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2024 Fall CTSA Program&nbsp;Annual Meeting

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The Poster Submission period for the Fall 2024 Annual Meeting is now closed. For questions or support please contact us at <a href="mailto:fallmtg@ccos.ctsa.io">fallmtg@ccos.ctsa.io</a>.

The Poster Presentation session is designed to provide hub-selected presenters with a platform to present a poster related to the overarching theme, Building CTSA Program Impact through Innovation, Collaboration, and Equity.&nbsp;&nbsp;Poster Submissions open August 12 at 9:00 am ET and close October 25 at 3:00 pm ET.&nbsp;Eligible Submissions:Each hub may submit only one poster related to the conference theme. We ask that the UL1/UM1 Principal Investigators work with their hub’s TL1/T32 and KL2/KL12 Principal Investigators, as well as Hub Administrators, to select a Hub member (e.g., scholar, trainee, investigator, administrator, evaluator, communicator, researcher, etc.) to present a hub project or research findings that exemplify innovation, collaboration and/or equity.&nbsp;&nbsp;Submission Instructions:<ul style="list-style-type:disc;"><li>Hub Administrators will log onto the CCOS website to submit the poster abstract and poster PDF by October 25, 2024 at 3pm ET.&nbsp;<ul style="list-style-type:circle;"><li>Hub Administrators will be able to designate a delegate to submit on their behalf by email at <a href="mailto:support@ccos.ctsa.io" target="_blank" rel="noopener noreferrer">support@ccos.ctsa.io</a> by October 1, 2024.</li></ul></li><li>Upon submission, Hub Administrators and first authors will receive email confirmation of the poster submission. Changes cannot be made after submission.&nbsp;</li></ul>Poster Presentations:<ul style="list-style-type:disc;"><li>Poster dimensions can be a maximum of 44"H x 90"W.</li><li>Poster presenters must print their poster for onsite presentation.&nbsp;</li><li>Printing and delivery to the conference are the responsibility of the hub/presenter.</li><li>Posters will be randomly assigned to one of two sessions on November 14.</li><li>A jury will review posters onsite and rate them based on quality of science, quality of presentation and overall poster design. Additional awards will be given for impact in collaboration, innovation and DEIA.</li><li>Award presentations will be made at the close of the meeting on November 15.</li></ul>Attendance:<ul style="list-style-type:disc;"><li>Posters must be presented in-person during the Annual Program Meeting.</li><li>The limit for in-person registration is (5) per hub plus one (1) poster presenter, for a total of six (6) in-person attendees (speakers are counted outside of this limit).</li></ul>Communications:<ul style="list-style-type:disc;"><li>Questions about the poster sessions can be directed to <a href="mailto:fallmtg@ccos.ctsa.io">fallmtg@ccos.ctsa.io</a>.</li><li>Submission confirmations will be sent automatically to the Hub Administrator and first author.</li><li>Assistance with resubmission/deletion of posters submitted in error should be directed to <a href="mailto:support@ccos.ctsa.io">support@ccos.ctsa.io</a>.</li><li>Authors will be notified of presentation time slot, poster number and set up instructions by November 11.</li></ul>

Poster Submission Details

The Poster Submission period is now open and will close on October 25.

Poster Submission

The Fall 2024 CTSA Program Annual Meeting theme is Building CTSA Program Impact through Innovation and Collaboration. Topics to be addressed include Primary Care Practice-Based Research Networks (PBRNs), PCORnet, Translational Research to Translational Science, and Generative AI and Large Language Models in Translational Science.

2024 Fall CTSA Program Annual Meeting

2024 Fall Annual Meeting - Hub Administrators Meeting Slides

2024 Fall Annual Meeting - Hub Administrators Meeting Recording 1 of 4

2024 Fall Annual Meeting - Hub Administrators Meeting Recording 2 of 4

2024 Fall Annual Meeting - Hub Administrators Meeting Recording 3 of 4

2024 Fall Annual Meeting - Hub Administrators Meeting Recording 4 of 4

2024 Fall Annual Meeting - Hub Administrators Meeting Transcript 1 of 4

2024 Fall Annual Meeting - Hub Administrators Meeting Transcript 2 of 4

2024 Fall Annual Meeting - Hub Administrators Meeting Transcript 3 of 4

2024 Fall Annual Meeting - Hub Administrators Meeting Transcript 4 of 4

2024 Fall Annual Meeting - Steering Committee Slides

2024 Fall Annual Meeting - Opening Session Slides

2024 Fall Annual Meeting - Opening Session Recording

2024 Fall Annual Meeting - Opening Session Transcript

2024 Fall Annual Meeting - CTSA Collaborations with Primary Care PBRNs Session Slides

2024 Fall Annual Meeting - CTSA Collaborations with Primary Care PBRNs Session Recording

2024 Fall Annual Meeting - CTSA Collaborations with Primary Care PBRNs Session Transcript

2024 Fall Annual Meeting - Keynote Session Recording

2024 Fall Annual Meeting - Keynote Session Slides

2024 Fall Annual Meeting - Keynote Session Transcript

2024 Fall Annual Meeting - PCORnet/CTSA Collaboration and Innovation to Ensure Hub Engagement Session Slides

2024 Fall Annual Meeting - PCORnet/CTSA Collaboration and Innovation to Ensure Hub Engagement Session Recording

2024 Fall Annual Meeting - PCORnet/CTSA Collaboration and Innovation to Ensure Hub Engagement Session Transcript

2024 Fall Annual Meeting - Equity in Focus Session Slides

2024 Fall Annual Meeting - Equity in Focus Session Recording

2024 Fall Annual Meeting - Equity in Focus Session Transcript

2024 Fall Annual Meeting - CTSA Experiences with Transition from Translational Research to Translational Science Session Slides

2024 Fall Annual Meeting - CTSA Experiences with Transition from Translational Research to Translational Science Session Recording

2024 Fall Annual Meeting - CTSA Experiences with Transition from Translational Research to Translational Science Session Transcript

2024 Fall Annual Meeting - Application of Generative AI and Large Language Models in Translational Science Session Slides

2024 Fall Annual Meeting - Application of Generative AI and Large Language Models in Translational Science Session Recording

2024 Fall Annual Meeting - Application of Generative AI and Large Language Models in Translational Science Session Transcript

2024 Fall Annual Meeting - NCATS Session Element E/RC2/RO3 Approaches Session Slides

2024 Fall Annual Meeting - NCATS Session and Closing Session Recording

2024 Fall Annual Meeting - NCATS Session and Closing Session Transcript

2024 Fall Annual Meeting - Closing Session Slides

Agenda and Meeting Materials

If you would like to view the meeting materials from this meeting, please reach out to <a href="mailto:support@ccos.ctsa.io" target="_blank" rel="noopener noreferrer">email CCOS Support</a>.

Meeting Materials

The Fall 2024 CTSA Program Annual Meeting brings together personnel from CTSA Program Hubs with active grants for networking, sharing best practices and knowledge sharing. Topics to be addressed include:&nbsp;<ul><li>Primary Care Practice-Based Research Networks (PBRNs)&nbsp;</li><li>PCORnet&nbsp;</li><li>Translational Research to Translational Science&nbsp;</li><li>Generative AI and Large Language Models in Translational Science&nbsp;</li></ul>

Meeting Topics

Bethesda North Marriott Hotel and Conference Center5701 Marinelli RoadBethesda,&nbsp;MD&nbsp;20852,&nbsp;US

Location

A CTSA Program hub is defined as a UL1 or UM1 award with a linked KL2 or K12 award and an optional TL1 or T32 award. CTSA Program hubs may consist of a single institution or may include one or more participating partner institutions. Personnel from partnering institutions are encouraged to participate in the CTSA Program meetings. Personnel from CTSA Program hubs that have active grants are encouraged to attend.&nbsp;Attendee Limits&nbsp;In-person attendance for each Hub is limited to five (5) people, plus one poster presenter, plus any speakers from that Hub.&nbsp;&nbsp;Non-hub ParticipantsNon-hub participants must receive approval to attend the Fall Program Meeting.&nbsp;

Eligibility to Attend

Hubs will be invited to submit one representative poster for the Fall CTSA Program Meeting.

Poster Session

Please review the following documents:<ul><li><a href="https://uploads.ccos-cc.ctsa.io/2024_CTSA_Annual_Meeting_Code_of_Conduct_8db5dfdc6c.pdf" target="_blank" rel="noopener noreferrer">Code of Conduct</a>&nbsp;</li><li><a href="https://uploads.ccos-cc.ctsa.io/Roster_2024_Planning_Committee_e71bf9af82.pdf" target="_blank" rel="noopener noreferrer">Fall Planning Committee</a>&nbsp;</li></ul>&nbsp;Questions about the 2024 Annual Meeting? Please contact <a href="mailto:fallmtg@ccos.ctsa.io" target="_blank" rel="noopener noreferrer">fallmtg@ccos.ctsa.io</a>.&nbsp;

Additional Information

2024 Fall CTSA ProgramAnnual Meeting

Registration

Objective
Scientists are increasingly confronted with science critical belief systems. Politicization of science has contributed to a growing hesitancy to adopt therapeutic modalities that are the product of sound scientific evidence. To overcome these barriers, we aim to devise strategies to communicate clinical translational science (CTS) through art.
Methods
In 2022, we embedded an artist-in-residence (AIR) into the ITMAT Translational Research Immersion Program (TRIP). Since 2009, TRIP has been a pipeline program for CTS Workforce Development (WFD) through a 10-week mentored, curriculum-rich summer undergraduate research experience. Students are competitively recruited from 5 regional institutions, 6 HBCUs, and the University of Puerto Rico. Their scientific interests are matched to CTS mentor research laboratories across the University of Pennsylvania and the Children’s Hospital of Philadelphia. AIR is structured into 3 phases: (1) Immersion: To gain exposure to the scientific process, (2) Production: To conceptualize the process of CTS into works of art. (3) Engagement: To create opportunities for CTS workforce, artists, and community to interact on science-to-art materializations. 
Results
Since 2022, we received 28 applications, enrolling 1 AIR per summer. The immersion of AIR amounted to ≈35hrs/yr of TRIP curricular activities. Focus groups and site visits to mentors’ labs were used for in-depth explorations of the science space. Deliverables comprised (i) an AIR-led scientific workshop culminating in (ii) an “Empowering CTS Communication” public event where TRIP students engaged with community members through elevator pitches of their CTS summer project on a rotating basis, (iii) a month-long art-CTS exhibition featuring contributions from AIR, TRIP students, and ITMAT members to draw the public into art-science conversations (≈100 registrants for the opening event), (iv) mobile clay studio where TRIP students transformed their CTS projects into artwork guided by AIR, followed (v) by a public event where TRIP students used their science-artwork to engage the community  and (iv) a public installation of the clay artwork planned for Spring 2025. Qualitative insights were that TRIP is an effective art-science incubator, students strengthened their CTS communication skills, and art functions as an icebreaker between science and communities. 
Conclusions
We established a model to embed an AIR into an existing CTS WFD program. This iterative process evolved (i) from conditioning TRIP to establish mechanisms for data collection, (ii) creating a safe space for art and science to interact with beneficial friction, (iii) expanding the students’ toolbox of science communication through hands-on artwork, (iv) to eventually building a connective tissue between art, science, and communities. Success indicators are the artists’ exceptional expertise in art, teaching, and community engagement. This model will strengthen the impact of CTS in the public.

Enhancing knowledge transfer through art: An artist-in-residency program to develop a model for clinical translational science to multiply science communication through a science-art-public partnership

Background: Approximately 1 in 5 US children have obesity. Primary care-based screening for healthy lifestyle behaviors is one way to identify children at risk of obesity and related consequences. When screening is implemented, however, providers often lack the tools to connect patients and families to resources to address identified needs. Our study sought to identify essential elements of an electronic health record (EHR)-based screening and community referral system to help pediatric patients meet physical activity and nutrition guidelines.

Methods: Our mixed-methods study was conducted at a large, academic pediatric medical center and the surrounding community in a Midwestern US city. Guided by Sociotechnical Systems Theory, qualitative data was collected from in-depth interviews (n = 17) with health care workers, as well as from focus groups with community organizations (n = 15), parents and guardians of pediatric patients (n = 9), and a bioinformatics team (n = 5). Data were coded with Dedoose using a hybrid inductive/deductive approach and informed a subsequent survey with health care providers (n=40). Descriptive statistics were summarized with REDCap and interpreted alongside qualitative findings.

Results: Participants indicated that a screening-referral system would need to be trusted, sustainable, and tailored. Screening should be anchored in a non-judgmental conversation, streamlined and time efficient, and offer options that cater to individual circumstances and needs. Referrals to community resources would need to be sourced from a comprehensive and high-quality database, tailored to an individual’s preferences, and kept up-to-date. Participants emphasized the importance of families’ control over warm handoff and follow-up decisions and acknowledged the challenge of balancing affordability with community organization operating costs to facilitate connecting families to resources in a sustainable way.

Conclusions: Overall, participants believed a system to facilitate community referrals for physical activity and nutrition would be valuable and having options throughout the system would help maximize acceptability. Our study explored a novel way to use EHR-based screening to link pediatric patients to community resources that could help them meet physical activity and nutrition recommendations, and generated recommendations to guide future innovations to improve the health and well-being of pediatric patients with obesity-related lifestyle risk factors.

From Assessing To Connecting: A Formative Research Study For Pediatric Patients With Physical Activity And Nutrition Needs

Clinical researchers frequently need to conduct counts of patient populations based on specific conditions and events across multiple institutions to generate hypotheses and assess clinical trial feasibility.  Determining patient counts across institutions is labor intensive and inefficient without normalized databases that have been engineered to permit interoperability, and without applications that can query the databases with a point-and-click interface that investigators can use easily.  At the Institute for Translational Medicine, we connected normalized databases engineered for the National Patient-Centered Clinical Research Network (PCORnet) at the University of Chicago, RUSH University Medical Center, and Loyola University Chicago to Leaf, a flexible, user-friendly, secure, and open-source web application created at the University of Washington's Institute of Translational Health Sciences to enable cohort discovery.

Methods:  We leveraged existing informatics infrastructure developed for PCORnet and selected the following data domains to connect to three institutional implementations of Leaf: demographics, encounters, diagnoses, procedures, and death, with an initial data load of January 1, 2016 to March 31, 2023.  Data were deidentified according to definitions specified by HIPAA and secured behind three institutional firewalls.  We determined governance around use of the cohort discovery tool and pursued a memorandum of understanding signed by institutional officials from the three institutions allowing sharing of patient counts in a federated manner given specific conditions and events.  We deployed the Leaf tool together with partners from our institutions' information technology departments and developed training modules to distribute to clinical researchers to encourage use of the tool.  The Leaf application was launched in August 1, 2023 (https://chicagoitm.org/itm-leaf/).

Results:  We connected data for 2,370,523 patients to Leaf (UChicago: 939,769, RUSH: 778,468, Loyola: 652,286).  Demographics, encounters, diagnoses, procedures, and death information were easily queryable through a concept tree and search bar.  Query performance was excellent, and generally took less than five seconds to complete.  There have been no application outages since deployment.  Between August 1, 2023 and July 31, 2024, the number of unique users per month ranged from 1-6 at UChicago, 4-17 at RUSH, and 0-4 at Loyola, whereas the number of unique queries per month ranged from 3-20 at UChicago, 17-273 at RUSH, and 0-20 at Loyola.

Conclusions:  Cohort discovery was enabled across three institutions by connecting PCORnet databases to three Leaf applications allowing for federated inter-institutional querying.  Use varied by institution, likely due to the existence of other self-service tools at some participating institutions.  Expanding the number of data domains available in Leaf for query may increase use.

A New Leaf: Cohort Discovery through the Institute for Translational Medicine

Background: Early life environments impact lifelong health, yet the effects of childhood exposure to public investments on community-based resources (public primary and secondary education, libraries, parks and recreation, community development and housing) on adult health remain unclear. 

Objective: To examine the associations between childhood exposure to local - combined city, county, school district - public spending on community-based resources and adult physical and mental health outcomes. 

Methods: We conducted a retrospective longitudinal analysis of merged data from the Fiscally Standardized Cities dataset and U.S. Census spanning 1977-2017 and outcome data from the 2019 national Panel Study of Income Dynamics. Sample was limited to respondents living in childhood cities with populations over 150,000 residents in 1980. The dependent variables were adult self-rated health (fair/poor; primary), cardiovascular disease (CVD), and anxiety or depression diagnoses reported 2-42 years later in 2019. Our independent variable summed the city, county, and school district operational spending per capita within a city’s boundaries on community-based resources available to respondents during childhood. Weighted linear probability models were estimated, adjusting for adult demographics, childhood city characteristics, and public spending on remaining categories (i.e. hospitals). 

Results: The sample included 2,164 adult respondents (mean age 37 years). In 2019, 17% rated their health as fair/poor. For every 1% increase in childhood resource spending, the probability of reporting fair/poor health and CVD decreases by 0.21% (95% CI: -0.36%, -0.05%) and 0.26% (95% CI: -0.45%, -0.08%), respectively. Increased public education and library spending were linked to lower reports of poorer health, while higher spending on education and community development and housing was associated with fewer CVD reports. Results were not significant for anxiety/depression. 

Conclusion: Childhood exposure to public spending on community resources, particularly education, is associated with improved overall health and less CVD as adults. Local budgetary decisions regarding resource allocation should consider their long-term health implications.

Childhood Exposure to Public Spending on Community Resources and Adult Health Outcomes

Background: Randomized controlled trials (RCTs) have found rapid, robust, and enduring therapeutic effects after 1-2 applications of psilocybin when paired with behavioral therapy, known as psilocybin-assisted therapy (PAT). PAT shows promise in treating alcohol (AUD) and other substance use disorders, however the neuropsychological mechanisms have yet to be identified. The neuropsychopathology of addiction is characterized by heightened negative emotionality (NE; i.e., low mood), abnormal incentive salience (IS; i.e., drug craving), and impaired executive functioning (EF; i.e., behavioral control). Therefore, the present results and future study designs examine PAT effects across these domains.  
Methods: In a double-blind, placebo controlled RCT, 93 patients with alcohol use disorder (AUD) were randomized to two administrations of psilocybin (25-40/mg/70kg) or active placebo (diphenhydramine, 50-100mg). Pre-to-post treatment effects were evaluated for: 1) drinking behavior, 2) craving, 3) confidence and temptation to drink; 4) self-compassion; and 5) personality traits. In a subsample (n = 11), functional MRI (fMRI) analyses examined psilocybin-induced changes in neural activity and functional connectivity to alcohol and visual stimuli. 
Results: Psilocybin-treated patients showed a significant reduction in Percent Heavy Drinking Days and Drinks per Day relative to placebo (Figure 1). Psilocybin-treated patients also reported lower craving and temptation to drink and greater confidence and self-compassion (Figures 2 & 3).  Relative to placebo, psilocybin treatment induced lower neuroticism and greater extraversion and openness. Decreases in impulsivity, a facet of neuroticism, were associated were lower drinking rates across the post-treatment follow-up period. Pilot fMRI data suggest that PAT increased activity and functional connectivity in prefrontal cortical brain areas associated with executive functioning, and decreases activity in brain areas associated with craving (Figure 4). 
Discussion: These results suggest that PAT may directly intervene on the neuropsychopathology of AUD, implicating the NE, IS, and EF domains of addiction. PAT elicited similar changes in neural activity to alcohol and affective stimuli, which may reflect a general alteration in emotional processing. 
Next steps: In an NIAAA-sponsored RCT (N = 120), we will examine the neuropsychological mechanisms of a single dose of psilocybin in patients with AUD who are in a 28-day residential treatment program. In a NIDA-sponsored multi-site RCT (N = 240), we will examine the efficacy and psychological effects of a single dose of psilocybin in patients with opiate use disorder (OUD). In the NIDA trial, patients will be adhering to methadone replacement therapy, but still actively using illicit opiates. Both study designs integrate PAT into pre-existing standards of care and examine psilocybin’s effects on the core features of addiction in difficult-to-treat populations.

Psilocybin-assisted Therapy for Addiction: Preliminary Evidence and Study Design for NIH-funded RCTs

SMART IRB is a platform that encompasses a common IRB reliance agreement (the SMART IRB Agreement) and a suite of resources to facilitate single IRB review. With over 1,295 Participating Institutions from across the US, including all CTSA Hubs, the SMART IRB Agreement has become the gold-standard approach to single IRB oversight for domestic multisite research. Now, the Agreement is undergoing important changes to: 

Address feedback from current and potential Participating Institutions
Incorporate 2018 Common Rule changes to IRB Review Requirements
Enable additional federal department/agency participation (e.g., US Department of Veterans Affairs, Department of Defense, Department of Energy, and others)

Launched in 2016, SMART IRB is funded by the NIH National Center for Advancing Translational Sciences. Over the years, SMART IRB has accelerated efforts to grow its network, support and train institutional representatives and study teams in the implementation of single IRB review and promote harmonization across the nation.

In 2020, the implementation of Version 2.0 of the SMART IRB Agreement enabled NIH to join as a Participating Institution. Subsequently, work began towards the next update to the agreement (Version 3.0). Proposed changes were circulated to and discussed with representatives from federal agencies, who provided critical feedback and requested revisions that would allow them to join SMART IRB. Feedback was also elicited from the SMART IRB Ambassadors and Harmonization Steering Committee (HSC). Finally, comments from annual symposia, monthly SMART Talks, and help desk tickets were reviewed for thematic concerns.

Between November 15, 2023, and February 15, 2024, the SMART IRB Team sought public input on Version 3.0 from the broader single IRB and research community, which yielded: 250 unique comments and suggested revisions to the Agreement from 54 institutions: Academic Medical Centers/Universities, Independent/Commercial IRBs, Community Advocacy Organizations, Research Consortiums.

Further revisions in response to community feedback will be available for a second public review period in fall 2024, with an expected implementation of Version 3.0 in early 2025. The SMART IRB Agreement is a “treaty” among the signatories; it is not “owned” by any one institution. Input from all interested parties has been essential to the success of SMART IRB from the very beginning, informing the original Agreement and subsequent revisions, while fostering collaboration and building trust within the single IRB research community.

SMART IRB Reliance Agreement Version 3.0: Building the Future of Multisite Research & Single IRB Review

Lichen sclerosus is a chronic, inflammatory skin condition that remains underrecognized and underserved, with an estimated prevalence ranging from 1 in 300 to 1,000 individuals. It predominantly affects women, most commonly affecting vulvar skin, where it is known as vulvar lichen sclerosus (VLS). The condition leads to severe quality-of-life impacts, including irreversible scarring, sexual and genitourinary dysfunction, and psychological distress. Despite its significance, there are no FDA-approved therapies for VLS, and the molecular drivers of disease progression remain poorly understood. To address this gap, we employed single-cell RNA sequencing (scRNAseq) and spatial transcriptomics (ST) to identify key molecular regulators and cell-type-specific signatures in keratinocytes, fibroblasts, and immune cells that contribute to VLS pathogenesis. By integrating scRNAseq’s high-resolution gene expression data with ST’s spatial context, we uncovered distinct cellular and molecular alterations in VLS skin, including heightened stress responses in fibroblasts and keratinocytes, and enhanced T cell activation. Dysregulation of the IFN, JAK/STAT, and p53 pathways was observed, offering potential therapeutic targets. This combined approach offers a promising strategy to uncover disease mechanisms and develop personalized treatments for VLS, while also serving as a model for research into other rare inflammatory diseases. Our findings contribute to advancing women’s health and rare disease research, with translational potential for drug repurposing and new therapeutic development.

Uncovering the Pathogenesis of Vulvar Lichen Sclerosus through Single-Cell RNA Sequencing  and Spatial Transcriptomics: Advancing Women’s Health and Rare Disease Research

Operationalizing an Academic Learning Health System in a Large US Health System

In 2022, Advocate Health (AH) was established as the third-largest non-profit health system in the U.S., merging Atrium Health, Aurora Healthcare, Advocate Healthcare, and Wake Forest University School of Medicine (WFUSM), which serves as its academic core. This merger augmented the WFUSM academic Learning Health System (aLHS) to integrate and transition research into clinical practice effectively. Supported by the Wake Forest Clinical and Translational Science Award (CTSA) and the PCORI-funded Health System Implementation Initiative (HSII), this effort created a structured decision-making infrastructure. A centralized AH Solutions Hub was developed, combining expertise from performance improvement, change management, and implementation science, all aimed at enhancing healthcare quality and safety. Additionally, a care site phenotyping tool was introduced, facilitating targeted clinical research by linking patient and practice data with social and environmental indices. The aLHS Executive Committee now oversees project prioritization through a gated process, ensuring alignment with AH's strategic goals while advancing translational research and community health initiatives.

The Wright Regional Center for Clinical and Translational Science is a collaboration of partner institutions (VCU, EVMS, ODU, VSU) that serve different regions of Virginia. We utilize authentic community engagement grounded in community-based participatory research (CBPR) methods. We employ multiple strategies to engage our community and key stakeholders which includes community advisory boards, academic and policy partnerships, engaged cohorts of respondents and training sessions. Many of these engagement efforts are longitudinal. They are not project specific, but rather they are intended to inform and build infrastructure and research that aligns with our communities’ needs by creating a shared research agenda.

Wright Regional Center for Clinical and Translational Research Annual Partnership Assessment

Background: The Trial Innovation Network (TIN) is an NCATS-funded initiative designed to enhance collaboration and streamline the operational processes of multisite clinical trials. As part of the Clinical and Translational Science Award (CTSA) program, the TIN is focused on improving efficiency, fostering inclusivity, and broadening access to clinical research opportunities across a diverse range of institutions and populations, including minority-serving institutions (MSIs). 

Methods: The TIN has developed several tools and resources to optimize engagement with the CTSA hubs. One tool the TIN has implemented is a centralized, streamlined Expression of Interest (EOI) process that facilitates rapid dissemination of multicenter study opportunities across the CTSA network which addresses barriers to participation in multisite research. The TIN has established an infrastructure that supports bidirectional resource sharing via an online toolbox and monthly newsletter. The toolbox allows any site to contribute best practices, tools, and resources. This foster’s sharing and dissemination across the consortium. In addition, the TIN is also focusing on enhancing training, workforce development, and capacity building. 

Results: From 2017 to 2024, 90 proposals were submitted to the TIN for an EOI, of which 75 received one. The average response time was 13 days, with a 60% response rate from CTSAs. Additionally, the TIN developed a toolbox with 112 open-source resources developed jointly by the TICs, RIC and the CTSA, resulting in 96,468 downloads to date. With training programs like Faster Together, Training Program for Multicenter Clinical Trial Management, Statistical DIDACT, and Community of Practice, the TICs and RIC strive for continued dissemination of best practices and innovative solutions. 

Conclusion: The Trial Innovation Network provides essential resources and support to conduct efficient, collaborative trials. Its comprehensive infrastructure aims to accelerate multisite clinical research in all domains.

Trial Innovation Network - Connecting with the CTSA and Beyond

This project explores how artificial intelligence (AI) can streamline and improve clinical research administration processes. By applying AI to tasks such as Qualifying Clinical Trials (QCT) and Medicare Coverage Analysis (MCA) activities, cleaning charge master data, creating IRB consent forms from grant documents, and conducting thematic analyses of past research aims, we aim to enhance efficiency and accuracy. AI tools also assist in designing studies, offering innovative approaches to generating hypotheses and developing research protocols. These improvements are expected to reduce administrative burdens, minimize errors, and provide valuable insights for strategic planning. Ultimately, this project supports the mission of the Clinical and Translational Science Awards (CTSA) program by accelerating translational science and enhancing public health outcomes through advancing the application of developing technologies.


Transforming Clinical Research Administration: The Role of Generative AI and Chatbots

Scholars within the integrated Translational Health Research Institute (iTHRIV) participated in a novel program titled “Team Science of Team Science” (Team STS) as a collaborative investigation into an issue affecting the quality and integrity of translational research through an interdisciplinary lens. The Team STS program involves cross-discipline Scholars, who represent different areas of health research, collaborating on a research project addressing an issue that is key to successful translational science. This project represents the group effort of three health scientist Scholars, three community health workers, and two community-university liaisons to address gaps in the implementation of high-quality community engaged research (CEnR). Despite a significant amount of literature detailing best practices for community-engaged research (CEnR), there remain important gaps and challenges to conducting high-quality CEnR. Scholar authors conducted a scoping review of the literature on CEnR best practices and convened with other co-authors, who are experts in a broad range of public health issues and represent diverse backgrounds, to present identified knowledge gaps. Though a focus group involving all co-authors, we identified three major topic areas underrepresented in the literature, which all authors considered important. Authors then created a set of recommendations for addressing these gaps. Community partner recommendations for best practice in CEnR include: building and maintain trust; developing and implementing plans for dissemination and sustainability; and ensuring appropriate training for researchers early in their careers. This commentary represents a collaborative, iterative process of co-writing across diverse disciplines, research experiences, and identities. Authors identified opportunities for structural, educational, and process-related changes that will enhance the quality and impact of CEnR conducted by academic institutions and communities.

Common Gaps in Effective Community-Engaged Research

 US rural, compared to non-rural, populations have diabetes health disparities. However, it is unknown if there are rural disparities in incident and prevalent diabetes. The objective was to examine differences in incidence and prevalence of diagnosed diabetes by county rurality. We used US CDC data, 2004–2019, for county estimates of incidence and prevalence of diagnosed diabetes. County rurality was based on six levels (large central metro counties [most urban] to noncore counties [most rural]). Weighted least squares regression was used to relate rurality with diabetes incidence rates (IR; per 1000 adults) and prevalence (%) in adults aged ≥20 years after adjusting for county-level sociodemographic factors (e.g., food environment, healthcare providers). The crude IR and prevalence of diabetes were highest in noncore counties. In age- and sex ratio-adjusted models, the IR of diabetes increased monotonically with increasing rurality whereas prevalence showed a weak, non-monotonic but statistically significant increase. Further adjustment for sociodemographic factors including food environment, healthcare providers, inactivity, and obesity attenuated differences in incidence across rurality levels, and reversed the pattern for prevalence (prevalence ratios [vs. large central metro] ranged from 0.98 [95%CI 0.97−0.99] for large fringe metro to 0.94 [95%CI 0.93−0.96] for noncore). In region-stratified analyses additionally adjusted for inactivity and obesity, increasing rurality was inversely associated with incidence in the Midwest and West only, and inversely associated with prevalence in all regions. The crude incidence and prevalence of diabetes increased with increasing county rurality. After accounting for sociodemographic factors including food environment, health care professionals, inactivity, and obesity, county rurality showed no association with incidence and an inverse association with prevalence.

US County Rurality and Incidence and Prevalence of Diagnosed Diabetes

Background: Homelessness during pregnancy contributes to adverse pregnancy and infant outcomes from birth through early childhood. Washington DC, a microcosm of structural inequities in the United States, has persistent racial disparities in perinatal outcomes and housing insecurity. Grounded in a reproductive framework, we aimed to explore the lived experience of navigating homelessness assistance while pregnant.

Methods: We conducted 20 individual interviews with DC residents who experienced homelessness during pregnancy. We analyzed the data using thematic analysis and an action-oriented approach. 

Results: Participants described the experience of homelessness during pregnancy including themes related to the stress of finding safe shelter, meeting basic needs, and managing the pregnancy. Participants shared perspectives on support services including themes related to inconsistent support, importance of care and respect, and seeking long-term stability.

Discussion: Access to stable housing is critical to ensure that pregnant and parenting people  can have and raise children in a safe and sustainable environment - key tenets of reproductive justice. Housing support must be meaningfully accessible, including service delivery that acknowledges and makes accommodations from the complex social histories and competing demands that often accompany housing insecurity.

Health Equity Implications: Achieving health equity for birthing people in Washington DC requires concerted political will to promote economic justice and commit to ensuring avenues that enable individuals and families to achieve safe, sustainable, and affordable housing. Collaboration between community based organizations, health systems, and government are needed to prevent and address homelessness, achieve health equity, and mitigate the adverse perinatal health effects of housing insecurity.

Navigating Homelessness Assistance While Pregnant: A Rapid Qualitative Research-to-Policy Collaboration in Washington DC

Background: Human endogenous retroviruses (HERVs) are remnants of exogenous retroviruses that have been incorporated into the human genome throughout evolution. They have been found to be prevalently expressed in cancer genomes, contributing to oncogenesis and immunogenicity. In this project, we aim to characterize the HERV expression landscape in Pan-Cancer and to investigate associations between HERV transcription and clinical outcomes. Methods: The loci-specific HERV expressions in different tumor types from an intermember project were estimated using the Telescope algorithm with the HERV annotation database (hg38). Canonical genes, including protein-coding genes, were quantified using RSEM and STAR. Batch effects were evaluated, and batch correction was performed using the ComBat algorithm to remove unwanted variations caused by differences in sample preservation methods. HERV expressions were normalized using variance-stabilizing transformation for dimensionality reduction and clustering analysis. The optimal number of HERV clusters was determined using the Consensus Clustering approach. Results: We assessed HERV expression in ~7,000 primary tumor samples from 12 different cancer types from the ORIEN RNASeq dataset. A total of 13,640 loci-specific HERVs were identified across the primary tumors. Most of the expressed HERVs were detected in multiple types of tumors with distinct expression levels. The HERV burdens were significantly different across tumor types, with median HERV burdens ranging from 440 in Head and Neck Cancer to 1,477 in Brain Cancer. Dimensionality reduction and clustering analyses based on the expression profiles of the top 1,000 highly expressed HERVs produced distinguishable patterns across different cancer types. Association analyses suggested that HERV expression show strong correlations with patient prognosis, tumor stage/subtypes, and tumor-infiltrating immune cells. Conclusion: We identified genome-wide HERV activations in 12 cancer types from the ORIEN dataset. The HERV expression profiles successfully recapitulated the transcriptional differences of various cancer types, with cancer-specific expression patterns suggesting their great potential as biomarkers and therapeutic targets. 

Human Endogenous Retroviruses Links with Cancer Patient Prognosis and Disease Status

Genetically-informed drug repurposing analysis identifies hydralazine as a therapeutic candidate for uterine fibroids

Introduction: Uterine leiomyomata (fibroids) are benign tumors affecting up to 80% of people with a uterus by age 50. One fibroids risk factor is hypertension, and there are significant racial disparities of both hypertension and fibroids. Hysterectomy is the only curative treatment, and other surgical treatments have multiple contraindications and high recurrence rates. Current medications lack long-term efficacy. Repurposing approved medications can identify new treatment options for reducing fibroid risk. Using genetic proxies, we identified novel fibroid drug candidates and estimated effects on risk of fibroids diagnosis. 
 
Methods: We performed a genetically predicted gene expression (GPGE) analysis using S-PrediXcan and GTEx tissue models with multi-ancestry genome-wide association study (GWAS) summary statistics for fibroids from 540,104 individuals. There were 81 genes significantly associated with fibroid risk. Querying drug-gene interaction databases identified 56 approved medications that target these genes, including two anti-hypertensives, hydralazine and spironolactone. We used independent multi-ancestry GWAS summary statistics from 635,969 individuals for systolic blood pressure (SBP) and diastolic blood pressure (DBP) and conducted GPGE analyses. Blood pressure (exposure) and fibroids (outcome) GPGE summary statistics in the same tissues were used for two-sample Mendelian randomization (MR) analyses to proxy medication effects. 

Results: GPGE analyses identified hydralazine/tumor protein P53 (TP53) activity and spironolactone/thyroid hormone receptor beta (THRB) activity as drug-gene candidate pairs. Both drugs increase gene activity of their paired gene. Increased TP53 expression was associated (p < 0.05) with SBP values in four tissues (exposure). The inverse variance weighted (IVW)-MR results indicated that hydralazine use, proxied by increased TP53 expression, may reduce fibroid risk by 42% per standard deviation of gene expression (odds ratio [OR] = 0.58, 95% confidence interval [CI] = 0.49 - 0.67, p = 1.43x10-12). 
 
Increased THRB expression was associated with DBP in eight tissues and were included in the MR (exposure). The IVW-MR results indicated that spironolactone use, proxied by increased THRB expression, may reduce fibroid risk by 23% per standard deviation of gene expression (OR = 0.77, 95% CI = 0.69 - 0.86, p =5.94x10-6).
 
Conclusions: We provide biologically plausible evidence for repurposing hydralazine and spironolactone for reducing risk of fibroid diagnosis. Repurposing these hypertension medications could provide novel preventative treatments for fibroids, particularly individuals disproportionately affected by both conditions.

Background: The National Institutes of Health (NIH) Clinical & Translational Science Awards (CTSA) program, supported by Digital Infuzion (DIFZ) through Coordination, Communication, and Operations Support (CCOS), aims to enhance the impact of translational research. To measure this impact, CTSA-funded hubs have developed the Translational Science Benefits Model (TSBM), a framework for assessing clinical, community, economic, and policy impacts. However, the large scale of the CTSA program renders manual application of the TSBM infeasible, requiring approximately 1 million hours to evaluate publication abstracts alone. Automating the extraction of CTSA program insights from public data sources, therefore, offers a scalable solution, freeing researchers and administrators from additional workload while expanding opportunities for collaboration and exploration of research topics.

Approach: The CCOS Impact Analysis Team is pioneering an approach that leverages Natural Language Processing (NLP) and Machine Learning (ML) to automate impact extraction from public databases, such as NIH RePORTER and PubMed. Using NIH ExPORTER, CTSA project data and linked publication PMIDs were sourced, while PubMed API provided data for over 92,000 CTSA program publications. By applying NLP techniques, including Bag of Words (BoW) and Latent Dirichlet Allocation (LDA), approximately 300 topics were mapped to TSBM benefits by subject matter experts, allowing for automated tagging of publications with relevant impacts.

Preliminary results: show effective extraction of clinical and community benefits from publication data, while economic and policy impacts were less prevalent, prompting the integration of patent documents and ongoing efforts to incorporate policy databases. Furthermore, topic analysis of CTSA-funded publications identified certain benefits not captured by Medical Subject Headings (MeSH) terms, highlighting complementary insights from different tagging methods.

Conclusion: This strategic automation approach has enabled efficient benefit extraction, impact assessment, and alignment tracking with CTSA goals, generating valuable insights without imposing additional burdens on administrators or hubs.

Demonstrating CTSA Program Benefits: Topic Analysis of Grants and Publications Toward Automated Impact Extraction

This study successfully used a three-phase research approach that recognized Hispanic/Latino individuals as experts in how to recruit for cancer early detection research within their communities. Through seven focus groups that used a positive deviance approach, three recruitment messaging themes were identified by Hispanic and Latino HOP participants. A second phase of survey research validated and refined the messaging appeals with 42 members of the same population. A final field experiment with 610 Hispanic and Latino Oregonians tested the effectiveness and efficiency of the developed culturally relevant messaging appeals delivered through mobile phone text messages.  
 
Focus group participants identified three cultural themes relevant to their participation in HOP: trust in the academic medical center leading the study, the importance of family in both the decision to participate and as a reason to join, and respect shown to them as participants through a research process that is easy and not time consuming. 

Survey participants rated six messages developed from the three culturally relevant themes identified in the focus groups. Quantitative feedback directed researchers to the most and least effective versions of the draft messages. Qualitative feedback helped to revise specific wording and imagery to improve the draft messages. 

Experimental results demonstrated high cost efficiency for delivery recruitment materials via text messages and identified the most effective messaging condition was a static image with a trust theme and resulted in 47.4% of participants joining HOP, which was a significant improvement over a message condition based on the HOP’s top-performing social media ad (26.7% joined). Mobile phone text messaging was an efficient recruitment method, especially for static images, with more than half of participants who joined doing so after just one text.  

Recruitment of Hispanic and Latino Participants in Cancer Genetic Screening Research

The Indiana Clinical and Translational Sciences Institute (CTSI) leverages its unique statewide focus, robust research and informatics infrastructure, extensive community engagement, and broad partnership network to support clinical and translational research across Indiana and beyond. The Indiana CTSI is a collaborative effort among Indiana’s three major research-intensive academic institutions—Indiana University (IU), Purdue University (PU), and the University of Notre Dame (ND)—along with the Regenstrief Institute and numerous non-academic partners. These partners include community organizations, healthcare providers, governmental bodies, and industry leaders. Together, we catalyze research. 

Innovative projects often face barriers due to resource challenges, missing collaborators, failed recruitment or retention efforts, and data access issues. We leverage our multi-institution and statewide infrastructure to overcome these barriers, increasing these projects’ opportunities to make an impact. We offer researcher support in clinical research, informatics, workforce development, research services and support, and community engagement. 

Success stories highlight the impact of our multi-partner approach. From securing $19.9 million in federal funding to enhance pedestrian safety through a pilot community-engaged research project, to advancing kidney transplantation by developing a device to increase transplantation rates through project development teams, to assessing the economic impact of untreated mental illness to support legislative changes enhancing mental health care access and protections in Indiana. The Indiana CTSI is committed to advancing translational research and improving health outcomes. 

Indiana CTSI: Catalyzing Research

Background: Mexican American women are experiencing sexual and reproductive health (SRH) disparities that are preventable and related to one’s access to care. Previous research has demonstrated that those with lower health literacy have lower access to care and poorer health outcomes. This study explores the health literacy of young Mexican American women who have displayed positive deviant behavior, by successfully accessing sexual and reproductive healthcare (SRHC) over the previous year, to identify methods used to overcome barriers to SRH literacy and to access care. 

Methods: Using a community-engaged mixed-methods study design, participants completed a survey and engaged in semi-structured interviews with questions inspired by the European Health Literacy Survey Questionnaire. Thematic analysis was conducted on Dedoose to analyze the health literacy processes of accessing, understanding, appraising and applying health information as they relate to participant access SRHC.

Results: Participants had a range of health literacy. Barriers to access included lack of privacy and discomfort talking about SRH. SRH information was difficult to understand, and participants used apps, talk-to-text features on cell phones and clinic personnel to facilitate understanding. Having comorbidities and indecision regarding SRH choices made appraising challenging but was facilitated by seeking more knowledge. Not knowing where to get care, concerns about confidentiality and a lack of health insurance, cost, and transportation, were all barriers to applying SRH information which were overcome using clinic resources. Participants described how having trusted, experienced individuals, ‘health literacy gatekeepers,’ in their lives facilitated each of the health literacy processes and connected them to SRHC. 

Conclusion: Identification of how participants overcame barriers to the health literacy processes, by using heath literacy gatekeepers and clinic resources, can inform future work to operationalize participant strategies to address health disparities and provide a missing piece in the provider-community-client link of the translational science framework. 

Examining the Barriers and Facilitators on Sexual and Reproductive Health Literacy Processes as Described by Young Adult Mexican American Women Living in Upstate NY Using a Positive Deviance Approach

Introduction: Hepatitis C (HCV) is a significant public health threat, particularly among opioid-using populations, where injection drug use leads to higher transmission rates. Fragmented data systems hinder efforts to track and improve HCV screening and treatment. The Worcester Integrated Health Data Exchange (WIHDE), a collaboration between the City of Worcester, UMass Memorial Health (UMMH), UMass Chan Medical School (UMass Chan), and the Family Health Center of Worcester (FHCW), aims to address these challenges by integrating health data to enable targeted public health interventions. WIHDE’s initial project focuses on increasing HCV screening and treatment in opioid-using populations.
Methods: WIHDE is built on UMass Chan’s Platform for Learning Health System at UMass (PLUM), using a Data Mesh architecture to organize health data from multiple organizations into distinct Data Domains. Data from each organization undergoes an Extract, Transform, Load (ETL) process, which maps it to an enhanced OMOP Common Data Model (CDM) for consistency and analysis. Secure data transfer is ensured via sFTP servers and Amazon S3 buckets, with data stored in a Redshift warehouse under a comprehensive security structure integrated with UMass Chan’s auditing systems.
Data from UMMH and FHCW, including opioid use history and HCV screening data, are being ingested into WIHDE. Privacy-Preserving Record Linkage (PPRL) via Datavant ensures that de-identified patient data can be linked securely across organizations. Real-time dashboards, built with Power BI, provide insights into screening rates, vaccination coverage, and other public health metrics.
Results: WIHDE’s infrastructure passed UMass Chan’s security review and is fully operational. EC2 instances for data harmonization, S3 buckets for ingestion, and the Redshift warehouse are active. Data ingestion from UMMH is complete, and FHCW is in progress, with opioid use data mapped to the OMOP CDM. FHCW has identified approximately 2,100 individuals for inclusion in the dataset. PPRL infrastructure is ready for implementation pending final contract approval with Datavant.
Discussion: The integration of opioid use and HCV data in WIHDE offers a comprehensive approach to improving public health. HCV screening and treatment benefits all stakeholders: healthcare organizations gain revenue from reimbursed treatments, patients receive life-saving care, and public health systems reduce HCV transmission and associated healthcare costs. WIHDE’s infrastructure paves the way for future expansion to address other health issues. 
Conclusion: WIHDE marks a significant advance in public health data integration, improving HCV screening and treatment efforts among opioid-using populations in Worcester. The infrastructure and initial data integration provide a strong foundation for ongoing efforts to reduce HCV transmission and improve health outcomes.


The Worcester Integrated Health Data Exchange (WIHDE): A Data-Driven Initiative to Improve Hepatitis C Screening and Treatment Among Opioid-Using Populations

Chagas disease, caused by the parasite Trypanosoma cruzi and transmitted by insect vectors, is an emerging infection in the US. It affects ~8 million people globally, and ~300,000 people in the US. ~30% of chronic Chagas disease infections lead to severe cardiac or gastrointestinal complications, cardiomyopathy, and death. Though the disease is primarily contracted in endemic regions of Latin America, local transmission is increasingly being detected in the US, particularly in southern states, due to enhanced surveillance efforts. We have built a full-spectrum translational research team composed of primary care clinicians from Federally Qualified Health Centers (FQHCs) and other safety-net practices, public health practitioners, laboratory scientists, and researchers, and identified high priority areas for clinical and public health research and practice. We have built an online learning community of ~300 healthcare providers, researchers, and public health professionals, and conducted educational/training series using the Extension for Community Healthcare Outcomes (ECHO) model. These activities have increased attendees’ knowledge and confidence levels in screening, diagnosing, and treating Chagas disease, as measured by pre- and post-session questionnaires. We conducted a feasibility analysis of Chagas disease epidemiologic surveillance by extracting Electronic Health Record (EHR) data from Health Information Exchanges (HIEs), PCORnet Clinical Data Research Networks (CDRNs), and other databases. We queried Epic Cosmos, a national EHR database of >252 million unique patients, for each year from 2014 to 2024. Joinpoint regression was conducted to examine trends in the prevalence of Chagas-related diagnosis and treatment. We also queried EHR data from Einstein/Montefiore Medical Center (Bronx NY), an academic medical center in the Bronx, for each year from 2014 to 2023. Poisson regression was conducted to examine trends in frequency of Chagas disease and T. cruzi testing. We identified ~4,000 patients with Chagas disease in national databases. In Epic Cosmos, we found that the average annual percent change (AAPC) in Chagas disease prevalence was higher than the AAPC for the prevalence of related comorbidities. The AAPC for T. cruzi antibody testing was higher than the AAPC in Chagas disease prevalence. In data from Einstein/Montefiore Medical Center (Bronx NY), we found that the number of patients with Chagas disease diagnosis codes by year increased over time, while the number of T. cruzi tests by year did not. The differing trends over time in T. cruzi testing and Chagas disease prevalence indicate a significant gap in Chagas disease testing, diagnosis, and treatment in the USA. All information related to this project, including recorded ECHO training sessions, is consolidated into a dissemination website, www.CDNetwork.org/chagas.

Chagas Disease as an Emerging Infectious Disease in the USA: Building a Full Spectrum Translational Research & Learning Collaborative


Background & Aims: Surf therapy is an activity-based intervention organized around riding ocean waves to promote well-being. Previous work indirectly suggests pain-reducing effects of surf therapy, but no study has examined surf therapy in individuals for whom chronic pain is their primary complaint. Here we perform a proof-of-principle study of surf therapy in chronic pain and begin to examine its mechanism in multiple ways, including virtual reality (VR) surfing.

Methods: We studied 9 participants (6 female and 3 male) suffering from chronic pelvic pain with at least one other chronic overlapping pain condition (COPC). The study design included a baseline assessment, followed by four weekly beach sessions, ending with a follow-up assessment and a single VR surf session. The primary outcome measure was pain assessed using a 0-10 scale.  

Results: Pain was significantly reduced after each surf session compared to before. Additional pain assessments suggested this effect came from the activity of surfing and not only being in the outdoor environment. Pain was also significantly reduced following the VR surf session, suggesting that the activity of surfing may provide separable benefits from water immersion. Data at follow-up indicated a significant overall symptom improvement trajectory over the study period, with the strongest improvement occurring in patients with the most COPCs.

Conclusions: These findings provide proof-of-principle evidence that surf therapy can help alleviate pain in patients with chronic pelvic pain and COPCs, and provide groundwork for future research on how immersive activity-based interventions can play a role in the management of complex chronic pain.

The neuroscience and engineering of ocean wave surfing as a therapy for chronic pain

Background: The Trial Innovation Network (TIN), a partnership funded by the National Center for Advancing Translational Sciences (NCATS) within the Clinical and Translational Science Award (CTSA) program, addresses critical challenges in multi-site clinical research. By leveraging the extensive national CTSA infrastructure, its network partners, and fostering collaboration, the TIN accelerates the translation of innovative research into therapeutic solutions. 

Methods: Two Trial Innovation Centers (Johns Hopkins University, Vanderbilt University Medical Center) and one Recruitment Innovation Center (Vanderbilt University Medical Center) provide no-cost consultation services for multicenter studies, connecting clinical investigators with domain experts, strategic partners, and leveraging the entire CTSA network to optimize trial design and operational efficiency. The TICs and RIC have formed partnerships with more than a dozen CTSAs to enhance and strengthen the TIN consultation experience. 

Results: By working closely with investigators, the TICs and RIC have provided resources and facilitated numerous successful consultations across the TIN. 

Conclusion: The TIN offers a sustainable model for overcoming barriers in multisite clinical trials with innovative solutions, supporting the future optimization of clinical research.

Trial Innovation Network - A collaborative, academic approach to optimizing the national clinical research infrastructure

There is a shortage of qualified Clinical Research Professionals (CRPs), due to a combination of large workloads, complex tasks, inconsistent training, and lack of professional development opportunities. The Joint Task Force for Clinical Trial Competency created a competency framework for CRPs, which has demonstrated positive results from various institutions, but programs have been limited in standardization, replicability, and dissemination. In hopes of improving this, we designed the University of Texas Southwestern (UTSW) Medical Center Clinical Research Foundations (CRF) Training Program, which is a competency-based online self-paced CRP training curriculum hosted via the Collaborative Institutional Training Initiative (CITI) portal. We examined the feasibility, acceptability, and uptake of the UTSW CRF training on an institutional scale and were pleased to find that this curriculum is not only feasible, but had high levels of acceptability. Furthermore, faculty, clinicians, and trainees voluntarily completed this training program indicating utility across diverse groups. The UTSW CRF combines the existing CITI training modules with UTSW-created material, providing optimal balance between generalized clinical research education and institutionally-tailored content. We believe the UTSW CRF curriculum can serve as a plug-and-play foundational model for other research centers to tailor according to their audience and institutional needs. 

Clinical Research Foundations: A clinical research professional training program for all institutions

Clinical & Translational Science Award (CTSA) hubs are charged with building and advancing the field of translational science (TS). As a nascent field, researchers are not currently incentivized by funding agencies or institutional promotion/tenure structures to study scientific and operational barriers in the translational process. For the foreseeable future, CTSA hubs will be the primary investors in identifying and mitigating roadblocks that slow research progress. To inform strategic investment in TS, the Michigan Institute for Clinical & Health Research (MICHR) at the University of Michigan aims to develop a framework that guides us in systemically identifying, and efficiently solving, TS problems. Given that TS problems are abundant, ill-defined, complex and embedded within broader structures and dynamics, we drew from methods in the fields of design and systems thinking to craft our framework. Design thinking is an approach to problem solving and innovation that prioritizes understanding the experiences, and desired solutions, of those experiencing the problem. Systems thinking methods help us visualize and analyze problems within the context of related processes and people.  We have constructed an eight-step framework to identify and solve TS problems that centers both those who experience the problem and those charged with implementing the solution. The first four steps guide in creating a common understanding of the TS problem, identifying its root cause, and creating a holistic view of the system in which it resides. The last four steps are solutions-focused, with iterative brainstorming, testing and refining of potential solutions before they are implemented and disseminated. Each step in the framework contains a series of guiding questions, methods, outputs and metrics for rigorous evaluation. We are currently prototyping the framework with TS case studies. Ultimately, we will use this framework to ensure our resources are allocated to the most pressing TS problems important to the research community and to bring efficiency and a user-centered approach to creating TS solutions.

Strategically Investing in Translational Science: An Innovative Framework for Selecting & Solving Problems

Development of a Peer and Near-Mentoring Program to Support Early Career Research Faculty ASPIRE!: Accountability and Safe-space to, Promote, Inspire. Recharge, and Empower​

ASPIRE! (Accountability and Safe-space to Promote, Inspire, Recharge, and Empower) is a peer and near-peer mentoring program established in 2016 by a group of seven, including clinicians and non-clinician early career research faculty. All founding members participated as scholars of the TRANSFORM KL2 Program at Columbia University Irving Medical Center’s (CUIMC) Irving Institute for Clinical and Translational Research.  This abstract focuses on the program’s origins, development, and ongoing evolution. We explore the identified academic gaps for junior faculty that led to the program's creation and share the lessons learned. Furthermore, we discuss how these insights guided the implementation of a peer program across a large academic medical center campus. Our individual successes and experiences demonstrate that peer mentoring can be a powerful tool for enhancing the early academic experience.

Development of a Peer and Near-Mentoring Program to Support Early Career Research Faculty ASPIRE!: Accountability and Safe-space to, Promote, Inspire. Recharge, and Empower 

In today’s scientific landscape, cross-disciplinary collaboration is crucial for accelerating research and
innovation. However, managing multi-institutional efforts presents challenges such as aligning goals,
managing resources, and ensuring clear communication. Our project addresses these challenges by
developing a structured framework that facilitates data integration, research acceleration, and equitable
resource distribution across academic, industrial, and national lab partners.

As a case study, we apply this model to breath biomarker analysis. Breath analysis is emerging as a
non-invasive diagnostic tool, detecting conditions through volatile organic compounds (VOCs). Our
initiative aims to build a comprehensive human breath biomarker database by integrating data from
technologies like Gas Chromatography (GC), Mass Spectrometry (MS), Infrared Spectroscopy (IR),
and “Electronic Nose” (EN) devices for high-precision diagnostics.

In alignment with the CTSA Program’s focus on innovation, collaboration, and equity, this initiative will
enhance diagnostic precision and accelerate the development of diagnostic tools through structured
collaboration. Surveys conducted at key project milestones will identify strengths, challenges, and best
practices to guide future partnerships. Initially, we identified needs for flexibility due to changes in entity
funding and instrument availability. Additionally, early communication between collaborators and prior
approvals of the IRB framework and data use agreements are essential.

Ultimately, the integration of diverse data streams and collaborative strengths will move the field of
translational diagnostics forward. The resulting breath biomarker database will serve as a resource for
disease detection and personalized treatment strategies, setting new standards for collaboration in the
development of diagnostic technologies.

Building a Collaborative Framework for Advancing Non-Invasive Breath Biomarker Diagnostics

Injury to critical normal structures, such as nerves and vessels, during prostate cancer surgery can cause devastating complications for patients; yet, imaging these subsurface structures in real time during the procedure is currently not possible. Identifying and localizing nerves and vessels so that surgeons can make rapid intra-operative decisions to avoid injuries to normal structures is an unmet clinical need. This poster describes an ARPA-H project funded under its Precision Surgery Interventions (PSI) initiative to develop and evaluate new multi-modal optical imaging technology for identifying critical normal structures at depth during laparoscopic surgery. The system, termed MODIS (Multi-Modal Optical Depth Imaging System), is an end-to-end solution to eliminate the impact of iatrogenic critical structure damage during robot-assisted, laparoscopic radical prostatectomy (RARP). A multimodal, minimally invasive, optical laparoscope will image two near-infrared (NIR) fluorescent agents simultaneously and at depth that target normal human nerve, and either ureter or local vasculature. In Phase I, the MODIS system will be realized and tested in phantom and preclinical animal models and demonstrated to meet technical specifications on spatial resolution and depth sensing with real-time visualization and co-registration with the surgical field. Clinical studies will begin in Phase II, first to validate the technical performance observed in phantom and preclinical testing, and then in Phase III, to evaluate the efficacy of MODIS as an end-to-end solution for identifying critical normal structures at depth during laparoscopic RARP. In the project, Dartmouth and Dartmouth-Health are teaming with investigators at Johns Hopkins University and Oregon Health Sciences University, along with commercial partners in two start-ups, Trace Biosciences and Quell Imaging, and a major medical device company, Intuitive Surgical, to develop, test, and validate the MODIS technology in anticipation of its commercialization in the future.


Dartmouth SYNERGY Meets ARPA-H Through PRECISION SURGERY INTERVENTIONS (PSI) To INNOVATE & TRANSLATE. MODIS: a Multi-Modal Optical Depth Imaging System to identify critical normal structures at depth during laparoscopic surgery

Background: Most people who use drugs either do not seek treatment or face barriers to accessing treatment. Because primary care (PC) is often the first point of contact with the healthcare system, supporting patients in reducing risk of drug-related harms and/or use may be beneficial. In collaboration with the Washington, Wyoming, Alaska, Montana, Idaho (WWAMI)-region Practice and Research Network (WPRN), this study identified harm reduction strategies (HRS) used/recommended by patients and clinicians and explored their perspectives on the acceptability of offering HRS in PC.
Method: We used a convergent parallel mixed-method design. Patients with lived/living experience of stimulant and/or opioid use and clinicians from 3 WPRN clinics in Washington and Montana were eligible. We conducted semi-structured interviews and surveys with patients (n=10) and clinicians (n=12). We used deductive coding of interview transcripts to identify HRS used (guided by a framework created through community-based participatory research) and inductive coding to explore patient/clinician perspectives on delivery of HRS in PC. Survey data were descriptively analyzed. Data were triangulated and integrated using joint displays.

Results: Patients reported using multiple HRS to be safer and healthier without changing use, to use more safely, and to moderate use. Ten strategies were unanimously recommended by patients (e.g., safer injection practices, not mixing stimulants and opioids, safer routes of administration). Clinicians reported supporting patient HRS use through sharing informational (e.g., community resources) and tangible resources (e.g., naloxone, hygiene products, behavioral healthcare), though several HRS were not currently supported in PC. Clinicians desired more training and standardization of HR practices (e.g., naloxone prescribing). Patients and clinicians reported high acceptability of offering HRS in PC and emphasized the importance of offering multiple strategies.

Discussion: Offering HRS in PC is acceptable to patients who use stimulants and/or opioids and PC clinicians, though additional supports are needed by clinicians. Future directions include co-designing tools with WPRN clinicians (i.e., clinician-facing HRS infographic, clinical note templates, order preference list, HR and anti-stigma training) to increase the feasibility and sustainability of integrating harm reduction into primary care for patients who use stimulants and/or opioids. Tools will be disseminated to WPRN clinics.

Integrating Harm Reduction into Primary Care: A Practice-Based Research Network Collaboration

Idiopathic hypersomnia (IH) and narcolepsy are sleep disorders characterized by excessive daytime sleepiness and disrupted sleep patterns, often requiring complex procedures for diagnosis. This project aims to develop a machine learning tool to improve the accuracy and speed of diagnosing these conditions by identifying key risk factors and enabling early detection. The goal is to create a more accessible and reliable diagnostic method validated against gold-standard sleep studies such as the Multiple Sleep Latency Test (MSLT) and polysomnography (PSG).
The study analyzed 19,398 records from an academic sleep center, including clinical data, patient questionnaires, and polysomnography results collected over 10 years. Data preprocessing included normalization, handling missing values, and feature selection. Machine learning algorithms, including logistic regression and random forests, were used to develop predictive models trained on 80% of the dataset, with 20% reserved for validation and testing. Model performance was measured using accuracy, F1-score, and AUC-ROC, with subgroup analyses ensuring generalizability across diverse populations.
	For model development, data from 588 patients who had undergone both PSG and MSLT tests were used. The model identified previously underexplored clinical variables (e.g., alcohol consumption, occupation, alarm clock use) through advanced feature selection, incorporating them into diagnostic models and tools can enhance early detection and patient stratification. Preliminary results show that our multimodal model, using t-SNE and a Random Forest classifier to predict abnormal MSLT results, achieved an average of over 80% accuracy, >0.90 AUC, and >0.80 F1 score. This performance consistently outperformed alternative approaches like PCA, UMAP, and other ML algorithms, which achieved only ~60% accuracy. This suggests that the t-SNE and Random Forest combination is particularly effective for predicting abnormal MSLT results via clinical variables. 
These models are expected to complement traditional diagnostic tools by identifying new clinical predictors, enhancing screening processes, and improving co-morbidity identification and management. With its uniquely large dataset, this project enables robust, data-driven predictions, reducing reliance on expensive diagnostic tests. The extensive data and careful curation enhance the predictive models’ reliability and open avenues for future research into the links between sleep disorders and metabolic or neurological comorbidities. The impact of this work sets a precedent for applying machine learning to transform sleep medicine, enhance clinical screening for sleep disorders, and contribute to public health advancement.



Machine Learning for Sleep Disorder Diagnosis: Predictive Models for Idiopathic Hypersomnia and Narcolepsy Using Clinical and Polysomnography Data 

Health inequities based on race are well documented in access to care, life expectancy, maternal and infant health outcomes, disease burden, entry into clinical trials, representation in basic human research, insurance coverage, and much more. At the root of racial inequities in health and wellbeing is structural racism which refers to the totality of ways in which societies foster racial discrimination through mutually reinforcing systems of housing, education, employment, earnings, benefits, credit, media, healthcare, and criminal justice. These patterns and practices in turn reinforce discriminatory beliefs, values, and the distribution of resources. 

The MeasuringRacism data portal is a national population-level geodatabase of quantifiable measures and variables of structural racism to link health and clinical data. This database and web interface provides an environment to explore and examine the role of structural racism in any area of health or health-related research

Introduction and Objective: Minorities are disproportionally impacted by T2D and have higher disease morbidity; however, prognosis improves with good glucose control. Dulce Digital (DD), a simple low-cost text message program with educational, motivational and glucose reminder messages delivered 2-3 times/day over 6 months has lowered HbA1c in RCTs for diverse low SES populations. This study evaluated the reach and effectiveness of DD in real-world community settings.

Methods: As part of dissemination and implementation efforts, DD was offered throughout Southwest US sites serving low income, mostly Hispanic and Pacific Islander communities with T2D. Tailored feedback was provided based on blood glucose responses. Responses to blood glucose prompts were categorized and analyzed below 70; 71-130; 131-180; 181-250; and over 250. 

Results: Participants enrolled from 01/21-12/23-Fig 1A. Blood glucose metrics demonstrate significant incremental improvement in time in target range (p < .00001)-Fig 1B. There was enthusiastic adoption of DD by community sites with simple enrollment processes and minimal staff efforts for deployment.

Conclusion: DD texting program improved blood glucose metrics, with greater time in range for low-income diverse communities. Outreach to enroll patients in community clinic settings and outreach events can be successful and serve as an enhanced approach to support DSME/S.

OUTCOMES OF REAL-WORLD DEPLOYMENT OF THE DULCE DIGITAL TEXTING EDUCATION  PLATFORM FOR LOW-INCOME DIVERSE POPULATIONS WITH DIABETES

Over the last two decades, the research enterprise has drastically increased in size and complexity while resting heavily on a talented and interconnected workforce. While this expansion has created more career opportunities and a demand for experienced leadership, the vast diversity in research administration careers require specific experience and qualifications, particularly in the academic research setting. A viable prospect to fill this workforce gap are trained Ph.D. scientists interested in a non-academic career path. Ph.D. scientists not only hold key transferable skillsets but have the lived experience of being academic researchers who understand complex scientific concepts and the challenges of research. While Universities have acknowledged the demand for career development beyond academia, there is still a strong need to address the multifaceted environment of post-Ph.D. career path opportunities. The UC Davis Health Clinical and Translational Science Center (CTSC) Research Administration Fellowship is a two-year rotation-based training program that serves as a pipeline to prepare Ph.D. graduates and postdoctoral trainees as future leaders in research administration at leading research institutions. The program consists of CTSC specific rotations, elective rotations, and leadership and career development training. Through the core and elective rotations, the fellows will train in the program’s essential components: grant facilitation, pre- and post-award services, strategic operations and infrastructure, program management and evaluation, and programming for researcher success. At the end of the fellowship, trainees will be able to demonstrate knowledge of key principles as they pertain to academic research operations and infrastructure, an understanding and application of research development practices, applied leadership and project management capabilities, and enhanced professional and career development strategies. 

UC Davis Health CTSC Research Administration Fellowship: Preparing Future Leaders in Research Administration

To develop and evaluate an automated neural language processing tool, “Waldo,” for AE detection from unstructured text data.

Waldo: Automated Adverse Event Discovery from Text Data

Maximizing the impact of clinical and translational research relies on integrating stakeholder perspectives throughout the research process. In 2019, Tufts Clinical and Translational Science Institute (CTSI) introduced a mandatory Stakeholder Engagement Plan within our Pilot Awards Program to ensure that research initiatives incorporate the insights and needs of key stakeholders, enhancing both their relevance and public benefit. Our phased implementation has facilitated continuous evaluation and refinement, drawing on input from Tufts CTSI programs, past applicants, pilot award recipients, and community members. We developed a comprehensive suite of resources—guidance documents, templates, case studies, and consultations—to empower researchers in crafting effective engagement plans. Furthermore, we incorporated support for the dissemination and implementation of study findings, ensuring research outcomes are effectively communicated and utilized.

The Stakeholder Expert Panel (SEP), now over 40 members strong, comprises community members with diverse professional and cultural backgrounds. SEP has been pivotal in shaping the engagement process, defining review criteria, and developing strategic resources for the initiative. This collaborative effort has led to increased investigator buy-in, greater utilization of consultation resources, and high satisfaction with the tailored guidance provided. Additionally, community input is seamlessly integrated into the proposal review process, informing the Scientific Review Committee's final voting decisions and funding recommendations to Tufts CTSI Senior Leadership. Ultimately, our approach fosters stronger collaborations between researchers and stakeholders, providing a scalable model for CTSA hubs to embed stakeholder input in their research processes, thereby amplifying the impact of clinical and translational research.


Triple Win Strategy: A Scalable Model for CTSA Hubs to Engage Stakeholders, Boost Research, and Drive Results - Implementing Stakeholder Engagement Plans in Pilot Awards Programs

Background: Underrepresented researchers are disproportionately leaving the biomedical research workforce. 
Methods: The Building Up a Diverse Biomedical Workforce for Biomedical Research trial (Building Up) was a multi-center, cluster-randomized controlled trial at 25 CTSAs. The CTSAs were randomized to receive the 10-month Building Up intervention, comprised of monthly meetings, networking, mentoring, and coursework, or a usual care control. Participants were post-doctoral fellows and early-career faculty from backgrounds underrepresented in biomedical science. We compared hope, self-efficacy, resilience, and optimism between the Building Up and control arms using linear mixed models. Participants were followed for up to three years following the intervention.
Results: Two-hundred and twenty out of 224 (98%) enrolled participants completed the pre-intervention assessment and 84% completed at least one of three follow-up assessments. Seventy-nine percent the cohort identified as female, 33% identified as Hispanic/Latinx, and 33% identified as Non-Hispanic Black. Individuals in Building Up had significantly higher level of self-efficacy [Beta (95% CI): 1.23 (0.38, 2.07); p=0.005], resilience [Beta (95% CI): 0.95 (0.10, 1.79); p=0.03], and optimism [Beta (95% CI): 0.96 (0.02, 1.90); p=0.04)] as compared to individuals in the control arm.
Conclusions: Building Up improves resiliency, self-efficacy, and optimism and has the potential to improve retention of post-doctoral fellows and early-career faculty who are underrepresented in biomedical research. 

Building Up a Diverse Biomedical Research Workforce

Directors of the Utah CTSI sought to foster growth in CTSI programming through a new CTSI leadership hire. A process was designed to hire a new CTSI Assistant Director (AD) from the Utah faculty for up to two years (.20 FTE), and to provide experiential leadership training by empowering them to lead the enhancement of a select CTSI subunit. The new AD identified a CTSI core, based on her training and expertise, to benefit from capacity building and translational science innovation. Objectives were to develop and implement an approach for translational science enhancement in consultation with CTSI Directors and subunit leads. In this case, the AD chose to work with the Utah Cellular Translational Research Core (CTRC), and leveraged expertise in process design and biorepository programming from within the Biomedical Informatics Core (BMIC). This presentation describes the first year of challenges and accomplishments from the "deep dive" into a CTSI subunit. Challenges have included new and significant training needs for existing staff, difficulty increasing staffing to scale up capacity, and the complex and consuming implementation of a new biorepository tool, OpenSpecimen (facilitated by the BMIC). However, accomplishments have included a comprehensive needs assessment of the core, organizational restructuring to facilitate growth, personalized training for staff and leadership development, and comprehensive process design with continued supervision of all faculty and staff. In addition, the AD has been provided with valuable leadership experience, a new professional connection to administration in an area related to her expertise (Genomics), and continued "big picture" mentorship from Utah CTSI Directors.



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