OBJECTIVES/GOALS: To examine the prevalence of new indications for existing drugs conducted by non-originator companies from 2015 to 2021 and determine how many could qualify for 505(b)(2) under the Food, Drug, and Cosmetics Act. METHODS/STUDY POPULATION: A search within Clinicaltrials.gov was conducted to identify phase 3 drug interventional studies completed from 2015 to 2021. Results were categorized by funding source and industry sponsored studies were further separated into originator- and non-originator companies using dailymed.com. An in-depth review of 2018 was conducted to understand the nature of the studies including indication, dosage form, and route of administration. RESULTS/ANTICIPATED RESULTS: According to clinicaltrials.gov, a total of 7148 phase 3 studies were conducted between 2015 and 2021. Most of these studies were funded by industry (4447, 66.21%), followed by other (2428, 33.97%), NIH (266, 3.72%), and government (62, 0.87%). In-depth examination of the studies completed in 2018 (n=1077) revealed similar pattern in that most were funded by industry (674, 62.58%) followed by other (356, 33.05%), NIH (43, 3.99%), and government (10, 0.93%). Some studies were funded by more than one type. Of the industry-sponsored studies, 623 were funded by originator companies and 51 by non-originator companies. A total of 49/674 of the industry sponsored studies were for new indications, with 42 studies conducted by originator companies and 7 conducted by non-originator companies. DISCUSSION/SIGNIFICANCE: The 505(b)(2) is a way for manufacturers to add new indications to drugs by non-originator companies. In 2018, 49/674 studies were conducted to pursue new indications with few, 7/49, conducted by non-originator companies. The product development landscape reveals few opportunities for entities pursuing the 505(b)(2) pathway for new indications.

OBJECTIVES/GOALS: Guided by the health belief model and social identity theory, we aim to identify socio-cultural and psychological factors that influence rural tobacco users a) participation in research and b) quitting tobacco use. We also explore how citizen scientists are perceived as disseminators of messages. METHODS/STUDY POPULATION: In Phase I of this multi-stage project, we are conducting in-depth interviews with approximately 30 tobacco users. Interviews are on-going, and have been conducted with 16 participants thus far from four rural counties in Florida. The interview consists of semi-structured questions and multiple validated questionnaires. Specifically, we ask a series of questions about participants’ barriers to participating in research, tobacco use history, and internet use and message preferences. Additionally, we include questionnaires on participants’ substance use, nicotine dependence, motivation to quit, and willingness to participate in research studies. RESULTS/ANTICIPATED RESULTS: Initial findings suggest that rural tobacco users have an overall positive perception of research, and many choose to participate in research for altruistic reasons (i.e. they want to help others). Further, participants noted described feeling stigmatized due to their tobacco use. Although most began smoking to fit in with their community, many now feel on the outs. Participants also reported logistical barriers to participating in research, including lack of transportation. DISCUSSION/SIGNIFICANCE OF IMPACT: Findings can inform the development of recruitment materials to resonate with rural adults, including by emphasizing the collective potential to help by participating. This interdisciplinary highlights areas for collaboration to enhance the reach of health education and public health messages.

OBJECTIVES/GOALS: To evaluate the clinical trial designs of stimulant medications approved for the treatment of adult Attention-Deficit/Hyperactivity Disorder (ADHD) and identify discrepancies between safety and efficacy outcome measure criteria. METHODS/STUDY POPULATION: There are 24 stimulants currently approved and marketed for the treatment of adult ADHD: 12 amphetamine (AMP)-based and 12 methylphenidate (MPH)-based formulations. A mixed methods review of clinical trials that have evaluated the safety and efficacy of these drugs will be performed using qualitative and quantitative data, including inclusion and exclusion criteria, primary and secondary outcome measures, manufacturer recommendations, and package inserts, as well as FDA recommendations for industry. After compiling a list of clinical trials for each of the 24 drugs, this information will be analyzed for themes and trends in the assessment of safety and efficacy with particular attention paid to differing criteria between individual drugs and/or the two subclasses of prescription stimulants. RESULTS/ANTICIPATED RESULTS: The FDA has published recommendations for ADHD medication clinical trial design, including suggested outcome measures utilizing validated assessment tools. However, the FDA notes that these assessments may be altered to fit study populations and indicate that other primary and secondary endpoint measures may be acceptable. As such, efficacy assessments for these drugs may vary greatly, and the specific criterion selected for each drug’s study population and outcome measures may suggest more specific indications and usage conditions for optimal efficacy. DISCUSSION/SIGNIFICANCE: Regulatory officials consider AMP- and MPH-based stimulants equivalent therapeutic options for the treatment of ADHD. A study of clinical trial criteria reveals that differing mechanisms have been used to evaluate safety and efficacy. This discrepancy may have implications that affect clinical decision-making and patient experiences.

OBJECTIVES/GOALS: There is universal recognition of the importance of team science and team leadership. We have developed a semi-quantitative translational science specific team leadership competency assessment tool and have begun implementation studies to assess the impact of personalized feedback on the team science leadership skills of KL2 Clinical Scholars. METHODS/STUDY POPULATION: To create the instrument, we employed a modified Delphi approach by conducting a thorough literature review on Leadership to concretize the relevant constructs, then used these extracted constructs as a springboard for the Rockefeller Team Science Educators (TSE’s) to discuss and refine the leadership domain areas, collectively create domain-specific survey items. Further discussion helped refined the number, grouping, and wording. Scholars also contributed feedback in item development. We piloted the Leadership Survey by having all of the Rockefeller TSEs rate Clinical Scholars, and having each Scholar rate themselves. Each item was answered using a six-point Likert scale where a low score indicated poor expression and a high score represented excellent expression of the specific leadership attribute. RESULTS/ANTICIPATED RESULTS: Incorporation into a REDCap data base made consenting and rating process by TSE’s and the Scholars straightforward. The a priori domains (Foundational Leadership Competencies, Professionalism, Team Building and Team Sustainability, Appropriate Resource Use and Study Execution, and Regulatory Accountability) had high internal validity and good internal factor structure. The congruence between TSE and Scholar self-ratings were uniformly high, and discordance was often a function of “confidence” and “modesty” on the part of the scholar, rather than deficiency. Supporting comments were informative about performance barriers and mechanisms for improvement. Return of results allowed for the exploration of training gaps. Scholars were surveyed to gauge their reaction to the formal feedback. DISCUSSION/SIGNIFICANCE OF IMPACT: This quantification of team science leadership constructs has allowed for A)- the articulation of constructs essential for successful Translational Scientists to acquire during their training, B)- identification of gaps in that training and skill set, and C)- mechanisms for bolstering any identified gaps in these essential leadership constructs. CONFLICT OF INTEREST DESCRIPTION: None

OBJECTIVES/GOALS: Glioblastoma (GBM) is the most malignant brain tumor in adults and remains incurable with an average survival of 15 months after diagnosis. There is great need for treatment options without side effects that are devastating to the quality of life for patients. GBM tumors can circumvent cellular damage by upregulating antioxidant production. METHODS/STUDY POPULATION: Highly aggressive tumors tend to exhibit increased oxidative metabolism, and thus rely on a mechanism to eliminate reactive oxygen species (ROS) in order for cells to evade autophagy and cell death. We propose that recurrent GBM cells achieve this is by promoting methionine metabolism, upregulating glutathione production and preventing ROS accumulation. We investigated the expression of AHCY and MAT2A, two key enzymes in the methionine pathway, at the gene and protein level in both GBM and non-GBM tissues. We probed for markers of cell death following pharmacological inhibition and siRNA knockdown, and performed metabolite-mediated rescue experiments. Finally, we evaluated changes in cellular respiration using the Seahorse XFe96 real-time mitochondrial stress test following inhibitor treatment. RESULTS/ANTICIPATED RESULTS: The selective AHCY inhibitor markedly reduced cell viability in different cancer cell types, but significantly reduced cell viability in recurrent GBM cells compared to newly diagnosed GBM (p=.009; MD: -0.828, 95% CI -1.350 to -0.306) and normal astrocytes (p=.073; MD: -0.609, 95% CI -1.305 to 0.085). AHCY and MAT2a protein expression appeared to be higher in GBM cells compared to normal astrocytes, medulloblastoma cells and other cancer cell lines. Genetic knockdown of AHCY and MAT2A demonstrated reduced cell viability, increased Caspase, SOD2, LC3-II and Transferrin receptor expression. Acute treatment with the AHCY inhibitor induced cell death, markedly reduced oxygen consumption rate and ablated spare respiratory capacity in recurrent GBM cells compared to newly diagnosed GBM cells. DISCUSSION/SIGNIFICANCE: Oxidative damage was induced following interference with key methionine pathway enzymes by pharmacological inhibition, while a similar concentration of drug largely preserved normal astrocyte viability. These results point to a novel targetable mechanism of disease progression and expand the realm of treatment options for recurrent GBM.

ABSTRACT IMPACT: The existing literature describing immune-related adverse events (irAE) has predominantly focused on clinical trial populations, which may not be representative of the broader population receiving immune checkpoint inhibitors (ICI), so we sought to perform a comprehensive evaluation of irAE in a real-world population of cancer patients being treated with ICI. OBJECTIVES/GOALS: With a cohort of patients with malignancy treated with ICI, we characterized incidence, severity, timecourse of ir-AE. We sought to inform providers who prescribe ICI to recognize the clinical burden of irAE in an effort to more effectively communicate the benefits and risks of ICI with patients. METHODS/STUDY POPULATION: After obtaining approval from the institutional review board, we used a pharmacy database to identify adult cancer patients treated with an ICI between January 2014 and October 2018. We used electronic medical records to obtain baseline variables. Each patient was followed at each clinic visit for 12 months for development of a physician-reported irAE.

For irAE, site and grade were recorded as documented by the provider. At diagnosis and each follow-up visit, we collected: 1) adjustments to ICI, immunosuppression, and hormone therapy.

Continuous variables were summarized using mean and standard deviation (SD) or median and interquartile range (IQR). Categorical variables were summarized using frequencies and percentages. Time to development and resolution of irAE were calculated using Kaplan-Meier curves. RESULTS/ANTICIPATED RESULTS: Among 131 patients, two-thirds were men, and 60% were Caucasian with a mean age was 65 years. Nearly 40% had an Eastern Cooperative Oncology Group performance score of 2 or higher. A small proportion (3.1%) had an autoimmune disorder. Nearly half had lung cancer (49.6%), and several had received radiation (33.6%). Over 70% were former or current smokers. In total, 57 patients (43.5%) developed an irAE, resultng in a total of 95 irAE, at a median of 208 days (126 days, not reached). The most common irAE included dermatitis, thyroiditis, pneumonitis, and hepatitis. Of 95 irAE, half were grade 1, 30% were grade 2, and nearly 20% were grade 3 or higher. Median time to resolution was 85 days (56-183 days). DISCUSSION/SIGNIFICANCE OF FINDINGS: This study demonstrates that irAE are clinically impactful in this relatively unfit, medically complex population, which may be a more accurate reflection of patients receiving ICI in everyday practice. This study showcases that this population is susceptible to irAE, although this needs to be examined in larger, prospective trials.

Objectives/Goals: Both diabetes and obesity are major health issues in the USA. Though much focus is given on the impact of lifestyle modifications to control diabetes and obesity, more information needs to be established about the association of social determinants of health and them. This study explores these associations, focusing on the DMV area. Methods/Study Population: The data for this study were collected for 158 counties which cover two states Maryland and Virginia, and Washington DC from PolicyMap. PolicyMap is a geography information system (GIS) that aggregates different types of data from different sources for research purposes. County-level data on public health related to different SDoH like median age, and percentages proportions of different ethnicity (Hispanic or Latino), percentages of different race, and nativity (foreign born), gender (ratio of male to female), access to primary healthcare, social vulnerability index (SVI), and median household income was used in this study. Statistical methods like multiple regression, one way ANOVA, and Pearson’s correlation coefficients were used to determine which factors are associated with these two conditions. Results/Anticipated Results: For both diabetes prevalence and obesity, multiple linear regression model with backward elimination was used to select variables which associated with them. The backward elimination process selected the set of factors for which the adjusted R square was the highest. In both cases, median household income, median age of population, social vulnerability level, percentage of white population, and percentage of foreign-born population were found to be significant at 5% level of significant. Pearson’s correlation coefficients showed significant positive relationship between factors like obesity and diabetes, median age and access to health care, and negative relationship between obesity and foreign born. Income, healthcare access, and white population were found to be significantly different SVIs from ANOVA. Discussion/Significance of Impact: This research study found that some SDoH affect diabetes and obesity in the same direction. The association is positive for median age and negative for income, SVI, percentage of white population, and foreign born. The associations were found between actionable and non-actionable factors like percentage of white population with access to health care.

OBJECTIVES/SPECIFIC AIMS: National concerns about IRB-related research delays have led to re-assessment of IRB review processes at institutional levels. We sought to address whether a dedicated IRB Liaison Service at the Irving Institute’s central location could provide additional useful staff support to the investigator community for interactions with the IRB at various levels of protocol submission. METHODS/STUDY POPULATION: We evaluated the results of a user satisfaction survey and performed a focused in-depth analysis of Liaison Service impact. An online tracking and satisfaction survey was implemented for researchers to complete following each consultation. The goal was to gauge the uses, user types and usefulness of the Service, and to follow-up with researchers who might have additional questions. Data was gathered about users of the Service and their affiliations, and the topics and questions that were discussed. A terse summary was drafted to categorize each consultation that was conducted during office hour sessions. Additionally, surveys were emailed to researchers to gauge their experience with the Service and their overall satisfaction. Users completed the survey either in person at the end of the consultation, or by email request sent immediately following each in-person consultation. The impact of the IRB Liaison Service on IRB protocol approval times was analyzed for a random sub-sample of protocols for which consultations were provided. Consultations for studies with an associated IRB protocol number (i.e., at least initially submitted) from May 2015-June 2017 had been assigned a number in an Excel file. Using a randomization formula, a subset of 90 protocols was identified for further analysis. Protocols that did not result in an IRB submission and duplicate entries were removed. The final dataset consisted of 67 protocols. Those protocols were assessed by type of review process (expedited versus full board review), by status (new submission, first return, second return, etc.), and by which of the seven IRB committees completed the review. Consultations for each protocol included in this subset were reviewed using the notes about that consultation. IRB records in Columbia’s online research oversight system, Rascal, were also reviewed to assess the timing of and issues raised in subsequent IRB review. Factors examined included whether the protocol was approved at next submission and if not, whether questions raised in subsequent IRB returns were related to the topics discussed in the consultation. RESULTS/ANTICIPATED RESULTS: Since its inception in January 2015 through June 2017 (2.5 years), a total of 501 in-person consultations have been performed, usually 25-30 per month. Users were primarily study coordinators and investigators. Most requests concerned new protocol development, policy questions or assistance in addressing IRB comments from submitted protocols. Survey response rate was 43%. Results of 215 competed satisfaction surveys were 100% positive. Of 67 unique protocols analyzed for outcomes of the consultation, 73% were subsequently approved within 14 days. DISCUSSION/SIGNIFICANCE OF IMPACT: Overall, we have found the Liaison Service to be a popular addition to research support, and plan to continue the service. We will continue to evaluate its user satisfaction and usefulness. Additional focus will be placed on whether the Service can improve approval times for human subjects research for protocols using the Liaison Service.

At least 70% of premature adult deaths result from behaviors starting and reinforced in adolescence. The use of adolescent-centered outcomes and the necessity of creating space for the adolescent voice regarding research that directly impacts them is often overlooked. These omissions result in proposals and solutions that lack consideration of adolescent ingenuity, preferences, and needs. In 2021, Penn State PRO Wellness was awarded a Patient-Centered Outcomes Research Institute Engagement Award with the goal of addressing the gap in the inclusion of adolescents in research focused on teenage health. The resultant Adolescent Health Network (AHN) was developed in partnership with a stakeholder advisory board comprised of adolescents, parents, health researchers, and school staff. The AHN currently consists of 12 schools and 43 adolescents who have completed stakeholder training. For adolescents, the AHN simulates a school club or career enrichment activity with incoming freshmen replacing graduating seniors over time. For health researchers, the AHN provides rapid, easy access to a pool of adolescents with stakeholder training who are available to provide input on various aspects of a study from recruitment plans, to survey tools to dissemination strategies. This manuscript details the development, execution, and data from this novel program.

OBJECTIVES/GOALS: Health care systems are complex, dynamic, and varied. Advances in artificial intelligence (AI) are enabling healthcare systems to use their own data to elicit patterns and design suitable interventions. To realize this potential, computer scientists and clinicians need an effective, practical, and replicable approach to collaboration METHODS/STUDY POPULATION: In this study, computer scientists partnered with clinicians to investigate predictors of avoidable emergency department use. The team sought an approach to computational medicine that could increase the relevance and impact of prediction to solve pressing problems in the health system. The team adopted an emergent architecture that engaged system leaders, computer scientists, data scientists, health services researchers, and practicing clinicians with deep ambulatory and inpatient knowledge to form the initial questions that shaped the prediction model; to understand nuances of coding and recording in source data and the implications for models; and to generate insights for promising points of intervention. The team recorded decisions and challenges as it progressed to analyze its function. RESULTS/ANTICIPATED RESULTS: Most avoidance models focus on a narrow time period around target events, or on high cost patients and events. This interdisciplinary team used their insights into the health system’s workflows and patient population to adopt a longitudinal approach to their prediction models. They used AI to build models of behavior in the system and consider prevention points across clinical units, time, and place. The holistic, systemwide focus enabled the team to generate insights that the system leaders and subsequently specific clinical units could apply to improve value and outcomes. A facilitated team process using learning system and cooperative network principles allowed a large and modular interdisciplinary team to build a transparent AI modeling process that yielded actionable insights into hypercomplex workflows. DISCUSSION/SIGNIFICANCE OF IMPACT: An architecture for involving diverse stakeholders in computational medicine projects can increase the relevance and impact of AI for solving care delivery problems in complex health systems. Translational science and computational medicine programs can foster this type of engagement and encourage a whole system perspective.

OBJECTIVES/GOALS: To identify factors enabling growing underage consumption of disposable Electronic Nicotine Delivery Systems (ENDS) by understanding young adults’perceptions and patterns of use of disposable ENDS through surveying college students. METHODS/STUDY POPULATION: Disposable ENDS are all-in-one devices with pre-filled nicotine liquid and a built-in battery. Recent data shows increased sales as users, including youth, are switching from pod-based to disposable ENDS. Gaps were identified via a literature review of current survey data revealing unknown information about disposable ENDS. Based on these data gaps, an anonymous survey was developed to gain insight into youth disposable ENDS use. The survey was distributed to college students via social media, university email chains, and flyers with QR codes. Responses were analyzed to identify trends and correlations in disposable ENDS use among college students. The survey was approved by USC IRB, Study ID: UP-22-00023. RESULTS/ANTICIPATED RESULTS: Between March 6 and October 28, 2022, 166 completed survey responses were collected; 158 were students. 80.4% (127/158) of surveys were eligible for analysis with the following criteria: 18-20 years old, under the US legal age to use ENDS. Of respondents aged 18-20, 57.5% (73/127) reported using ENDS at least once. 79.5% (58/73) of underage respondents used disposable ENDS and 72.9% (51/70) reported disposable ENDS as their usual device. 93.0% (53/57) of underage users reported using a flavored product, 56.1% (32/57) reported Flum®as their usual brand, 48.2% (27/56) reported convenience of use as the most attractive aspect of disposable ENDS, and 46.4% (26/56) obtained disposable ENDS from a convenience store. Of all disposable ENDS-using respondents, 98.7% (75/76) used for the first time while under the age of 21. DISCUSSION/SIGNIFICANCE: The survey continues to be open for data collection, with the goal of obtaining additional data. The goal with the additional data will be to create a comprehensive list of identified risk factors influencing underage disposable ENDS use and to suggest specific regulatory and policy reform to better address underage nicotine addiction.

ABSTRACT IMPACT: Quantification of neonatal THC exposure will allow for better insight into how THC exposure correlates with neurodevelopmental outcomes. OBJECTIVES/GOALS: Tetrahydrocannabinol (THC) use has become increasingly prevalent in recent years, including among pregnant women. However, few, if any, clinical studies have quantified precise in utero exposure levels of THC during pregnancy. Our study aims to fill this gap by using analytical methods to quantify THC in mother and baby following prenatal THC use. METHODS/STUDY POPULATION: Pregnant women were asked to give a self-report of all cannabis and cannabinoid use during pregnancy, including dose, frequency, and route of consumption. Upon arrival at the labor and delivery unit, maternal blood samples were collected. Immediately following birth and 24 hours after birth, umbilical cord and neonatal blood samples were collected, respectively. All blood samples were analyzed using tandem liquid chromatography-mass spectrometry (LC-MS) for the presence of THC, tetrahydrocannabinol carboxylic acid (THC-COOH), and hydroxy-tetrahydrocannabinol (THC-OH). Maternal THC and metabolite levels were compared to both cord and neonate samples. RESULTS/ANTICIPATED RESULTS: To date, we have collected 3 mother-infant sample dyads and 4 mother-infant control samples. We anticipate collecting a total of 20 mother-infant samples from each group. We will quantify levels of THC and its metabolites in maternal samples and compare these to cord and infant samples. We expect that THC/metabolite levels will vary as a function of dose and frequency of consumption. We also expect that THC/metabolites will be higher in umbilical cord blood relative to neonatal blood. DISCUSSION/SIGNIFICANCE OF FINDINGS: This study is among the first to directly measure exposure in the neonate following prenatal cannabis use. Quantification of THC/metabolite concentrations will be supplemented with developmental evaluations of infants at 6 and 12 months of age in order to gain better insight into how THC exposure correlates with neurodevelopmental outcomes.

OBJECTIVES/GOALS: Irritability, a proneness to anger and frustration, is a transdiagnostic symptom associated with poor mental health outcomes. Levels of irritability vary across development and high-risk trajectories have been observed. This study aims to use machine learning to predict irritability trajectories across the transition to adolescence. METHODS/STUDY POPULATION: Data were from the Adolescent Brain Cognitive Development (ABCD) Study, which is a 10-year longitudinal study that tracks the brain development, cognitive skills, physical health, and psychosocial functioning of a large, national sample starting from preadolescence. The baseline sample consisted of 11,861 9-10-year-old preadolescent youth. Irritability was parent-rated at baseline, 1-year, 2-year, 3-year, and 4-year follow-ups on the Child Behavior Checklist (CBCL) irritability index. Latent class growth analysis (LCGA) was used to determine developmental trajectories of irritability. Two machine learning approaches were applied to develop predictive models of youth irritability developmental trajectories. We used baseline (preadolescent) variables that spanned a wide range of domains. RESULTS/ANTICIPATED RESULTS: Preliminary results fromthe LCGA indicated best support for a four-class model that differentiated growth trajectories in irritability across the transition to adolescence: 1) persistent low irritability (n = 8691, 73.27%), 2) moderate irritability and decreasing (n = 1257, 10.60%), 3) low to moderate irritability and increasing (n = 1295, 10.92%), and 4) chronic high irritability (n = 618, 5.21%). We expect the machine learning analyses to generate predictive models with acceptable accuracy. We hypothesize that the most important predictors in the models will originate from the youth mental health domain, including baseline youth irritability, externalizing symptoms, internalizing symptoms, and oppositional behaviors, and the parent psychopathology domain, particularly parent irritability. DISCUSSION/SIGNIFICANCE: The present study elucidates unique developmental trajectories of irritability and generates predictive models to classify high-risk irritability trajectories using machine learning approaches. Clinicians can use these predictive models to identify at-risk youth and provide early intervention to preadolescents at high risk.

OBJECTIVES/SPECIFIC AIMS: Because clinical trial results are instrumental in the approval of a new drug or changes to the practice of medicine, ensuring the accuracy and validity of collected data is critical in the clinical trial process. This function, routinely carried out by clinical trial monitors in industry-sponsored trials, is often lacking in investigator-initiated trials (IITs) conducted in academia. To address this challenge, we have developed a self-study module that can be used to cross-train academic researchers in essential concepts and practical approaches to monitoring. Furthermore, we are applying a framework drawn from implementation science in the development and launch of this initiative. This framework, as used in other educational programs, is employed here to close the gap between initiative and practice, thereby effectively disseminating this training would improve the quality of clinical trials in academia. METHODS/STUDY POPULATION: This research project applied exploration, installation and implementation stages of the implementation science process by 1) exploring the need for a new initiative, 2) disseminating results, 3) engaging stakeholders, 4) creating standard operating procedures (SOPs) for installation and implementation, 5) studying user satisfaction and effectiveness, 6) addressing feedback and 7) conducting implementation. RESULTS/ANTICIPATED RESULTS: From literature review and internet searches we determined that although numerous GCP training resources exist, most are too broad and lack the practical approaches to meet the complex requirements of monitoring. Moreover, most of the offerings identified are costly or inaccessible. With only about 65% of IITs reported as being monitored (Figures 1 and 2), it appears that there is a clear need for training tools that are easily available to a broader audience. And because monitoring skills are substantially different from those associated with research coordination, it is not surprising that research professionals believed that they would need additional training to become proficient. To address this need, we began developing a monitoring module. We engaged key stakeholders from academia and industry to gain insights into their needs. The results indicated that although our training module was effective, supplementary information on the fundamentals of clinical trials should be included for those new to the field. After incorporating suggested changes and completing the module, we conducted user testing to determine if our module is ready to be broadly disseminated (Figures 3 and 4). Following positive feedback from the group, we are currently in the process of disseminating our module and studying its impact. DISCUSSION/SIGNIFICANCE OF IMPACT: IITs are instrumental in translating academic research into product development. Deficiencies in the quality control of these trials can lead to inadequacies in data accuracy and validity that could lead to significant delays in bringing innovative therapies to patients. Recent NIH policies require data and safety monitoring for all of the trials it supports. The latest addendum to ICH GCP, E6(R2), discusses a need for quality management across the clinical trial lifecycle. As we continue to disseminate and share information during the development of our self-study monitoring module, we are engaging key stakeholders from academia, government, and private institutions to understand and address quality challenges in conducting clinical trials. Finally, this research informs dissemination and implementation research, specifically for creating training for academic research professionals.

OBJECTIVES/GOALS: Transcriptional adaptation is a phenomenon in which a mutation in one gene leads to the genetic compensation of another homogenous gene. Understanding the mechanism of transcriptional adaptation may contribute to an explanation for variation in clinical manifestations of rare Amyotrophic lateral sclerosis patient phenotypes. METHODS/STUDY POPULATION: The presence of a premature termination codon triggers transcriptional activation. Therefore, we utilized CRISPR-Cas9 tool to generate a premature termination codon in CHCHD10 gene in multiple types of cells, including induced pluripotent stem cells derived from patient samples with known CHCHD10 mutations causative for Amyotrophic lateral sclerosis. CRISPR-Cas9 tool was delivered via ribonucleoprotein electroporation and transfect cell’s DNA was sequenced to validate gene editing. To confirm transcriptional adaption, changes in levels of protein and gene expression will be measured via immunoblot and quantification of CHCHD10 and CHCHCD2 from whole cells lysates of the edited cells. RESULTS/ANTICIPATED RESULTS: We anticipate that CHCHD2 transcriptional adaptation can functionally compensate for the locus loss of function of CHCHD10. This mechanism of transcriptional adaptation may contribute to an explanation for variation in clinical manifestations of patient phenotypes. DISCUSSION/SIGNIFICANCE: Our approach would advance discovery science towards by exploring transcriptional adaptation mechanism in humans, which can lead to novel therapies for rare Amyotrophic lateral sclerosis, such as CHCHD10.

Objectives/Goals: Our goal was to determine whether a consensus exists around 1) what the main barriers to innovation in Health artificial intelligence (AI) are 2) where there are gaps in education and training in Health AI and 3) where in their workflows organizations should implement AI to see the most immediate impact on productivity. Methods/Study Population: We employed a three-round Delphi method survey to stakeholders with health and/or engineering expertise. The first round was open-ended to generate responses to the three research questions. The second round asked participants to rank the responses and provide feedback as to their reasoning. The third round provided aggregated results and feedback and asked participants to re-rank the responses. Participants were attendees at a conference that brought people with health and/or engineering backgrounds together to discuss innovation in Health AI. 55 people in total participated across the three rounds. Results/Anticipated Results: Consensus emerged on all three questions: lack of trust was seen as the single greatest barrier to innovation, experience with implementation as the greatest gap in training, and automating health documentation as the point of most immediate impact. Consensus also emerged as to which of the 10–15 responses to each question were top priorities, which were somewhat significant, and which were not that important. Some of the rankings (such as implementation) seemed to reflect hot topics of discussion at the conference, but others (such as documentation) only emerged as significant in the surveys. Discussion/Significance of Impact: We successfully employed the Delphi method to discover what stakeholders think about three important questions in Health AI. Interestingly, although we polled experts from both health and engineering backgrounds, their answers converged on all three questions.