The objective of this STTR proposal is to develop a 2-D diffusion point-of-care assay (POC) for B-type natriuretic peptide (BNP). The primary goal of the proposed work is to create a test format that will allow patients with chronic heart failure to quantitatively self-monitor serum levels of BNP. Determination of baseline level of BNP and changes in this level over time have prognostic utility in patients presenting with acute coronary syndromes and acute heart failure, and data suggest that monitoring levels over time may be a useful adjunct to traditional clinical evaluation by chronic monitoring of volume status in heart failure patients and potentially in guiding their treatment. While the applications of point-of-car testing of BNP in the outpatient clinic setting are obvious, quantitative devices remain cumbersome and are not well suited to patient engagement in their own monitoring and care. In this proposal, we exploit technological advances that simplify real-time testing and data transmission in order to place testing in the hands of patients. This will be accomplished through the use of the 2-D diffusion assay platform, which consists of a nanoscale nonfouling poly(oligoethylene glycol methacrylate) brush coated glass chip that contains two types of printed microspots: stable microspots of capture antibodies and soluble microspots of detection reagents. A finger stick of blood is applied to the chip, and the protein analytes in the blood diffuse across the non-fouling brush and bind to stable spots of capture antibodies embedded within the brush. Simultaneously, the blood dissolves the soluble spots of fluorescently labeled detection antibodies, so that the detection antibodies can diffuse and label any analyte bound by the stable spots of capture antibodies. Detection is via a custom fluorescence detector that attaches to an Android smart phone and uses the phone's camera to record an image of the fluorescent microspots. Fluorescent spot intensities are converted to analyte concentration by a built in phone app. Images are automatically uploaded to a secure central server that allows a second analysis of the image to take place before automatically updating the patient's electronic health record. The assay incorporates a built in calibration scheme capable of minimizing many of the sampling variables inherent in POC testing. In addition, the microarray can be viewed through the custom detector by the naked eye and visually compared side-by-side with calibration spots when a smartphone is not available.