Research Capacity Core

ABSTRACT The NYCenter for Advancing Translational Research and Health (NYCenter) Research Capacity Core (RCC) will strengthen the productivity of the research projects, the quality of pilot projects, and the overall research capabilities of researchers at the CUNY School of Medicine (CUNY MED) and the City College of New York (CCNY). Recurring emphasis will be on research that can potentially eliminate or reduce health disparities (HD). Conceptual prowess and practical familiarity with relevant research and analytical techniques are critical to research excellence and productivity; this core will focus on equipping and supporting our investigators with resources and skills through technology workshops, hands-on training, team-building initiatives to encourage collaboration, and optimized access to research equipment and resources currently scattered across the campus. Led by a team of senior researchers from diverse disciplines, the capacity-building resources and services administered through this core will be organized under four interwoven themes. The Research Technology Resource will mobilize critical research cores and instrumentation across campus to create a coordinated research infrastructure network accessible to the NYCenter investigators and campus researchers. Hands-on training in the applications of cutting-edge equipment and techniques will be provided to strengthen researchers’ capabilities in conceiving, designing, conducting, and analyzing innovative and HD-related research in their fields. The Research Design and Analytics Resource will deploy biostatisticians and bioinformaticists to provide expert consultations in rigorous research design and hands-on data analytics across scientific disciplines. We will establish hardware and staff support in data structures, data warehousing, data analytics, and communications tools consistent with NIH’s ongoing emphasis on research rigor and reproducibility. The Research Artificial Intelligence (AI) Resource will build on the reality that AI tools and concepts are defining research and innovation across disciplines, whereas significant challenges related to HD persist. We will develop and deploy data tools, learning algorithms, and devices for detecting and debiasing AI systems, particularly those used in biomedical, behavioral, and clinical HD-related research. Core tools developed or acquired, ranging from EHRs to diagnostic and language tools, will be made available, along with training to deploy them in their research. The Community Participation Resource will work closely with the CEC and investigators to implement proven strategies for engaging communities in research co-ideation, community participation in ongoing research, and strategizing to improve access to healthcare-related technologies. Additionally, it will provide communication support for investigators whose research involves access to clinical or community-drawn participants. These resources and services will strengthen the research projects and the pilot projects, enhancing the institutional HD research quality and productivity.