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Using Archived Data and Specimen Collections to Advance Maternal and Pediatric HIV/AIDS Research (R21 CT Not Allowed) - RFA-HD-27-007

Funder
National Institutes of Health
LOI Required
No
Application Deadline
Funding Amount
$500,000.00
Maximum Project Duration
2 years
Research Focus Areas
Training (e.g. community providers, staff, faculty, peers)
Medical Comorbidities
Description
The secondary use of archived data and/or biospecimen collections represents a critical opportunity to advance research in maternal, pediatric, and adolescent HIV. These resources enable investigators to validate prior findings, address novel hypotheses, and generate insights that extend beyond the scope of the original studies. Leveraging existing data not only maximizes the return on prior research investments but also accelerates the pace of scientific discovery in a cost-effective and efficient manner. The Maternal and Pediatric Infectious Disease Branch (MPIDB) has a longstanding commitment to the collection and preservation of high-quality HIV-related data and specimens. The strategic reuse of these HIV-related datasets and biospecimens is essential to addressing persistent and emerging research questions in maternal and child health. The integration of innovative data science methods, existing research infrastructure, and interdisciplinary perspectives to generate new insights from existing datasets is strongly encouraged. One source of data includes the NICHD Data and Specimen Hub (DASH), a centralized, controlled-access data repository for researchers to share de-identified data from clinical and population health studies relevant to NICHD populations. DASH is also a portal for requesting biospecimens from selected studies. Collections include research on HIV/AIDS, pharmacology, pregnancy, and infant care, as well as other topics across various life stages, domestic and international settings, and study types. Access to DASH is free and publicly available. Areas of Research Interest include but are not limited to those listed below: • Use of innovative and new data science approaches to study HIV, comorbidities, and/or coinfections, including advanced statistical modeling and artificial intelligence (AI); • Use of dissemination and implementation data elements to evaluate implementation science (IS) outcomes such as fidelity, adaptability, adoption, penetrance, affordability, scalability, and sustainability of evidence-based interventions in HIV service delivery models; • Research on the establishment and characteristics of HIV reservoirs across developmental stages, including examining the role of the myeloid lineage in HIV pathology and persistence; • Investigating responses to and effects of HIV and antiretroviral therapy (ART) on people exposed to or living with HIV, including those perinatally infected; • Pregnancy and post-partum effects of HIV infection and HIV treatment; • Research on markers of HIV progression and treatment response.