Duke Improving Clinical and Translational Science (IMPaCTS) Challenge: General Pilot Awards (2027 – 2028)

Applications for this funding program are currently OPEN

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• Purpose
• Funding
• Eligibility
• Key Dates
• RFA and Application Instructions
• Reference Materials
• Contact Information

The Duke Clinical & Translational Science Institute (CTSI) catalyzes science that improves health—for individuals and communities—in our region and across the nation. The institute invites proposals for innovative pilot projects that improve the efficiency, effectiveness, and impact of translational research and accelerate the advancement of scientific discoveries into practice to improve health and reduce disease burden. This funding opportunity is made possible through support from the National Center for Advancing Translational Sciences’ (NCATS) Clinical and Translational Science Award (CTSA).

Purpose

Projects supported through this funding mechanism will develop generalizable solutions that improve the efficiency and effectiveness of the translational research process at one or more stages (e.g., basic science, preclinical testing, clinical research in humans, implementation into medical practice, policy, and population health impact). These challenges are shared across diseases, populations, settings, and research programs. As such, solutions developed under this mechanism are expected to have broad relevance and impact.

We invite projects that: (1) explore innovative new directions; (2) employ interdisciplinary approaches, and/or (3) establish proof of concept. This funding supports developmental, exploratory, and pilot studies, including projects that pilot the implementation of existing, proven strategies for improving clinical and translational research.

Special Focus: AI-Driven Early Translation

For this cycle, the program has a special focus on Artificial Intelligence (AI)-Driven Early Translation – the application of AI, including machine learning (ML), predictive modeling, and generative approaches, to accelerate the early stages of the translational pipeline. Responsive projects may include AI-enabled target identification and validation, biomarker discovery, selection and refinement of pre-clinical models, prediction of safety or efficacy signals to inform first-in-human readiness, or AI-assisted regulatory workflows. For more examples, please see the companion Examples of Responsive Research document. Applications responsive to this special focus are highly encouraged along with applications addressing the general scope described above. 

Methodologies

We welcome varied methodologies, including qualitative, survey, evaluation, user-centered design, systems engineering, implementation science, AI/ML, and community-engaged approaches. Applications proposing new processes, tools, technologies, or programs must include empirical approaches to inform, test, and evaluate their development.

Leveraging Existing Data, Research, and Resources

We encourage the use of existing Duke data sources, validated measures, and ongoing research programs. Examples include study-level data, administrative data (OnCore), survey data, electronic health records, and add-on studies drawing on participants from existing research (e.g., recruiting participants from an existing study into an add-on qualitative or survey study). Pilot funds may not be commingled with existing research funding; consult CTSI accelerator staff regarding allowable costs. Several Duke units support access to this data, where consultation is required. This is indicated in the Required Consultations section in the Request for Applications (RFA).A list of available data sources and supporting resources is provided in the Additional Resources document.

Examples of Responsive Research

Example topic areas are provided below. A supplementary document, Examples of Responsive Research provides more examples in each area.

• Research Process Efficiency: Projects improving regulatory workflows, study operations, or other systemic bottlenecks to enhance research quality and timeliness.
• Data Science & Technology Integration: Use of AI, ML, or data interoperability tools to advance translational research capacity.
• Mechanistic & Translational Science: Research that develops, validates, and/or implements novel tools, methods, and techniques for elucidating biological or behavioral mechanisms with clear and generalizable applications in clinical and translational research.
• Innovative Trial Design & Digital Health: Development and/or evaluation of adaptive or platform trials, or technology-enabled strategies that improve participant engagement and trial efficiency.
• Implementation & Integration into Practice: Research on approaches for accelerating the application of findings into real-world settings through evidence-to-practice frameworks and stakeholder engagement.
• Community-Engaged Research: Projects that develop, test, or evaluate community-engaged approaches (e.g., partnered study design, recruitment, retention, and dissemination) that strengthen the relevance and reach of translational research.
• Team Science & Collaboration: Projects enhancing interdisciplinary collaboration or building infrastructure for multi-institutional research.
• Workforce Development: Projects that develop, implement, and evaluate innovative training, mentoring, and career pathway programs that build the skills and capacity needed to advance translational research.
• Rural Health Challenges: Projects that develop, test, or evaluate generalizable solutions to clinical and translational science challenges encountered in rural settings. Areas may include improving research access and participation; adapting research processes for geographically dispersed populations; strengthening research infrastructure, workforce, data, or technology capabilities; improving implementation in rural healthcare settings; and accelerating the adoption and dissemination of evidence-based practices.

Funding

• The program will award projects for one funding cycle (up to 12 months) during the period of August 1, 2027 – July 31, 2028, contingent upon approval from NCATS.
• Each award will provide $25,000 to $50,000 in total costs, with $25,000 minimum direct cost.
• Cost sharing is not allowed. Pilot projects must be fully supported only with NIH funds awarded through the CTSA program (no other funding sources may be used to support these projects).
• Funds may not directly support any clinical trials.
• All salary requests are subject to the current NIH-mandated annual salary cap.
• Project must be completed within the specified funding cycle; no-cost extensions will not be approved.
• Institutional Submission Requirements: This award does not need to be routed through the Duke Office of Research Administration (ORA). All applicants, including external investigators, partners, and collaborators, are required to involve their institutional grants or business office in the preparation of the proposal budget. External investigators, partners, and collaborators must also follow all applicable proposal review, approval, and submission requirements of their home institution or organization.