This application to RFA-AI-19-002 is to continue as the statistical and data management center (SDMC) for the HIV Prevention Trials Network (HPTN). The overarching goal of the HPTN is to identify acceptable, feasible, safe, effective, and scalable interventions for HIV prevention that address the needs of populations at risk in the US and around the world. The HPTN will address this goal through identifying: 1) new biomedical products and tools for HIV prevention that have unique characteristics, such as longer duration of action, new targets of HIV inhibition or as multi-purpose technologies; 2) integrated strategies that optimize use of proven efficacious prevention interventions tailored to specific populations at risk to achieve maximal public health impact. The HPTN SDMC is housed at the Fred Hutchinson Cancer Research Center in Seattle and takes advantage of the particular strengths of the institution, which also includes the HVTN SDMC, and data and coordinating centers for several other research networks. The HPTN SDMC has faculty biostatisticians experienced in the design, conduct and analysis of global HIV prevention studies, who support the goals of HPTN research through leadership in statistical design, trial conduct and analysis, and development and implementation of innovative statistical methods as needed and motivated by HPTN scientific goals. The SDMC provides regulatory compliant data management functions for all HPTN trials, including electronic data capture directly from research sites, integration of laboratory specimens and assay results, and electronic participant reported outcomes. During the grant period, the SDMC will design and analyze Phase 1-3 trials of both antiretroviral and broadly neutralizing monoclonal antibody (bNAb) products, including completion of two Phase 3 active-controlled randomized clinical trials (RCTs) of long-acting cabotegravir (CAB LA) and two Phase 3 placebo-controlled RCTs of the bNAb VRC-01. The SDMC will fully support the development pathway for multi-purpose technologies, encompassing both acceptability and user-based design. If CAB LA proves efficacious, it will be incorporated into integrated strategy trials for populations at risk. Trial designs for integrated strategies will range from individual-randomized, to cluster-randomized (either parallel or step-wedge), to non-randomized trials, depending on the context and population. Mathematical modeling will estimate the population impact and cost- effectiveness of successful HPTN interventions in specific populations at risk. The SDMC will continue to deliver high-quality, timely, cost-efficient, and secure data management and safety monitoring functions for HPTN trials. State-of-the-art systems for data acquisition, storage, quality control, curation, and annotation, will be compliant with Clinical Data Interchange Standards Consortium (CDISC) and maintained using a continuous quality improvement strategy. HPTN socio-behavioral research is supported through flexible data interface processes with external data sources including mobile apps, SMS, tablets, and electronic Patient Reported Outcomes.
This application to RFA-AI-19-002 is to continue as the statistical and data management center (SDMC) for the HIV Prevention Trials Network, which plans to 1) conduct a program of Phase 1-3 trials for testing new agents (antiretrovirals, broadly neutralizing monoclonal antibodies and multi-purpose technologies) for the prevention of HIV infection and 2) evaluate integrated strategy interventions that optimize use of proven efficacious prevention interventions tailored to specific populations at risk. The HPTN SDMC has faculty biostatisticians experienced in the design, conduct and analysis of global HIV prevention studies, who support the goals of HPTN research through leadership in statistical design, trial conduct and analysis, and development and implementation of innovative statistical methods as needed and motivated by HPTN scientific goals. The SDMC provides regulatory compliant data management functions for all HPTN trials, including electronic data capture directly from research sites, integration of laboratory specimens and assay results, and electronic participant reported outcomes.
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