Little has been published on the demographic composition of the clinical and translational science research workforce within the Clinical and Translational Science Awards (CTSA) Program despite the well-documented need for greater diversity in the biomedical research workforce. Analyses of workforce demographic reveal that women and members of underrepresented groups remain persistently underrepresented in the CTSA hub and training components principal investigators. In contrast, in the CTSA Program career development and training programs, females have greater representation as participants, and non-Whites were better represented in training programs.

OBJECTIVES/GOALS: Regardless of their career choices, today’s biomedical researchers need to blend great science with core skills ininnovation and entrepreneurship (I&E). The objective of this NIH-funded education program was to develop and test a pragmatic training program to teach relevant I&E skills. METHODS/STUDY POPULATION: We used a modified Delphi approach to identify 15 relevant competencies for I&E and the essential topics to include in the program. Learner interviews identified preferences for online training programs (short, high-quality audio-visual content, ability to self-navigate, peer and instructor interactions). The inaugural program included 7 short, online courses that addressed how to identify and validate opportunities for innovation, sell your innovation to diverse audiences, assess its ethical consequences, work in teams, and develop resilience as an innovator. It also included mentor support, a team-based capstone project, and an optional in-person boot camp. RESULTS/ANTICIPATED RESULTS: 51 students enrolled and 41 participants from 9 institutions completed the program, including pre- and post-doctoral students and junior faculty. They organized into 10 teams to complete the capstone project, with 6 teams pitching their innovation to fellow students and mentors at the boot camp. Students rated satisfaction with courses highly overall, with 79% stating they would be disappointed if the program was no longer available. Preliminary results suggest participants increased their knowledge about and ability to perform tasks taught throughout the program. Suggestions for improvement included providing more practical advice and real-world examples to complement educational videos. DISCUSSION/SIGNIFICANCE OF IMPACT: The inaugural E4B program was well received and effective in increasing I&E skills. Improvements will include increased opportunity for mentor interactions and for advanced entrepreneurial training. The program is open for biomedical research trainees from all institutions with a CTSA award.

OBJECTIVES/GOALS: The rates of computational phenotyping algorithm reuse across health systems are low, leading to a proliferation of algorithms for the same trait. We propose a framework for reusing computational phenotyping algorithms and describe the real-world deployment of this framework for the development of the Colorado Diabetes EHR Research Repository. METHODS/STUDY POPULATION: The novel phenotype reuse framework consists of 4 steps: select algorithms that are appropriate for reuse by assessing whether they are fit for purpose; extend the algorithm to account for changes in data and care practice standards; localize the algorithm to use local database standards and terminologies; optimize the algorithm by applying a data driven approach to achieve the desired local performance. To identify individuals with type 1 diabetes (T1D) or type 2 diabetes (T2D), we selected and implemented T2D algorithms in a cohort of adults with any diabetes or pre-diabetes related diagnosis code, medication, or abnormal glucose-related laboratory test in the clinical data warehouse for UCHealth and the University of Colorado. RESULTS/ANTICIPATED RESULTS: We included a total of 926,290 patients who were identified by initial filters. Patients were more likely to be female (53%), identify as non-Hispanic white (69%) and had a median age of 58 years (IQR: 41, 70). Implementation, extension, localization, & optimization through iterative chart review prioritized high sensitivity for all-cause diabetes and high specificity for T1D and T2D. Of the original cohort, 252,946 (27%) were identified by the all-cause diabetes algorithm. Of these 11,688 were identified as T1D and 135,588 as T2D. After optimization the all-cause diabetes algorithm had 88% sensitivity, 90% specificity, 74% positive predictive value (PPV), and 96% negative predictive value (NPV). Our algorithms for T1D and T2D had high specificity (100% and 99%, respectively) and PPV (100 and 96% respectively). DISCUSSION/SIGNIFICANCE: Developing computational phenotyping algorithms is expensive and time consuming, yet algorithm reuse is low due to a lack of practical approaches for reusing algorithms. We demonstrate application of a novel framework for algorithm reuse, yielding good alignment of algorithm performance with study goals for identifying individuals with diabetes.

ABSTRACT IMPACT: This study highlights the importance of creatine in developmental myelination and remyelination to investigate whether creatine provides a therapeutic value during a central nervous system (CNS) demyelinating insult with a potential value in patients with Multiple Sclerosis. OBJECTIVES/GOALS: Creatine is vital for ATP buffering in the brain. Interestingly, the cells that generate myelin express the main enzyme for creatine synthesis, Gamt. Patients with Gamt mutations display intellectual delays and impaired myelination. Therefore, we hypothesize that creatine is essential for developmental myelination and improves remyelination. METHODS/STUDY POPULATION: To investigate these hypotheses, we developed a new transgenic mouse model with LoxP sites flanking exons 2-6 of the guanidinoacetate methyltransferase (Gamt) gene where excision leads to expression of a green fluorescent tag allowing us to track the cells normally expressing Gamt. We used immunohistochemistry techniques to look at the corpus callosum, the main white matter tract in the brain, and evaluate the number of oligodendrocytes (OL), glial cells responsible for generating myelin. We also used the cuprizone model of toxic demyelination to investigate whether dietary creatine and cyclocreatine, a planar analog of creatine that more efficiently crosses the blood-brain barrier, can enhance remyelination. RESULTS/ANTICIPATED RESULTS: In this mouse model, we show a 95% (+/-0.47%, n=3) co-localization of Gamt within mature OL during postnatal (P) day P14 with no co-localization in neurons or other glial cells. This suggests that mature OL are the main cells making creatine in the CNS. Next, we show that knocking out Gamt leads to a significant reduction in OL in the developing corpus callosum, at P14 and P21 (P14: 0.007, n=3; P21: 0.04, n=3). We also show that creatine supplementation causes a trending increase in mature OL density in the corpus callosum following cuprizone demyelination (2% creatine; p=0.052; n=4). Interestingly, cyclocreatine supplementation significantly increased mature OL density in the corpus callosum following cuprizone demyelination (0.1% cyclocreatine; p=0.034; n=4). DISCUSSION/SIGNIFICANCE OF FINDINGS: These studies highlight the important role creatine plays in developmental myelination and remyelination to investigate whether creatine and cyclocreatine provide a therapeutic value during a CNS demyelinating insult. This work investigates a potential therapeutic value of creatine to patients with Multiple Sclerosis.

OBJECTIVES/SPECIFIC AIMS: Chronic obstructive pulmonary disease (COPD) is a leading cause of both hospitalizations and readmissions in the United States, and about 1 in 5 hospitalized patients with COPD will be readmitted within 30 days. COPD-focused self-management programs are frequently used to help patients better manage their symptoms and prevent hospitalization. However, while the majority of patients with COPD have at least one comorbidity, most trials of COPD self-management programs either excluded patients with significant comorbidities or did not analyze the impact of comorbidities on patient outcomes. Using data from the BREATHE trial of a COPD self-management program, this study aims to determine if patient post-intervention outcomes differ based on the intensity and type of patient comorbidities. METHODS/STUDY POPULATION: In total, 240 patients hospitalized for COPD were randomly assigned to either a comprehensive self-management intervention or usual transitional care. Primary outcomes for this trial were the number of COPD-related hospitalizations and emergency department visits at 6 months and changes in COPD-specific quality of life. To determine whether patient comorbidities modify the effect of the self-management intervention on readmission and quality of life outcomes, we will compare patient outcomes across groups stratified by comorbidity burden (Charlson Comorbidity Index) and type (baseline diagnosis of congestive heart failure, diabetes, and depression). In addition, we will use regression analysis with interaction terms to test for interaction between comorbidity burden/type and intervention assignment. RESULTS/ANTICIPATED RESULTS: We hypothesize that the effect of the self-management intervention will differ in patients with greater comorbidity burden due to competing medical demands for patients with multimorbidity. DISCUSSION/SIGNIFICANCE OF IMPACT: The results of this study will help clinicians better target disease-specific self-management programs to the groups of patients with COPD who are likely to receive the greatest benefit from this type of intervention.

This paper describes the development and validation of a new 32-item test of knowledge of good clinical practice (GCP) administered to 625 clinical research coordinators. GCP training is mandated by study sponsors including the US National Institutes of Health. The effectiveness of training is rarely assessed, and the lack of validated tests is an obstacle to assessment. The GCP knowledge test was developed following evaluation of two existing widely used GCP tests to ensure it accurately reflects the content of current training. The final GCP knowledge test demonstrated good reliability (α = 0.69). It is a valid and reliable instrument for measuring knowledge of GCP. The test will be useful in assessing the effectiveness of GCP training programs as well as individuals’ mastery of GCP content.

OBJECTIVES/SPECIFIC AIMS: About 75% of the estimated 2.5 million traumatic brain injuries (TBIs) diagnosed annually classify as mild TBI (mTBI); yet cognitive impairments associated with poor patient outcomes can persist for weeks to years. mTBI symptoms are difficult to measure objectively and often remain undiagnosed in the context of an unknown cognitive baseline. Formal neuropsychological exams hold limited utility due to their extensive resource burden. We aimed to define the clinical importance of a 4-question assessment of subjective cognitive complaints (SCC) in predicting return to work at 6 months following mTBI. METHODS/STUDY POPULATION: mTBI participants from the prospective Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot Study were included. A self-report affirmation to at least 1 of 4 subjective cognitive symptoms yielded positive SCC. Regression analysis was used to determine factors associated with return to work by 6-months. RESULTS/ANTICIPATED RESULTS: Of 479 enrolled participants with mTBI, 271 (57%) had complete follow-up data. Of which, 156 (58%) had at least sheltered employment at enrollment. Thirty-four (22%) of workers had no return to work at 6-months. Demographics, prior education, presenting injury severity, work status, and post-traumatic stress disorder were associated with return to work. SCC was associated with lower odds of return to work by 6-months (OR=0.11, p=0.01). DISCUSSION/SIGNIFICANCE OF IMPACT: We suggest a concise 4-question assessment of SCC may be clinically relevant in estimating the likelihood of return to work by 6 months post-mTBI.

When the emergency committee of the World Health Organization declared that the outbreak of COVID-19 meets the criteria of a “Public Health Emergency of International Concern” on January 30th, 2020, no one could ever imagine how soon it will spread globally, and a health crisis would turn to a social crisis that affects everything including higher education. However, during this uncertainty, Tehran University of Medical Sciences (TUMS) tried to respond quickly. In this study, we explain how a nerve center has helped TUMS respond to this crisis and ensure safety to keep key operations going, and set up a functional decision-making system for the future. We also share perspectives on the critical issues, the challenges ahead, and the opportunities emerging in the “new normal.”

The ACT Network was funded by NIH to provide investigators from across the Clinical and Translational Science Award (CTSA) Consortium the ability to directly query national federated electronic health record (EHR) data for cohort discovery and feasibility assessment of multi-site studies. NIH refunded the program for expanded research application to become “Evolve to Next-Gen ACT” (ENACT). In parallel, the US Food and Drug Administration has been evaluating the use of real-world data (RWD), including EHR data, as sources of real-world evidence (RWE) for its regulatory decisions involving drug and biological products. Using insights from implementation science, six lessons learned from ACT for developing and sustaining RWD/RWE infrastructures and networks across the CTSA Consortium are presented in order to inform ENACT’s development from the outset. Lessons include intentional institutional relationship management, end-user engagement, beta-testing, and customer-driven adaptation. The ENACT team is also conducting customer discovery interviews with CTSA hub and investigators using Innovation-Corps@NCATS (I-Corps™) methodology for biomedical entrepreneurs to uncover unmet RWD needs. Possible ENACT value proposition hypotheses are presented by stage of research. Developing evidence about methods for sustaining academically derived data infrastructures and support can advance the science of translation and support our nation’s RWD/RWE research capacity.