UC Davis

Biomarkers are measurable indicators of disease states or health conditions of an individual. Cellular and subcellular biomarkers offer insights for disease progression and therapeutic response. Traditional methods for biomarker detection, such as reverse transcription polymerase chain reaction (RT-PCR), enzyme-linked immunosorbent assay (ELISA), and mass spectrometry, are proven to be effective but often require complex procedures and extensive sample preparation.

To overcome such limitations, this dissertation focuses on two innovative biosensing approaches: deformation-based microfluidic devices for cellular-level diagnosis and photonic sensors for subcellular-level diagnosis. Deformation-based microfluidic devices leverage principles of mechanical filtration, inertial microfluidics, and deterministic lateral displacement to sort cells based on their deformability. A novel microfluidic device featuring a flow-focusing channel with a cylindrical post is proposed to address challenges in current deformation-based sorting methods. On the other hand, photonic sensors offer label-free detection with high sensitivity and multiplexing capabilities. Specifically, ring resonator biosensors are highlighted for their compact size and sensitivity comparable to conventional methods. This dissertation presents design, fabrication, and characterization of integrated ring-assisted Mach-Zehnder interferometer (RA-MZI) biosensor with microfluidic channel. Such RA-MZI sensor offers high signal-to-noise ratio, sensitivity, and capability to detect optical changes in a larger dynamic range. Additionally, by integrating microfluidics, sample volume can be minimized.

This dissertation research lays the groundwork for the development of point-of-care platform. By sequentially connecting the deformation-based droplet separation microfluidic device with the RA-MZI photonic sensor, a single system can be created which can be used for purification and detection of desired subcellular biomarkers within urinary or blood samples. This innovative device would enable quick, sensitive, and real-time detection, which could have a wide range of applications in diagnosing, predicting, and monitoring diseases.