Clinical And Translational Science Award Program Research Articles

Translation in action: Influence, collaboration, and evolution of COVID-19 research with Clinical and Translational Science Awards consortium support.

The National Institutes of Health (NIH)'s Clinical and Translational Science Awards (CTSA) consortium aims to accelerate translational processes that move discoveries from bench to bedside. The coronavirus disease 2019 (COVID-19) pandemic presented unmatched challenges and applications for CTSA hubs nationwide. Our study used bibliometrics to assess features of COVID-19 publications supported by the national CTSA program to characterize the consortium's response to the pandemic. Our goal was to understand relative scientific influence, collaboration across hubs, and trends in research emphasis over time. We identified publications from NIH's curated iSearch COVID-19 Publication Portfolio from February 2020 to February 2023; 3234 peer-reviewed articles relevant to COVID-19 cited a CTSA grant. All 66 CTSA hubs were represented, with large-size and longstanding hubs contributing more publications. Most publications cited UL1 grants, 457 cited KL2/TL1 training grants, and 164 cited multiple hub grants. Compared to a random sample of non-CTSA-supported COVID-19 publications, the CTSA portfolio exhibited greater clinical relevance, more human research, and higher altmetric and citation influence. Results were similar for multi-hub publications involving networked initiatives like multi-site clinical trials or the National COVID-19 Cohort Collaborative. Shifts from molecular/cellular-oriented research toward human-oriented research over time were evident, demonstrating translation in action. Results illuminate how the CTSA consortium confronted the pandemic through high-quality projects oriented toward human research, working across hubs on high-value collaborations, advancing along the translational spectrum over time. Findings validate CTSA hubs as critical support structures during health emergencies.

The rocky road to translational science: An analysis of Clinical and Translational Science Awards

Abstract Studies point out that the productivity decline in biomedicine is in significant part due to difficulties in translating basic science into clinical application. To promote translational research, the US NIH launched the Clinical and Translational Science Awards (CTSA) program in 2006. Prior evaluations of the CTSA program often assumed that the key to translation is inter-organizational collaboration or multidisciplinarity; hence, changes in either of these were measured as evidence of translational science. However, using novel measures of translational science, this study examines the relationship between CTSAs and translational science per se. We define ‘translational science’ as basic science that has translational features, and we employ two distinct, complementary measures of translational science based on publication data. Using 115 Carnegie R1 universities and their translational science publications, we find that receiving a CTSA does not obviously cause receiving institutions to conduct more translational science. Furthermore, our Principal Investigator-level analysis shows that those who received direct support from the CTSA program had already generated more translational science than others and that their research behavior did not change significantly after receiving a CTSA. Future evaluation research can adopt our novel measures of translational science and evaluation research design in the assessment of translational research activities. Finally, we conclude with a discussion of the implications of our findings for science governance.

Attitudes towards diversity, equity, and inclusion across the CTSA Programs: Strong but not uniform support and commitment.

This study describes attitudes towards diversity, equity, and inclusion (DEI) among members of the Clinical and Translational Science Awards (CTSA) Program. It also explores associations between program members' roles and their perceived importance of and commitment to improving DEI and assesses the link between perceived importance of and commitment to improving DEI. Lastly, it ascertains barriers and priorities concerning health equity research, workforce development, CTSA consortium leadership, and clinical trials participation among respondents. A survey was administered to registrants of the virtual CTSA Program 2020 Fall Meeting. Respondents reported their roles, perceived importance of and commitment to improving DEI. Bivariate cross-tabulations and structural equation modeling examined associations between respondents' roles, perceived importance of DEI, and commitment to improving DEI. Grounded theory was used to code and analyze open-ended questions. Among 796 registrants, 231 individuals completed the survey. DEI was "extremely important" among 72.7 percent of respondents and lowest among UL1 PIs (66.7%). Being "extremely committed" to improving DEI was reported by 56.3 percent of respondents and lowest among "other staff" (49.6%). Perceived importance of DEI was positively associated with commitment to improve DEI. Institutional and CTSA Commitment, Support, and Prioritization of DEI represented a key theme for improving DEI among respondents. Clinical and translational science organizations must take bold steps to transform individual perceptions of DEI into commitment and commitment into action. Institutions must set visionary objectives spanning leadership, training, research, and clinical trials research to meet the promise and benefits of a diverse NIH-supported workforce.

Utilizing the Un-Meeting model to advance innovative translational and team science.

Advances in translational science require innovative solutions, and engagement of productive transdisciplinary teams play a critical role. While various forms of scientific meetings have long provided venues for sharing scientific findings and generating new collaborations, many conferences lack opportunities for active discussions. We describe the use of an Un-Meeting to foster innovative translational science teams through engaged discussions across multidisciplinary groups addressing a shared theme. The Un-Meeting was delivered by the University of Rochester Center for Leading Innovation and Collaboration, the national coordinating center for the National Institutes of Health Clinical and Translational Science Awards (CTSA) program. This pilot CTSA program Un-Meeting focused on engaging translational scientists, policy-makers, community members, advocates, and public health professionals to address the opioid crisis. The participant-driven format leveraged lightning talks, attendee-led idea generation, and extensive breakout discussions to foster multidisciplinary networking. Results indicated participation by a broad set of attendees and a high level of networking during the meeting. These results, coupled with the growth of the Un-Meeting across the CTSA Consortium, provide practices and models to potentially advance team and translational science. While future work will further assess the impact of Un-Meetings, this format presents a promising approach to enhance translational science.

The CTSA Diversity, Equity, Inclusion, and Accessibility (DEIA) Task Force's recommendations for the CTSA program consortium.

The Clinical and Translational Science Award (CTSA) Program recognizes that advancing diversity, equity, inclusion, and accessibility (DEIA) requires moving beyond statements of commitment to transformative actions. In 2021, the CTSA Program created a Task Force (TF) to initiate work in support of structural and transformational initiatives that advance DEIA for the consortium and its individual hubs. We describe the process of forming the expertise-driven (DEIA) TF and our activities to date. We 1) developed and adopted the DEIA Learning Systems Framework to guide our approach; 2) defined a set of recommendations across four focus areas (Institutional; Programmatic; Community-Centered; and Social, Cultural, Environmental); and 3) designed and disseminated a survey to capture the CTSA Program's baseline demographic, community, infrastructural, and leadership diversity. The CTSA Consortium also elevated the TF to a standing Committee to extend our understanding, development, and implementation of DEIA approaches to translational and clinical science. These initial steps provide a foundation for collectively fostering environment that support DEIA across the research continuum.

Demographic composition of National Institutes of Health Clinical and Translational Science Awards (CTSA) Program principal investigators, scholars, and trainees.

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.

Advancing workforce diversity by leveraging the Clinical and Translational Science Awards (CTSA) program.

Clinical trials continue to disproportionately underrepresent people of color. Increasing representation of diverse backgrounds among clinical research personnel has the potential to yield greater representation in clinical trials and more efficacious medical interventions by addressing medical mistrust. In 2019, North Carolina Central University (NCCU), a Historically Black College and University with a more than 80% underrepresented student population, established the Clinical Research Sciences Program with support from the Clinical and Translational Science Awards (CTSA) program at neighboring Duke University. This program was designed to increase exposure of students from diverse educational, racial, and ethnic backgrounds to the field of clinical research, with a special focus on health equity education. In the first year, the program graduated 11 students from the two-semester certificate program, eight of whom now hold positions as clinical research professionals. This article describes how leveraging the CTSA program helped NCCU build a framework for producing a highly trained, competent, and diverse workforce in clinical research responsive to the call for increased diversity in clinical trial participation.

Feasibility, impact, and priority of key strategies to enhance diverse and inclusive training programs in clinical and translational research: A mixed methods study.

Enhancing diversity in the scientific workforce is a long-standing issue. This study uses mixed methods to understand the feasibility, impact, and priority of six key strategies to promote diverse and inclusive training and contextualize the six key strategies across Clinical and Translational Science Awards (CTSAs) Program Institutions. Four breakout sessions were held at the NCATS 2020 CTSA Program annual meeting focused on diversity, equity, and inclusion (DEI) efforts. This paper focuses on the breakout session for Enhancing DEI in Translational Science Training Programs. Data were analyzed using a mixed methods convergent approach. The quantitative strand includes the online polling results. The qualitative strand includes the breakout session and the chat box in response to the training presentation. Across feasibility, impact, and priority questions, prioritizing representation ranked number 1. Building partnerships ranked number 2 in feasibility and priority, while making it personal ranked number 2 for impact. Across each strategy, rankings supported the qualitative data findings in feasibility through shared experiences, impact in the ability to increase DEI, and priority rankings in comparison to the other strategies. No divergence was found across quantitative and qualitative data findings. Findings provide robust support for prioritizing representation as a number one strategy to focus on in training programs. Specifically, this strategy can be operationalized through integration of community representation, diversity advocates, and adopting a holistic approach to recruiting a diverse cadre of scholars into translational science training programs at the national level across CTSAs.

Advancing diversity, equity, and inclusion within clinical and translational science training programs: A qualitative content analysis of the training breakout session at the national CTSA program meeting.

Diversity, equity, and inclusion (DEI) in clinical and translational science (CTS) are paramount to driving innovation and increasing health equity. One important area for improving diversity is among trainees in CTS programs. This paper reports on findings from a special session at the November 2020 Clinical and Translational Science Award (CTSA) national program meeting that focused on advancing diversity and inclusion within CTS training programs. Using qualitative content analysis, we identified approaches brought forth to increase DEI in KL2 career development and other training programs aimed at early-stage CTS investigators, beyond the six strategies put forth to guide the breakout session (prioritizing representation, building partnerships, making it personal, designing program structure, improving through feedback, and winning endorsement). We used an inductive qualitative content analysis approach to identify themes from a transcript of the panel of KL2 program leaders centered on DEI in training programs. We identified four themes for advancing DEI within CTS training programs: 1) institutional buy-in; 2) proactive recruitment efforts; 3) an equitable application process; and 4) high-quality, diverse mentorship. Implementing these strategies in CTS and other training programs will be an important step for advancing DEI. However, processes need to be established to evaluate the implementation and effectiveness of these strategies through continuous quality improvement, a key component of the CTSA program. Training programs within the CTSA are well-positioned to be leaders in this critical effort to increase the diversity of the scientific workforce.

Exploratory study of the underutilization of CTSA module services.

The Clinical and Translational Science Award (CTSA) program aims to enhance the quality, efficiency, and impact of translation from discovery to interventions that improve human health. CTSA program hubs at medical research institutions across the United States develop and test innovative tools, methods, and processes, offering core resources and training for the clinical and translational research (CTR) workforce. Hubs have developed services across different domains, such as informatics and pilot studies, to provide ad hoc expertise and staffing for local research teams. Although these services can provide efficient, cost-effective ways to cover skills gaps and implement rigorous studies, three CTSAs of varying size found the majority of investigators were single domain service users, likely missing opportunities to further enhance their work. Through interviews with CTSA service users and a survey of CTSA service managers, this exploratory study aims to identify barriers to using services from multiple modules and solutions to overcome those barriers. Barriers include challenges in finding information about services, unclear or unknown user needs, and users' lack of funding to engage in services. More issues were identified for the largest CTSA. Although this study represents a small subset of CTSA hubs, we anticipate that our findings and proposed solutions will be relevant to the broader CTSA community. This study provides foundational information can use in their own efforts to increase service utilization and methods that can be used for more comprehensive studies that focus on explaining the relationship between CTSA features and rates of single versus cross-module service use.

Artificial intelligence in clinical and translational science: Successes, challenges and opportunities.

Artificial intelligence (AI) is transforming many domains, including finance, agriculture, defense, and biomedicine. In this paper, we focus on the role of AI in clinical and translational research (CTR), including preclinical research (T1), clinical research (T2), clinical implementation (T3), and public (or population) health (T4). Given the rapid evolution of AI in CTR, we present three complementary perspectives: (1) scoping literature review, (2) survey, and (3) analysis of federally funded projects. For each CTR phase, we addressed challenges, successes, failures, and opportunities for AI. We surveyed Clinical and Translational Science Award (CTSA) hubs regarding AI projects at their institutions. Nineteen of 63 CTSA hubs (30%) responded to the survey. The most common funding source (48.5%) was the federal government. The most common translational phase was T2 (clinical research, 40.2%). Clinicians were the intended users in 44.6% of projects and researchers in 32.3% of projects. The most common computational approaches were supervised machine learning (38.6%) and deep learning (34.2%). The number of projects steadily increased from 2012 to 2020. Finally, we analyzed 2604 AI projects at CTSA hubs using the National Institutes of Health Research Portfolio Online Reporting Tools (RePORTER) database for 2011–2019. We mapped available abstracts to medical subject headings and found that nervous system (16.3%) and mental disorders (16.2) were the most common topics addressed. From a computational perspective, big data (32.3%) and deep learning (30.0%) were most common. This work represents a snapshot in time of the role of AI in the CTSA program.

Sharing data among clinical trials of therapeutics in COVID-19: Barriers and facilitators to collaborating in a crisis.

The Clinical and Translational Science Award Program (CTSA) Trial Innovation Network (TIN) was launched in 2016 to increase the efficiency and effectiveness of multisite trials by supporting the development of national infrastructure. With the advent of the COVID-19 pandemic, it was therefore well-positioned to support clinical trial collaboration. The TIN was leveraged to support two initiatives: (1) to create and evaluate a mechanism for coordinating Data and Safety Monitoring Board (DSMB) activities among multiple ongoing trials of the same therapeutic agents, and (2) to share data across clinical trials so that smaller, likely underpowered studies, could be combined to produce meaningful and actionable data through pooled analyses. The success of these initiatives was understood to be dependent upon the willingness of investigators, study teams, and US National Institutes of Health research networks to collaborate and share information. To inform these two initiatives, we conducted semistructured interviews with members of CTSA hubs and clinical research stakeholders that probed barriers and facilitators to collaboration. Thematic analysis identified topics relevant across institutions, individuals, and DSMBs. The DSMB coordination initiative was viewed as less controversial, while the data pooling initiative was seen as complex because of its potential impact on publication, authorship, and the rewards of discovery. Barriers related to resources, centralization, and technical work were significant, but interviewees suggested these could be handled by the provision of central funding and supportive frameworks. The more intractable findings were related to issues around credit and ownership of data. Based on our interviews, we conclude with nine recommended actions that can be implemented to support collaboration.

An End-to-End Integrated Clinical and CT Based Radiomics Nomogram for Predicting Disease Severity and Need for Ventilator Support in COVID-19 Patients: A Large Multi-Site Retrospective Study

Objective: The disease COVID-19 has caused a widespread global pandemic with ~3.93 million deaths worldwide. In this work, we present three models- Radiomics (MRM), Clinical (MCM), and combined Clinical-Radiomics (MRCM) nomogram to predict COVID-19 positive patients who will end up needing invasive mechanical ventilation from the baseline CT scans.  Method: We performed a retrospective multicohort study of individuals with COVID-19 positive findings for a total of 980 patients from 2 different institutions (Renmin hospital of Wuhan University, D1 =787 and University Hospitals, US D2 = 110). The patients from institution-1 were divided into 60% training, D1 T (N=473), and 40% test set D1 V (N=314). The patients from institution-2 were used for an independent validation test set D2 V(N=110). A U-Net-based neural network (CNN) was trained to automatically segment out the COVID consolidation regions on the CT scans. The segmented regions from the CT scans were used for extracting first-order and higher-order Radiomic textural features. The top Radiomic and clinical features were selected using the Least Absolute Shrinkage and Selection Operator (LASSO) with an optimal binomial regression model within D1 T. Results: The 3 out of the top 5 features identified using D1 T were higher-order textural features (GLCM, GLRLM, GLSZM), whereas the last two features included the total infection size on the CT scan and the total intensity of the COVID consolidations. The Radiomics Model (MRM ) was constructed using the Radiomic Score built using the coefficients obtained from the LASSO logistic model used within the linear regression (LR) classifier. The MRM yielded an area under the receiver operating characteristic curve (AUC) of 0.754 [0.709-0.799] on D1 T, 0.836 on D1 V, and 0.748 D2 V. The top prognostic clinical factors identified in the analysis were dehydrogenase (LDH), age, and albumin (ALB). The clinical model had an AUC of 0.784 [0.743-0.825] on D1 T, 0.813 on D1 V, and 0.723 on D2 V. Finally, the combined model, MRCM integrating Radiomic Score, age, LDH and ALB, yielded an AUC of 0.814 [0.774-0.853] on D1 T, 0.847 on D1 V, and 0.772 on D2 V. The MRCM had an overall improvement in the performance of ~3.77% (D1 T: p = 0.0003; D1 V p= 0.0165; D2 V : p = 0.024) over MCM Conclusion: The novel integrated imaging and clinical model (MRCM) outperformed both models (MRM) and (MCM). Our results across multiple sites suggest that the integrated nomogram could help identify COVID-19 patients with more severe disease phenotype and potentially requiring mechanical ventilation. Funding: National Cancer Institute of the US National Institutes of Health, National Center for Research Resources, US Department of Veterans Affairs Biomedical Laboratory Research and Development Service, Department of Defense, National Institute of Diabetes and Digestive and Kidney Diseases, Wallace H Coulter Foundation, Case Western Reserve University, and Dana Foundation. Declaration of Interest: AM reports grants from National Cancer Institute of the National Institutes of Health, grants from National Center for Research Resources, grants from VA Merit Review Award, grants from DOD Cancer Investigator-Initiated Translational Research Award, during the conduct of the study; grants from DOD Prostate Cancer Idea Development Award, grants from DOD Peer Reviewed Cancer Research Program, grants from National Institute of Diabetes and Digestive and Kidney Diseases , grants from the Ohio Third Frontier Technology Validation Fund, grants from the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University, grants from Department of Defense Peer Reviewed Cancer Research Program (PRCRP) Career Development Award, grants from Dana Foundation David Mahoney Neuroimaging Program. Ethical Approval: The study conformed to HIPAA guidelines was approved by University Hospitals, Cleveland (STUDY20200463), and the Ethics committee of the Renmin Hospital of Wuhan University (ethics number: V1.0).

A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer.

We developed and validated a prognostic and predictive computational pathology risk score (CoRiS) using H&E stained tissue images from patients with early-stage non-small cell lung cancer (ES-NSCLC). 1330 patients with ES-NSCLC were acquired from 3 independent sources and divided into four cohorts D1-4. D1 comprised 100 surgery treated patients and was used to identify prognostic features via an elastic-net Cox model to predict overall and disease-free survival. CoRiS was constructed using the Cox model coefficients for the top features. The prognostic performance of CoRiS was evaluated on D2 (N=331), D3 (N=657) and D4 (N=242). Patients from D2 and D3 which comprised surgery+chemotherapy were used to validate CoRiS as predictive of added benefit to adjuvant chemotherapy (ACT) by comparing survival between different CoRiS defined risk groups. CoRiS was found to be prognostic on univariable analysis, D2 (hazard ratio (HR)=1.41, adjusted (adj.) P=.01) and D3 (HR=1.35, adj. P < .001). Multivariable analysis showed CoRiS was independently prognostic, D2 (HR=1.41, adj. P < .001) and D3 (HR=1.35, adj. P < .001), after adjusting for clinico-pathologic factors. CoRiS was also able to identify high-risk patients who derived survival benefit from ACT D2 (HR=0.42, adj. P=.006) and D3 (HR=0.46, adj. P=.08). CoRiS is a tissue non-destructive, quantitative and low-cost tool that could potentially help guide management of ES-NSCLC patients. Data collection, anlaysis, and computation resources of the research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award numbers: 1U24CA199374-01, R01CA202752-01A1, R01CA208236-01A1, R01 CA216579-01A1, R01 CA220581-01A1, 1U01 CA239055-01. National Center for Research Resources under award number 1 C06 RR12463-01. VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.

11492 Mapping CTSA hub activities across the EQ-DI framework to discover opportunities for interaction between health equity and dissemination &amp; implementation science; the case of University of Colorado and University of Rochester

ABSTRACT IMPACT: This study provides a framwork to inform and organize health equity efforts and initiatives at CTSA institutes. OBJECTIVES/GOALS: to map the activities of the Clinical and Translational Science Award (CTSA) Program hubs across the EQ-DI framework, to depict opportunities for interaction between health equity and dissemination &amp; implementation (D&amp;I) science. METHODS/STUDY POPULATION: The EQ-DI framework demonstrates the dynamic interaction between D&amp;I science and health equity. Health equity could be a lens to sensitize and inform D&amp;I planning (through goal-setting and team development), execution (through ‘adaptation’ and D&amp;I strategies), and evaluation (through incorporating health equity in D&amp;I outcome assessment). On the other hand, D&amp;I models, methods, and study designs can operationalize dissemination and implementation of evidence-based interventions to improve equity. Stakeholder engagement is at the center of the framework to inform and direct the sensitization and operationalization cycles. RESULTS/ANTICIPATED RESULTS: We reviewed the activities of Colorado Clinical &amp; Translational Sciences Institute (CCTSI) and University of Rochester Clinical and Translational Science Institute (UR CTSI) to improve health equity and mapped them across the EQ-DI framework. The sensitizing activities included health equity training, eliciting community priorities, and inclusion of health equity as a critical axis in funding mechanisms. The operationalizing activities included D&amp;I methodological training and consultation, collaborative team science, and funding mechanisms to support implementation of health equity EBIs. Community engagement through studios, community liaisons, and consults was a core priority guiding sensitizing and operationalizing activities. DISCUSSION/SIGNIFICANCE OF FINDINGS: The CTSA Program has been a champion for community engagement and translational collaboration to improve individual and population health. CTSA hubs provide infrastructure and resources to facilitate equity-focused D&amp;I.

A compendium of community engagement responses to the COVID-19 pandemic.

Clinical and Translational Science Award Program (CTSA)-funded institutions were charged with developing clinical and translational science programs and transforming clinical research at their institutions. Community engagement (CE) was recognized as a key component and catalyst of that transformation. CE hub capacities for working with communities and translating knowledge into practice have been illustrated through their COVID-19 responses. CE hub leaders met and discussed their CTSA's early responses regarding the COVID-19 pandemic. The 2-hour discussion was distilled into themes which were sent to the CE hub leaders with a request for written accounts describing actions taken to engage local partners, communities, and institutions. The written reports form the basis for this compendium. Eighteen institutions submitted written reports describing activities in relation to six themes: (1) listen to the community and respond to concerns, (2) collect data to understand the impact of COVID-19 on distinct communities and groups, (3) communicate science and address misinformation, (4) collaborate with health departments, (5) engage hubs and underrepresented populations in COVID-19 research, and (6) support our own well-being and that of others. Bidirectional interactions comprise the foundation of CE, which requires trusted partnerships that sustain communication through a series of activities and goals. The nimble responses to the pandemic substantiate the need for CE programs to maintain the infrastructure necessary to achieve the primary CTSA goals of improving health within and across communities and localities as well as expanding research participation of community members.

CTSA pharmacies: Contribution to research and public health during the COVID-19 pandemic.

In March 2020, academic medical center (AMC) pharmacies were compelled to implement practice changes in response to the COVID-19 pandemic. These changes were described by survey data collected by the Clinical and Translational Science Awards (CTSA) program which were interpreted by a multi-institutional team of AMC pharmacists and physician investigators. The CTSA program surveyed 60 AMC pharmacy departments. The survey included event timing, impact on pharmacy services, and corrective actions taken. Almost all departments (98.4%) reported at least one disruption. Shortages of personal protective equipment (PPE) were common (91.5%) as were drug shortages (66.0%). To manage drug shortages, drug prioritization protocols were utilized, new drug supply vendors were identified (79.3%), and onsite compounding was initiated. PPE shortages were managed by incorporating the risk mitigation strategies recommended by FDA and others. Research pharmacists supported new clinical research initiatives at most institutions (84.0%), introduced use of virtual site visits, and shipped investigational drugs directly to patients. Some pharmacies formulated novel investigational products for clinical trial use. Those AMC pharmacies within networked health systems assisted partner rural and inner-city hospitals by sourcing commercial and investigational drugs to alleviate local disease outbreaks and shortages in underserved populations. Pharmacy-based vaccination practice was expanded to include a wider range of pediatric and adult vaccines. The COVID-19 pandemic radically altered hospital pharmacy practice. By adopting innovative methods and adapting to regulatory imperatives, pharmacies at CTSA sites played an extremely important role supporting continuity of care and collaborating on critical clinical research initiatives.

4436 A Content Analysis of CTSA Websites: The Identification and Evaluation of CTSA Program Hub Website Content Standards for Knowledge Management of NCATS CTSA Program Goals and Initiatives

OBJECTIVES/GOALS: Introduction: Between 2014 and 2019 the National Institute of Health (NIH) through the National Center for the Advancement of Translational Science (NCATS) has awarded about $2.7 billion to U.S. Academic Medical Centers to build a national network of clinical and translational science program hubs that serve to meet their key goals and initiatives. Today there are about 60 Clinical and Translational Science Award (CTSA) program hubs. Each CTSA program hub has a corresponding website highlighting its clinical and translational science centered programs and activities. These websites are a critical communication gateway to promote NCATS goals and initiatives. Objective: The objective of this research is to evaluate the NIH funded Clinical and Translational Science Award (CTSA) program hub websites for NCATS goals and initiative content alignment, navigability, and interactivity. METHODS/STUDY POPULATION: Methods: Each CTSA program hub website was systematically evaluated for information or tools that align with the five NCATS / CTSA Goals and eight CTSA nationally identified program initiatives. Each NCATS goal and CTSA initiative was subsequently ranked by information diversity level (text, tool, interactivity) and navigation level (click distance from the home page). RESULTS/ANTICIPATED RESULTS: Results: Four of the five NCATS goals are thoroughly and consistently represented among the CTSA Consortium with workforce development, patient and community engagement, and quality and efficiency of research being the top three. Informatics is thoroughly and consistently represented, but not always clearly identified on the home page. The most underrepresented goal is integration of special and underserved populations which was identified on only 60% of CTSA program hub websites. The most common focus of the eight CTSA program initiatives is the Trial Innovation Network in CTSA program hub websites. The Smart IRB comes in a distant second. The remaining six initiatives are severely underrepresented. DISCUSSION/SIGNIFICANCE OF IMPACT: Discussion: The identification of these gaps among the CTSA program hubs presents an understanding of content management and website functionality among the consortium from 3 principal approaches. First it creates an understanding of CTSA program hub content alignment with its funding source goals and initiatives. Such an understanding presents an opportunity to promote ways to create a better aligned consortium with improved collaboration pathways by the funding source through program hub website content standards. Second, it creates an opportunity for program hubs to understand and respond to the messaging their websites are presenting as it relates to the funding source. Third, it provides an opportunity to identify specific program initiatives and goals the CTSA institutions independently chose to highlight which can open a dialog to the better understanding the value of the program initiatives as they relate to the needs of CTSA program hubs. Ultimately, CTSA websites through content alignment should lead to an improved user experience.

Accelerating implementation of research in Learning Health Systems: Lessons learned from VA Health Services Research and NCATS Clinical Science Translation Award programs.

Translation of research to practice is challenging. In addition to the scientific challenges, there are additional hurdles in navigating the rapidly changing US health care system. There is a need for innovative health interventions that can be adopted in "real-world" settings. Barriers to translation involve misaligned timing of research funding and health system decision-making, lack of research questions aligned with health system and community priorities, and limited incentives in academia for health system and community-based research. We describe new programs from the US Department of Veterans Affairs Health Services Research and Development (HSR&D) and the National Center for Advancing Translational Sciences (NCATS) Clinical and Translational Science Award (CTSA) Programs that are building capacity for Learning Health System research. These programs help to incentivize adopting and adapting Learning Health System principles to ensure that, primarily in implementation science within academic/veterans affairs health systems, there is alignment of the research with the health system and community needs. Both HSR&D and NCATS CTSA Program encourage researchers to develop problem-focused research innovations in partnership with health systems and communities to ultimately facilitate design treatments that are feasible in "real-world" practice.

Designs and methods for implementation research: Advancing the mission of the CTSA program.

The US National Institutes of Health (NIH) established the Clinical and Translational Science Award (CTSA) program in response to the challenges of translating biomedical and behavioral interventions from discovery to real-world use. To address the challenge of translating evidence-based interventions (EBIs) into practice, the field of implementation science has emerged as a distinct discipline. With the distinction between EBI effectiveness research and implementation research comes differences in study design and methodology, shifting focus from clinical outcomes to the systems that support adoption and delivery of EBIs with fidelity. Implementation research designs share many of the foundational elements and assumptions of efficacy/effectiveness research. Designs and methods that are currently applied in implementation research include experimental, quasi-experimental, observational, hybrid effectiveness-implementation, simulation modeling, and configurational comparative methods. Examples of specific research designs and methods illustrate their use in implementation science. We propose that the CTSA program takes advantage of the momentum of the field's capacity building in three ways: 1) integrate state-of-the-science implementation methods and designs into its existing body of research; 2) position itself at the forefront of advancing the science of implementation science by collaborating with other NIH institutes that share the goal of advancing implementation science; and 3) provide adequate training in implementation science. As implementation methodologies mature, both implementation science and the CTSA program would greatly benefit from cross-fertilizing expertise and shared infrastructures that aim to advance healthcare in the USA and around the world.