(620g) A Diagnostics System for Monitoring Lupus Nephritis Based on Electrochemical Impedance Spectroscopy (Rapid Fire)
AIChE Annual Meeting
2015
2015 AIChE Annual Meeting Proceedings
Food, Pharmaceutical & Bioengineering Division
Poster Session: Bioengineering
Wednesday, November 11, 2015 - 6:00pm to 8:00pm
Millions of people worldwide suffer from the debilitating disease known as systemic lupus erythromatosus or SLE. Roughly half of these individuals will develop the potentially fatal kidney disorder lupus nephritis. In order to avoid this progression, maintaining SLE patient supervision through simple diagnostic testing is of the utmost importance. The following report details a novel biosensor platform for quick, non-invasive testing to assist researchers in identifying specific biomarkers of lupus nephritis for eventual patient monitoring.
The principal objective of our project is the development of a robust, low-cost, electrical biosensor capable of ultra-sensitive and highly selective protein biomolecule detection for monitoring lupus nephritis oxide platforms. We have designed a portable microelectrode sensor array platform for ultra-sensitive and highly selective detection of proteins. We have used a materials-based approach to overcome problems often associated with biosensors such as a lack of sensitivity and/or selectivity, dominance of signal noise, and adaptability of detection to a wide range of biomolecules. Point-of-care, rapid quantification of these biomarker molecules can help in various facets of disease detection, monitoring, and analysis. The key issues in protein detection have been achieving; (a) ultra-sensitivity in detection at concentrations (typically in lower pg/ml), and (b) selectivity in protein detection from complex solutions such as body fluids. We have designed a sensor for monitoring and tracking levels of vascular cell adhesion molecule-1 (VCAM-1) protein marker from patient urine samples in the range of 1fg/ml to 1μg/ml. We have demonstrated a great than 95% confidence in correlating the biosensor quantification of VCAM -1 with ELISA.