, our results indicate that exhaled aerosols ≤3.2 µm contribute the majority of SARS-CoV-2 inhalation exposure. DISCUSSION/SIGNIFICANCE: Our data provide additional evidence that respirable aerosols contribute to the spread of SARS-CoV-2. Thus, our data suggest that mitigation measures designed to reduce infectious aerosol inhalation, such as ventilation and the use of air cleaners and respirators, are needed to control the spread.

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.

OBJECTIVES/GOALS: Developing pharmacokinetic (PK) models to guide selective serotonin reuptake inhibitor (SSRI) dosing in youth is costly, time-intensive, and requires large numbers of participants. We evaluated the use of remnant blood samples from SSRI-treated youth and developed precision PK dosing strategies. METHODS/STUDY POPULATION: Following IRB approval, we used a clinical surveillance platform to identify patients with routine phlebotomy within 24 hours of escitalopram or sertraline dosing. Remnant blood samples were obtained from youth aged 5–18 years, escitalopram and sertraline concentrations were determined, and clinical characteristics (e.g., age, sex, weight, concomitant medications that inhibit sertraline or escitalopram metabolism) and phenotypes for CYP2C19, the predominant enzyme that metabolizes these SSRIs, were extracted from the electronic medical record (EMR). A population PK analysis of escitalopram and sertraline was performed using NONMEM. The influence of clinical variables, CYP2C19, and dosing was evaluated from simulated concentration-time curves. RESULTS/ANTICIPATED RESULTS: Over 21 months, we collected315 samples from escitalopram-treated patients (N=288) and 265 samples from sertraline-treated patients (N=255). In youth, escitalopram and sertraline exposure (concentrations over time) and specific pharmacokinetic parameters (e.g., clearance) were influenced by CYP2C19 phenotype, concomitant CYP2C19 inhibitors, and patient-specific characteristics. Escitalopram and sertraline concentrations from remnant blood samples were 3.98-fold higher and 3.23-fold higher, respectively, in poor metabolizers compared to normal metabolizers (escitalopram, p<0.001) and compared to normal, rapid, and ultrarapid metabolizers combined (sertraline, p<0.001). DISCUSSION/SIGNIFICANCE: Combining remnant blood sampling with pharmacogenetic-integrated EMR data can facilitate large-scale population PK analyses of escitalopram and sertraline in youth. This real-world approach can be used to rapidly develop precision SSRI dosing strategies, including slower titration and reduced target doses in CYP2C19 poor metabolizers.

OBJECTIVES/GOALS: The Community Research Liaison Model (CRLM) is a novel model to facilitate community engaged research (CEnR) and community–academic research partnerships focused on health priorities identified by the community. We describe the CRLM development process and how it is operationalized today. METHODS/STUDY POPULATION: The CRLM, informed by the Principles of Community Engagement, builds trust among rural communities and expands capacity for community and investigator-initiated research. We followed a multi-phase process to design and implement a community engagement model that could be replicated. The resulting CRLM moves community–academic research collaborations from objectives to outputs using a conceptual framework that specifies our guiding principles, objectives, and actions to facilitate the objectives (i.e., capacity, motivations, and partners), and outputs. RESULTS/ANTICIPATED RESULTS: The CRLM has been fully implemented across Oregon. Six Community Research Liaisons collectively support 18 predominantly rural Oregon counties. Since 2017, the liaison team has engaged with communities on nearly 300 community projects. The CRLM has been successful in facilitating CEnR and community–academic research partnerships. The model has always existed on a dynamic foundation and continues to be responsive to the lessons learned by the community and researchers. The model is expanding across Oregon as an equitable approach to addressing health disparities across the state. DISCUSSION/SIGNIFICANCE: Our CRLM is based on the idea that community partnerships build research capacity at the community level and are the backbone for pursuing equitable solutions and better health for communities we serve. Our model is unique in its use of CRLs to facilitate community–academic partnerships; this model has brought successes and challenges over the years.

OBJECTIVES/GOALS: Determine the exosome mitochondrial DNA (mtDNA) copy number in cerebrospinal fluid (CSF) as a measure of neuronal mitochondrial integrity in patients with subarachnoid hemorrhage (SAH). Determine the patterns of beta amyloid and tau protein biology in CSF of SAH patients and correlate those measures with the clinical status of the SAH patients. METHODS/STUDY POPULATION: The CSF is collected from SAH patients undergoing ventriculostomy-based continuous CSF drainage. Adults from all ethnicities and sex are included in this study. The exosomes are isolated from CSF samples using a precipitation method and particle count and size are measured using NanoSight. The DNA is extracted using an exosomal DNA isolation kit (XCF kit). The CSF mtDNA copy number is measured using digital drop PCR with mitochondrial DNA primers. The levels of beta-amyloid (a-beta-40 and -42) and tau protein in CSF are measured using a sensitive ELISA-based assay. A quantitative evaluation of mitochondrial DNA copy number, clinical status of the SAH patients and beta amyloid, and tau protein levels will be conducted and reported. RESULTS/ANTICIPATED RESULTS: Preliminary results of four CSF samples showed similar patterns in CSF exosome particle number, particle size and exosomal mtDNA copy number in relation to samples from the admission day. Particle number decreased with time while particle size increased. More patient samples will be analyzed to confirm the patterns. We anticipate that mtDNA copy number will correlate with brain beta-amyloid and tau protein levels. Moreover, we anticipate that the clinical status of the SAH patients will associate with the mtDNA copy number. We specifically predict that higher mtDNA copy number levels will correlate with better clinical outcomes. DISCUSSION/SIGNIFICANCE: Mitochondrial function is critical to brain health, but we lack effective ways to monitor this parameter. Here we focus on a CSF based biomarker, exosome-derived mtDNA, which is intended to reflect the integrity of brain mitochondria. As bioenergetic metabolism influences beta amyloid and tau biology, predicting those levels are important.