Demonstration of POC Biosensor Toward Clinical Translation for Patient Bed-side Monitoring
| dc.contributor.advisor | Prasad, Shalini | |
| dc.contributor.advisor | Walker, Amy V. | |
| dc.contributor.committeeMember | Muthukumar, Sriram | |
| dc.contributor.committeeMember | Sirsi, Shashank | |
| dc.contributor.committeeMember | Ardestani Khoubrouy, Soudeh | |
| dc.creator | Tanak, Ambalika Sanjeev | |
| dc.date.accessioned | 2024-03-22T19:31:07Z | |
| dc.date.available | 2024-03-22T19:31:07Z | |
| dc.date.created | 2021-12 | |
| dc.date.issued | December 2021 | |
| dc.date.submitted | December 2021 | |
| dc.date.updated | 2024-03-22T19:31:08Z | |
| dc.description.abstract | The research presented in this dissertation focuses on developing and characterizing a multiplexed affinity based electrochemical biosensing device toward clinical translation. The goal of this work is to establish a portable POC device for early disease detection across diverse healthcare applications using low sample volume, rapid response time and usability amongst minimally trained individual relying on ASSURED (Affordable, Sensitive, Specific, User friendly, rapid, and Robust, Equipment free and Deliverable to end users) criteria. Primarily, we designed a robust, non-faradaic electrochemical affinity biosensing platform for the rapid assessment of parathyroid hormone (PTH) as a single biosensing system. Unique high density semiconducting nanostructured arrays on a flexible sensing surface were used to create the analytical nanobiosensor. The surface modification technique was specifically designed to improve the interaction of the nanostructure–biological interface to capture the desired PTH level in HS and plasma. This was followed by evaluating the analytical performance of the developed biosensor with clinical rigor. The assay validation results were compared with laboratory standard as reference with results that demonstrated comparable performance with higher accuracy. Next, the scope of the biosensor was expanded to solve a clinically challenging problem of detecting host immune markers for life-threatening sepsis infection. Herein, we demonstrate a first-of-a-kind multiplexed POC biosensing device that simultaneously detects a panel of eight key immune response cytokine biomarkers in sample volume equivalent to two drops of plasma and whole blood within 5 minutes without sample dilution. Moreover, this work focuses on validating the developed biosensing device with LUMINEX standard reference method for clinical translation using nearly 200 patient samples. The DeTecT (Direct Electrochemical Technique Targeting) Sepsis biosensing device is surface engineered with specific capture probes that utilizes EIS to measure the capacitive impedance change reflecting binding interactions between the capture probe and target biomarker enabling multiplexed detection. Specificity of the biosensor was validated using cross-reactive studies, which displayed insignificant interference from non-specific biomarkers. The biosensor also displays stable and repeatable performance. The novelty presented in this research combines the effectiveness of choosing specific host immune response biomarkers for detection of sepsis combined with unique surface modification strategy coupled with EIS technique to enable efficient clinical decision-making process. This unique sensor technology would allow medical practitioners to facilitate targeted interventions for septic patients as a rapid prognostic approach, preventing complications arriving from sepsis. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | ||
| dc.identifier.uri | https://hdl.handle.net/10735.1/10081 | |
| dc.language.iso | en | |
| dc.subject | Engineering, Biomedical | |
| dc.subject | Economics, Commerce-Business | |
| dc.title | Demonstration of POC Biosensor Toward Clinical Translation for Patient Bed-side Monitoring | |
| dc.type | Thesis | |
| dc.type.material | text | |
| local.embargo.lift | 2023-12-01 | |
| local.embargo.terms | 2023-12-01 | |
| thesis.degree.college | School of Engineering and Computer Science | |
| thesis.degree.department | Biomedical Engineering | |
| thesis.degree.grantor | The University of Texas at Dallas | |
| thesis.degree.name | PHD |
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