Access to affordable and user-friendly health-science monitoring platforms are crucial for advancing global healthcare. While lateral flow immunoassays have been the primary solution for decades, their limited sensitivity and suboptimal sample utilization present challenges. This project represents a systematic progression towards developing economically viable sensors with heightened sensitivity, applicable to both disease diagnostics and the detection of environmental contaminants. By integrating nanoplasmonics to induce visually perceptible signals and harnessing the coffee ring effect for protein pre-concentration, we achieved a remarkable limit of detection of 10 pg/ml for sepsis-indicating biomarkers—surpassing lateral flow assays by one to two orders of magnitude while reducing the sample size by tenfold. Building on this success, the platform is now being adapted for the detection of per- and polyfluoroalkyl substances (PFAS), leveraging similar principles of concentration enhancement and plasmonic visualization. Furthermore, our integration of machine learning algorithms establishes a fully automated pipeline for smartphone-based biosensing, enabling precise sample concentration determination.
Project currently funded by: Member Fees