Abstract LB157: Electrochemical biosensor in the detection of pancreatic cancer biomarkers: AI driven model & patient cohort study
Abstract
Pancreatic cancer stands as the 12th most common occurring cancer worldwide. The increasing mortality is due to the diagnosis of pancreatic cancer done at a very late stage as it is harder to pinpoint until the symptoms have advanced, causing rapid spread of the tumour affecting the pancreas and other surrounding organs. Late stage causes treatment to be less effective. There are various diagnostic tools for the detection of pancreatic cancer, the most common being scans like CT, MRI, blood tests, and biopsy, we have come to understand that utilization of electrochemical biosensors can be an efficient and sound point-of-care system in the early diagnosis of pancreatic cancer. Biosensors utilize electrode interfaces to transduce molecular recognition events into electrical signals. In our research, we use electrochemical biosensors to detect multiple protein biomarkers such as CA19-9, CA242, CEA, and CA125 in serum samples. To increase the sensitivity of the biosensors, we nanoengineer graphene oxide onto the surface to increase sensitivity and surface area. We validate our results with existing biological assays in detecting biomarkers like ELISA and Western Blot. We aim to analyze our data in an AI model to predict the risk levels.
Nanoengineering of Sensor: The gold working electrode surface of the biosensor is coated with graphene oxide nano colloidal solution and kept in UV overnight for crosslinking. Electrochemical Biosensor:The nanoengineered sensors are coated with a…
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Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence.
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