UCLA

In order to more effectively diagnose and treat both communicable and non-communicable diseases, it is crucial to develop diagnostic tests that are accessible at the point of care. This is especially pertinent in resource-limited settings areas, where there is a need for affordable, rapid, and robust diagnostic tests due to limited access to healthcare services and laboratory-based tests. One diagnostic modality that is well-suited for these settings is the lateral-flow immunoassay (LFA), which saw widespread use during the COVID-19 pandemic. However, the applicability of the conventional LFA to other diseases and conditions is limited by its inability to provide a quantitative readout, which this thesis aims to address.

First, we sought to improve the quantitative capabilities of the LFA by utilizing the multicolor etching of gold nanorods (GNRs). As a proof-of-concept, our group had previously combined the LFA with GNR etching in suspension to produce a multicolor readout that quantifies the concentration of digoxin in human serum. To make the assay more point-of-care friendly, we expanded upon this work in this thesis by adapting the workflow to be fully paper-based, which involved designing an all-in-one 3D-printed casing that combined both LFA detection and GNR etching via novel color-changing GNR pads. The resulting color hues from the GNR pads are easily distinguishable by the naked eye, thereby enabling a workflow that easily and quickly quantifies target biomarker concentrations in point-of-care settings.

Next, we turned to utilizing the chemiluminescence reaction of luminol as another method to improve the quantitative capabilities of the LFA. After detecting the target biomarker using the LFA, the light output generated from the chemiluminescence reaction can be quantified using a smartphone-based reader to determine the concentration of the target biomarker in the patient sample. To assist with the development of this assay, a mathematical model of the chemiluminescence reaction in the presence of phenolic enhancers—reagents that can significantly increase the light output of the reaction—was developed in MATLAB to optimize the reaction parameters and conditions.