Integrating paper fluidic liquid handling and whole blood plasma separation into silicon photonic biosensors.

Abstract

Silicon photonic biosensors have emerged as a powerful platform for various lab-on-a-chip applications. The technology can miniaturize assays, perform label-free detection, and is capable of rapid multiplexing. These qualities make silicon photonic biosensors a competitive platform to replace conventional clinical tests based on less scalable technologies. Most silicon photonic biosensors rely on external pumps to deliver samples and reagents over the photonic sensors. To increase the clinical viability of this technology, this project seeks to dramatically reduce the complexity of the bio-sensing system by integrating sample processing and fluidics via a capillary driven network. We have previously integrated paper microfluidic liquid handling with our custom silicon photonic test bench. With the work presented in this thesis, we demonstrate the integration of paper microfluidic networks into the Ratner lab’s OEM silicon photonic platform and we increase the complexity of the network to incorporate whole blood plasma separation. The Ratner lab has recently developed an ABO blood typing assay via silicon photonics. Using silicon photonics as the platform has the potential to achieve a higher level of automation than conventional ABO typing agglutination methods, while simultaneously reducing the assay time, and lowering costs. We validated our paper fluidic network with a reverse ABO typing assay based on the patient’s serology. In our system, we need to separate the whole blood sample in order to run the sample without running the risk of stopping the flow in the network. Here we demonstrate capillary network liquid handling and paper-based whole blood separation into our OEM silicon photonic system (i.e. the Genalyte Maverick). This integrated plasma separation and paper fluidic network reagent delivery make the system more suitable for point-of-care and rapid diagnostic testing applications. We hope this work helps bring silicon photonic biosensing closer to clinical adoption and more appropriate for clinical settings.