The lack of affordable and practical HIV diagnostics, including assays to monitor HIV RNA levels (""""""""viral load"""""""") and to diagnose HIV infection in infants, has been identified as a major barrier to HIV care worldwide. For resource-limited settings, a useful HIV RNA diagnostic assay would be simple, automated, and rapid and cost less than $10 per test. We propose to develop an HIV virion assay that meets these specifications using BioScale's proprietary sensor format. We hypothesize that capturing whole virions with specific physiological receptors (DC-SIGN, CD4) and/or new monoclonal antibodies against surface epitopes and integrating them into an assay on BioScale's detection platform will provide a sensitive new diagnostic that meets requirements of resource-poor setting. In the first year of the project, capture surfaces will be functionalized using recombinant soluble CD4, recombinant soluble DC-SIGN, and new anti-gp41 and anti-gp120 antibodies to create a novel system to capture and isolate HIV virions and anchor them to the sensor surface. In the second year, this new HIV virion assay will be optimized and validated for sensitivity and specificity compared to standard viral load measurements (i.e. RT-PCR) in 75 HIV-infected subjects. The successful completion of this proposal will demonstrate the feasibility of BioScale's HIV assay for resource-limited settings.
The specific aims of the proposal are three-fold: A) To develop a method to capture HIV virions using magnetic beads coated with receptors and/or new monoclonal antibodies; B) To develop a bead capture surface on the BioScale biosensor and integrate it with HIV capture beads, to create an HIV virion assay; and C) To evaluate the qualitative and quantitative threshold of HIV detection in whole blood via HIV assay testing compared to RT-PCR in HIV-infected subjects. The Phase II of this proposal is anticipated to include beta-testing of the instrument, larger clinical testing, and preparation for instrument and assay kit manufacturing and deployment in resource-limited settings.
