UC San Diego

Since the early 1970’s, flow cytometry has been an essential biomedical tool for measuring and quantitatively analyzing cells, its applications ranging from hematology to identifying prognostic indicators for cancer, HIV and other time dependent markers of disease activity. Developing countries are at a greater risk of disease, where diagnosis is delayed due to lack of advanced resources. A W.H.O. study reveals that more than 80% of the patients in these countries are already have cancer progressed to advanced stages, at the time of diagnosis. Timely detection of these biomarkers can have a huge impact on the treatment outcome and ultimately the survival rate while simultaneously reducing the economic burden.

Despite the advancements in optical and impedance based flow cytometers for diagnosis, they are limited by a poor readout with high background noise, dependence on cell suspension matrix and photo-bleaching. Magnetoresistance (MR) biosensors overcome all of the above limitations with applications in point-of-care settings. However, prior to developing the MR flow cytometer, it is necessary to model this system based on multiple parameters like the size of the magnetic nanoparticles, applied magnetic force and hydrostatic pressure. As part of this thesis, we optimized the sensing range mathematically and have estimated that a single magnetic bead about 4.5 µm in diameter can be detected by the sensor, while generating a signal as high as 600 mOhms. Microfluidics is incorporated to ensure close contact with the sensor surface with a minimal loss of signal due to diffusion.