Collaborative Research: Improving the Performance and Design of Potentiometric Biosensors for the Detection of Extracellular Histones in Blood with Deep Learning
Edgar J Lobaton
Project runs from 09/15/2019 to 08/31/2022
The objective of the proposed research is to enable the rapid translation from aptamer selection to deployment on a potentiometric biosensor’s surface for highly selective detection. Optimization of the sensor surface will be accelerated through the use of advanced machine learning techniques to distinguish target-specific responses from non-specific binding events and electrode drift effects in complex, clinically-relevant fluids that most studies struggle to overcome. To demonstrate the effectiveness of the proposed approach, a biosensor platform for extracellular histone detection will be developed. The understanding that extracellular histones mediate tissue injury and propagate organ failure is relatively new, while the report of aptamer-based therapies is even more recent. Despite this, there have been no reports of electronic microsensors with targeted affinity for circulating histones. We therefore hypothesize that aptamer chemistry can be leveraged to functionalize the surface of potentiometric microsensors in order to perform early-stage, point of care (POC) detection of circulating histones, facilitate the identification of individuals at high risk for development of Multiple Organ Dysfunction Syndrome (MODS), and allow early treatment.