Clinical And Translational Science Award Hubs Research Articles

Customized Career Development Platform (CCDP) for clinical and translational researchers: A pragmatic cluster-randomized controlled trial.

Early-stage clinical and translational researchers who set and track career goals, milestones, and progress are successful in career development. We aimed to determine the effectiveness of the Customized Career Development Platform (CCDP), an online individual development plan (IDP), versus the traditional IDP template in improving research success and career satisfaction. We conducted a pragmatic cluster-randomized controlled trial of 340 scholars and trainees at 27 US academic healthcare institutions. The primary outcome was number of published manuscripts 24 months post-intervention. Secondary outcomes included the number of grant proposals submitted and funded, job satisfaction, and level of communication with mentors. An analysis of CCDP participants assessed proficiency level for the 14 Clinical and Translational Science Award (CTSA) competencies. Data were analyzed using intention-to-treat. Participants were mostly female (60.3%) and Caucasian (67.2%); mean age was 34 years. Twenty-four months following the intervention, the CCDP versus traditional IDP groups showed a similar number of publications (9.4 vs 8.6), grants submitted (4.1 vs 4.4) and funded (1.3 vs 2.0), and job satisfaction score (3.6 vs 3.7). The CCDP group had higher odds of discussing communication (OR = 2.08) and leadership skills (OR = 2.62) and broadening their network (2.31) than the traditional IDP group. The CCDP arm reported improvements in 9 of the 14 CTSA competencies. The CCDP offers CTSA hubs an innovative alternative to traditional IDP tools. Future studies are needed to elucidate why the CCDP users did not fully appreciate or adopt the functionality of the online platform.

Maturity in enterprise data warehouses for research operations: Analysis of a pilot study.

Enterprise data warehouses for research (EDW4R) is a critical component of National Institutes of Health Clinical and Translational Science Award (CTSA) hubs. EDW4R operations have unique needs that require specialized skills and collaborations across multiple domains which limit the ability to apply existing models of information technology (IT) performance. Because of this uniqueness, we developed a new EDW4R maturity model based on prior qualitative study of operational practices for supporting EDW4Rs at CTSA hubs. In a pilot study, respondents from fifteen CTSA hubs completed the novel EDW4R maturity index survey by rating 33 maturity statements across 6 categories using a 5-point Likert scale. Of the six categories, respondents rated workforce as most mature (4.17 [3.67-4.42]) and relationship with enterprise IT as the least mature (3.00 [2.80-3.80]). Our pilot of a novel maturity index shows a baseline quantitative measure of EDW4R functions across fifteen CTSA hubs. The maturity index may be useful to faculty and staff currently leading an EDW4R by creating opportunities to explore the index in local context and comparison to other institutions.

The Evolve to Next-Gen ACT Network: An evolving open-access, real-world data resource primed for real-world evidence research across the Clinical and Translational Science Award Consortium.

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.

The Trial Innovation Network Liaison Team: building a national clinical and translational community of practice.

In 2016, the National Center for Advancing Translational Science launched the Trial Innovation Network (TIN) to address barriers to efficient and informative multicenter trials. The TIN provides a national platform, working in partnership with 60+ Clinical and Translational Science Award (CTSA) hubs across the country to support the design and conduct of successful multicenter trials. A dedicated Hub Liaison Team (HLT) was established within each CTSA to facilitate connection between the hubs and the newly launched Trial and Recruitment Innovation Centers. Each HLT serves as an expert intermediary, connecting CTSA Hub investigators with TIN support, and connecting TIN research teams with potential multicenter trial site investigators. The cross-consortium Liaison Team network was developed during the first TIN funding cycle, and it is now a mature national network at the cutting edge of team science in clinical and translational research. The CTSA-based HLT structures and the external network structure have been developed in collaborative and iterative ways, with methods for shared learning and continuous process improvement. In this paper, we review the structure, function, and development of the Liaison Team network, discuss lessons learned during the first TIN funding cycle, and outline a path toward further network maturity.

Training and cultivating the translational science workforce: Responses of Clinical and Translational Science Awards program hubs to the COVID-19 pandemic.

The coronavirus disease 2019 (COVID-19) pandemic has dramatically changed our lives and the delivery of healthcare. The pandemic also led to widespread disruption in the research activities and training of pre-doctoral, post-doctoral, and early career faculty researchers. This mini-review uses the Local Adaptive Capacity Framework to describe successful practices, challenges, and lessons learned on how Clinical and Translational Science Award (CTSA) hubs have used their expertise, resources, and collaborations to advance clinical and translational science research and workforce development while facing and adapting to a pandemic. Data for this mini-review were taken from the scientific literature (23 articles) and the Research Performance Progress Reports of 50 unique CTSA hubs (40 TL1 and 50 KL2 awards). Institutions responded in innovative ways to the disruption of the COVID-19 pandemic. Electronic and virtual platforms were used to overcome challenges related to physical distancing, laboratory closures, and travel bans. The importance of mentorship and well-being led to the creation of new virtual programs to expand mentoring and networking beyond the home institution and to promote well-being and resilience. These solutions to translational workforce development can be implemented to address future public health emergencies.

Leveraging CTSA hubs for rapid, large-scale, high-impact research: A case study during a global public health emergency.

As the COVID-19 pandemic took hold in the USA in early 2020, it became clear that knowledge of the prevalence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among asymptomatic individuals could inform public health policy decisions and provide insight into the impact of the infection on vulnerable populations. Two Clinical and Translational Science Award (CTSA) Hubs and the National Institutes of Health (NIH) set forth to conduct a national seroprevalence survey to assess the infection's rate of spread. This partnership was able to quickly design and launch the project by leveraging established research capacities, prior experiences in large-scale, multisite studies and a highly skilled workforce of CTSA hubs and unique experimental capabilities at the NIH to conduct a diverse prospective, longitudinal observational cohort of 11,382 participants who provided biospecimens and participant-reported health and behavior data. The study was completed in 16 months and benefitted from transdisciplinary teamwork, information technology innovations, multimodal communication strategies, and scientific partnership for rigor in design and analytic methods. The lessons learned by the rapid implementation and dissemination of this national study is valuable in guiding future multisite projects as well as preparation for other public health emergencies and pandemics.

Engaging community in the translational process: Environmental scan of adaptive capacity and preparedness of Clinical and Translational Science Award Program hubs.

This paper is part of the Environmental Scan of Adaptive Capacity and Preparedness of Clinical and Translational Science Award (CTSA) hubs, illuminating challenges, practices, and lessons learned related to CTSA hubs' efforts of engaging community partners to reduce the spread of the virus, address barriers to COVID-19 testing, identify treatments to improve health outcomes, and advance community participation in research. CTSA researchers, staff, and community partners collaborated to develop evidence-based, inclusive, accessible, and culturally appropriate strategies and resources helping community members stay healthy, informed, and connected during the pandemic. CTSA institutions have used various mechanisms to advance co-learning and co-sharing of knowledge, resources, tools, and experiences between academic professionals, patients, community partners, and other stakeholders. Forward-looking and adaptive decision-making structures are those that prioritize sustained relationships, mutual trust and commitment, ongoing communication, proactive identification of community concerns and needs, shared goals and decision making, as well as ample appreciation of community members and their contributions to translational research. There is a strong need for further community-engaged research and workforce training on how to build our collective and individual adaptive capacity to sustain and improve processes and outcomes of engagement with and by communities-in all aspects of translational science.

Leadership and administration to advance translational science: Environmental scan of adaptive capacity and preparedness of Clinical and Translational Science Award Program hubs.

COVID-19 reinforced the need for effective leadership and administration within Clinical and Translational Science Award (CTSA) program hubs in response to a public health crisis. The speed, scale, and persistent evolution of the pandemic forced CTSA hubs to act quickly and remain nimble. The switch to virtual environments paired with supporting program operations, while ensuring the safety and well-being of their team, highlight the critical support role provided by leadership and administration. The pandemic also illustrated the value of emergency planning in supporting organizations' ability to quickly pivot and adapt. Lessons learned from the pandemic and from other cases of adaptive capacity and preparedness can aid program hubs in promoting and sustaining the overall capabilities of their organizations to prepare for future events.

Adaptive capacity and preparedness of Clinical and Translational Science Award Program hubs: Overview of an environmental scan.

The ability of research networks and individual institutions to effectively and efficiently prepare, respond, and adapt to emergent challenges is essential for the biomedical research enterprise. At the beginning of 2021, a special Working Group was formed by individuals in the Clinical and Translational Science Award (CTSA) consortium and approved by the CTSA Steering Committee to explore "Adaptive Capacity and Preparedness (AC&P) of CTSA Hubs." The AC&P Working Group took a pragmatic Environmental Scan (E-Scan) approach of utilizing the diverse data that had been collected through existing mechanisms. The Local Adaptive Capacity framework was adapted to illustrate the interconnectedness of CTSA programs and services, while exposing how the demands of the pandemic forced them to quickly pivot and adapt. This paper presents a synopsis of the themes and lessons learned that emerged from individual sections of the E-Scan. Lessons learned from this study may improve our understanding of adaptive capacity and preparedness at different levels, as well as help strengthen the core service models, strategies, and foster innovation in clinical and translational science research.

The Virtual CTSA Visiting Scholar Program to Support Early-Stage Clinical and Translational Researchers: Implementation and Outcomes.

In addition to restrictions on conducting research, COVID-19-related travel bans and scientific meeting cancellations have negatively affected scholars in the Clinical and Translational Science Award (CTSA) Mentored Career Development Award (KL2) program. In response, a national virtual visiting scholar program was developed to provide opportunity for KL2 scholars to be virtual visiting professors at another CTSA hub, meet faculty and scholars, and expand networks and build collaborations. This article describes the design and short-term outcomes of the virtual CTSA Visiting Scholar Program. In 2020, a working group designed core program elements and developed an application and selection process. Anonymized surveys were sent to scholars post visit and to scholars and program directors 6 months post visit to evaluate their experience and solicit suggestions for improvements. Between November 2020 and May 2021, 56 KL2 scholars and 27 hubs participated. Forty-five (80.4%) participating scholars responded to the initial survey. Nearly all scholars (44, 97.7%) agreed their experience was valuable. All respondents indicated they would recommend the program to other KL2 scholars. For the 6-month survey, the response rate was 87.5% (49/56). Within 6 months of their visit, 36 (73.5%) respondents had contacted at least one person at the host hub and for 17 (34.7%) respondents, new collaborations with the host hub ensued. Twenty-five of 27 (92.6%) host hubs responded to the survey. Most (21, 84.0%) agreed that hearing visiting scholar talks was valuable to their own scholars and 23 (92%) indicated likelihood of their hub participating in future round of the program. The virtual Visiting Scholar Program provided KL2 scholars an opportunity to virtually visit another CTSA hub, present their research, and meet with faculty and other scholars to expand their networks. Although geared to KL2 scholars, this model is potentially generalizable to other nationally coordinated career development programs.

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.

Informatics education for translational research teams: An unrealized opportunity to strengthen the national research infrastructure.

To identify the informatics educational needs of clinical and translational research professionals whose primary focus is not informatics. Informatics and data science skills are essential for the full spectrum of translational research, and an increased understanding of informatics issues on the part of translational researchers can alleviate the demand for informaticians and enable more productive collaborations when informaticians are involved. Identifying the level of interest in different topics among various types of of translational researchers will help set priorities for development and dissemination of informatics education. We surveyed clinical and translational science researchers in Clinical and Translational Science Award (CTSA) programs about their educational needs and preferences. Researchers from 23 out of the 62 CTSA hubs responded to the survey. 67% of respondents across roles and topics expressed interest in learning about informatics topics. There was high interest in all 30 topics included in the survey, with some variation in interest depending on the role of the respondents. Our data support the need to advance training in clinical and biomedical informatics. As the complexity and use of information technology and data science in research studies grows, informaticians will continue to be a limited resource for research collaboration, education, and training. An increased understanding of informatics issues across translational research teams can alleviate this burden and allow for more productive collaborations. To inform a roadmap for informatics education for research professionals, we suggest strategies to use the results of this needs assessment to develop future informatics education.

Clinical and translational science award T32/TL1 training programs: program goals and mentorship practices.

A national survey characterized training and career development for translational researchers through Clinical and Translational Science Award (CTSA) T32/TL1 programs. This report summarizes program goals, trainee characteristics, and mentorship practices. A web link to a voluntary survey was emailed to 51 active TL1 program directors and administrators. Descriptive analyses were performed on aggregate data. Qualitative data analysis used open coding of text followed by an axial coding strategy based on the grounded theory approach. Fifty out of 51 (98%) invited CTSA hubs responded. Training program goals were aligned with the CTSA mission. The trainee population consisted of predoctoral students (50%), postdoctoral fellows (30%), and health professional students in short-term (11%) or year-out (9%) research training. Forty percent of TL1 programs support both predoctoral and postdoctoral trainees. Trainees are diverse by academic affiliation, mostly from medicine, engineering, public health, non-health sciences, pharmacy, and nursing. Mentor training is offered by most programs, but mandatory at less than one-third of them. Most mentoring teams consist of two or more mentors. CTSA TL1 programs are distinct from other NIH-funded training programs in their focus on clinical and translational research, cross-disciplinary approaches, emphasis on team science, and integration of multiple trainee types. Trainees in nearly all TL1 programs were engaged in all phases of translational research (preclinical, clinical, implementation, public health), suggesting that the CTSA TL1 program is meeting the mandate of NCATS to provide training to develop the clinical and translational research workforce.

Understanding enterprise data warehouses to support clinical and translational research: enterprise information technology relationships, data governance, workforce, and cloud computing.

Among National Institutes of Health Clinical and Translational Science Award (CTSA) hubs, effective approaches for enterprise data warehouses for research (EDW4R) development, maintenance, and sustainability remain unclear. The goal of this qualitative study was to understand CTSA EDW4R operations within the broader contexts of academic medical centers and technology. We performed a directed content analysis of transcripts generated from semistructured interviews with informatics leaders from 20 CTSA hubs. Respondents referred to services provided by health system, university, and medical school information technology (IT) organizations as "enterprise information technology (IT)." Seventy-five percent of respondents stated that the team providing EDW4R service at their hub was separate from enterprise IT; strong relationships between EDW4R teams and enterprise IT were critical for success. Managing challenges of EDW4R staffing was made easier by executive leadership support. Data governance appeared to be a work in progress, as most hubs reported complex and incomplete processes, especially for commercial data sharing. Although nearly all hubs (n = 16) described use of cloud computing for specific projects, only 2 hubs reported using a cloud-based EDW4R. Respondents described EDW4R cloud migration facilitators, barriers, and opportunities. Descriptions of approaches to how EDW4R teams at CTSA hubs work with enterprise IT organizations, manage workforces, make decisions about data, and approach cloud computing provide insights for institutions seeking to leverage patient data for research. Identification of EDW4R best practices is challenging, and this study helps identify a breadth of viable options for CTSA hubs to consider when implementing EDW4R services.

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.

Scholarly Productivity Evaluation of KL2 Scholars Using Bibliometrics and Federal Follow-on Funding: Cross-Institution Study.

BackgroundEvaluating outcomes of the clinical and translational research (CTR) training of a Clinical and Translational Science Award (CTSA) hub (eg, the KL2 program) requires the selection of reliable, accessible, and standardized measures. As measures of scholarly success usually focus on publication output and extramural funding, CTSA hubs have started to use bibliometrics to evaluate the impact of their supported scholarly activities. However, the evaluation of KL2 programs across CTSAs is limited, and the use of bibliometrics and follow-on funding is minimal.ObjectiveThis study seeks to evaluate scholarly productivity, impact, and collaboration using bibliometrics and federal follow-on funding of KL2 scholars from 3 CTSA hubs and to define and assess CTR training success indicators.MethodsThe sample included KL2 scholars from 3 CTSA institutions (A-C). Bibliometric data for each scholar in the sample were collected from both SciVal and iCite, including scholarly productivity, citation impact, and research collaboration. Three federal follow-on funding measures (at the 5-year, 8-year, and overall time points) were collected internally and confirmed by examining a federal funding database. Both descriptive and inferential statistical analyses were computed using SPSS to assess the bibliometric and federal follow-on funding results.ResultsA total of 143 KL2 scholars were included in the sample with relatively equal groups across the 3 CTSA institutions. The included KL2 scholars produced more publications and citation counts per year on average at the 8-year time point (3.75 publications and 26.44 citation counts) than the 5-year time point (3.4 publications vs 26.16 citation counts). Overall, the KL2 publications from all 3 institutions were cited twice as much as others in their fields based on the relative citation ratio. KL2 scholars published work with researchers from other US institutions over 2 times (5-year time point) or 3.5 times (8-year time point) more than others in their research fields. Within 5 years and 8 years postmatriculation, 44.1% (63/143) and 51.7% (74/143) of KL2 scholars achieved federal funding, respectively. The KL2-scholars of Institution C had a significantly higher citation rate per publication than the other institutions (P<.001). Institution A had a significantly lower rate of nationally field-weighted collaboration than did the other institutions (P<.001). Institution B scholars were more likely to have received federal funding than scholars at Institution A or C (P<.001).ConclusionsMulti-institutional data showed a high level of scholarly productivity, impact, collaboration, and federal follow-on funding achieved by KL2 scholars. This study provides insights on the use of bibliometric and federal follow-on funding data to evaluate CTR training success across institutions. CTSA KL2 programs and other CTR career training programs can benefit from these findings in terms of understanding metrics of career success and using that knowledge to develop highly targeted strategies to support early-stage career development of CTR investigators.

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.

31257 A Case Study of Needs Assessment Practices Using I-Corp Customer Discovery Protocols Alongside REDCap Surveys for CTSA Activities.

ABSTRACT IMPACT: The results from this study will improve needs assessment practices. OBJECTIVES/GOALS: The discovery phase in project development is necessary to better understand the needs and requirements of the intended market. This paper compares the outcomes of two virtual data collection methodologies, NSF I-Corps Customer Discovery interviews and REDCap surveys, for a needs assessment. METHODS/STUDY POPULATION: Clinical and Translational Science Award (CTSA) Directors and Academic Administrators across the Consortium were asked about the types of skills needed to assess clinical research professional competencies and the need for a competency-based self-assessment tool (CBST). Parallel methods were used to extract qualitative and quantitative data. The first approach was to conduct interviews using I-Corps customer discovery guidelines, and data was collected using Innovation Within software. Targeted requests were sent via cold email outreach to 102 individuals within 63 CTSA hubs. The second approach involved the use of the NJ ACTS Training and Education Offering Inventory REDCap Survey which was distributed via LISTSERV to 63 CTSA hubs. Response rates and user insights from each method were compared. RESULTS/ANTICIPATED RESULTS: Twenty-one of 63 CTSA hubs responded to the survey (response rate: 33%) while 18 of 63 hubs participated in an interview (response rate: 28%). Twenty-two individuals out of 102 were interviewed (response rate: 21%). Fifty-nine percent of interviewees and 62% of survey respondents indicated a clear need for a CBST; types of responses varied. Forty user insights were obtained from ten interviews. Two insights were gained in the survey from the eight who were prompted to fill out the free-text response. Both survey participants and interviewees indicated that communication and team science soft skills were the most important competencies. Regarding hard skills, interviewees preferred written skills while survey participants favored ‘scientific design and concept’ skills. DISCUSSION/SIGNIFICANCE OF FINDINGS: Results suggest the use of a survey or an interview for a needs assessment is dependent on several factors: need for insights, burden of time, desire to obtain quantitative vs. qualitative data, and question format. The interview was more effective than the survey in addressing the key question and obtaining insights from the intended market.

Building biorepositories in the midst of a pandemic.

Biospecimen repositories play a vital role in enabling investigation of biologic mechanisms, identification of disease-related biomarkers, advances in diagnostic assays, recognition of microbial evolution, and characterization of new therapeutic targets for intervention. They rely on the complex integration of scientific need, regulatory oversight, quality control in collection, processing and tracking, and linkage to robust phenotype information. The COVID-19 pandemic amplified many of these considerations and illuminated new challenges, all while academic health centers were trying to adapt to unprecedented clinical demands and heightened research constraints not witnessed in over 100 years. The outbreak demanded rapid understanding of SARS-CoV-2 to develop diagnostics and therapeutics, prompting the immediate need for access to high quality, well-characterized COVID-19-associated biospecimens. We surveyed 60 Clinical and Translational Science Award (CTSA) hubs to better understand the strategies and barriers encountered in biobanking before and in response to the COVID-19 pandemic. Feedback revealed a major shift in biorepository model, specimen-acquisition and consent process from a combination of investigator-initiated and institutional protocols to an enterprise-serving strategy. CTSA hubs were well equipped to leverage established capacities and expertise to quickly respond to the scientific needs of this crisis through support of institutional approaches in biorepository management.

COVID-19 pandemic response varies by clinical trial sponsor type.

The COVID-19 pandemic has impacted millions of lives globally. To learn more about this disease and find potential diagnostic, therapeutic, and preventative products, the healthcare community has initiated a staggering number of clinical trials. ClinicalTrials.gov was reviewed to determine if trial sponsor type had a relationship to time to COVID-19 response, which was defined as the date from disease discovery in Wuhan, China to ClinicalTrials.gov study "First Posted" date. A total of 673 United States (US) sponsored, interventional study listings were retrieved, of which 293 (43.5%) were Industry-sponsored, 349 (51.9%) were Academic sponsored, and 31 (4.6%) were Other sponsor types. Of the Academic studies, 181 (51.9%) were Clinical and Translational Science Award (CTSA) hubs. The average response time for all sponsor types was 189 days, with Academic sponsors having the shortest average response time of 172.6 days (P < 0.001). CTSA hubs had a significantly (P < 0.001) shorter average response time (168.1 days) compared to all other sponsor types (197.4 days). However, while shorter in duration by 9.4 days, response time was not significantly different from non-CTSA sponsors (177.5 days; P = 0.238). Additionally, ANOVA indicated significant relationships (P < 0.001) between funding type, study phase, number of sites, and enrollment size on response time. Studies posted with the shortest response time were Academic-sponsored trials and included smaller sized investigations of repurposed approved or investigational drugs for the treatment of COVID-19 symptoms. A small second wave of study postings occurred approximately 4 months later, and included small, unique therapies targeting prevention or treatment of COVID-19.