The Data Managennent Core (DMC) will be responsible for overall data and information support for all components of the Program. The studies proposed in the Program represent a critically valuable source of data important for the development of an HIV vaccine. Developing a mechanism to coordinate collection of common key data elements across multiple sites can facilitate such collaboration and represents an important opportunity to leverage resources and accelerate the pace of scientific discovery concerning an effective preventative HIV vaccine based on understanding the humoral response.
We aim to develop and implement the infrastructure needed to combine data and coordinate research efforts across two successful primary HIV infection cohorts at UCSD (First Choice Program) and International AIDS Vaccine Initiative (lAVI Protocol C).
The aim i s not simply to create a combined database, but to standardize data management and retrieval procedures for issues such as HIV risk behavior, symptoms of acute HIV, antibody testing data, staging criteria, treatment history, and clinical outcomes. Legacy database solutions unnecessarily hinder investigators from querying and analyzing multi-faceted rich data sources. Such access will substantially facilitate collaborative investigations, as well as data exploration, hypothesis generation and discovery. Quality assurance procedures will also be developed and implemented to insure that combined data is cleaned, reliable, and ready for analysis. Additionally, the DMC will develop and implement the procedures necessary to manage the data generated and shared across the projects of the proposed, B Cell Immunology Partnership Program For HIV-1 Vaccine Discovery, which will be referred to as the
Through this proposal, we will develop, populate and maintain a sophisticated but user-friendly open source software system to house specimen, clinical, sequence and epidemiological data from the primary infection cohorts, which will maximize the utility of combined data from these cohorts by insuring compatibility of data, ease of use, adatabilitv to chanoina research goals and reproducible statistical data analsvis.
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