Poster W1 - Modelling a Multi-analyte, Minimally-invasive Biochip for Physiological Status Monitoring in Triage and Allograft Stratification

Introduction: Hemorrhage, a life-threatening condition marked by rapid blood loss and tachycardia, requires real-time monitoring of key physiological markers for optimal management(1). The Hemorrhage Intensive Severity and Survivability (HISS) score has been developed to immediately and continuously integrate measured metabolic indicators (glucose, lactate, pH, potassium, pO2) that are directly linked to the pathophysiology of hemorrhagic shock via a minimally invasive biochip array - The Physiological Status Monitoring Biochip (PSM Biochip)(2). A computational model that describes the individual biosensor elements of the array seeks to integrate functionality across the penta-analyte device as an adjunct to triage and allograft stratification (3). Table 1 shows the various physiologically relevant analytes, the motivation for their inclusion on the biochip, the method for conferred specificity, the electrochemical technique and transducer format used in their measurement.

Materials and

Methods: Microlithographically fabricated (lift off) biochip devices are shown in Fig. 1. Each biochip comprises five discrete sensor elements. The measurement and monitoring of glucose and lactate was made using generation-2 enzyme-amperometric biosensors that comprise a Microdisc Electrode Array (MDEA) architecture with supporting counter and reference electrodes. The potentiometric measurement and monitoring of potassium was made using a Microdisc Electrode (MDE) architecture fashioned with valinomycin carrying electroconductive hydrogel. The impedimetric measurement of pH was made using an Interdigitated Microsensor Electrode (IME) architecture fashioned with a pH-responsive hydrogel. The voltametric measurement of pO2 was made at a MDE architecture fashioned with under potentially deposited platinum nanoparticles. Computational models of the five sensor elements of the penta-analyte PSM Biochip were designed in both 2D and 3D using COMSOL Multiphysics v6.0 run on a PC.

Results, Conclusions, and Discussions: The MDEA glucose and lactate biosensors, employing glucose oxidase and lactate oxidase, were validated in 0.1 MFcCO2H and modeled as PPy/PPy+•PSS- mediated enzyme-amperometric reactions of linked Hill and Butler-Volmer equations. The potentiometric response of the MDE K+ sensor was modeled using the Nikolsky–Eisenman equation. The impedimetric response of the IME sensor was validated in 0.1M [Fe(CN)6]3-/4- and the pH responsive AEMA-hydrogel-IME was modeled as a cationic hydrogel by coupling the Langmuir availability of ionic states of the ionogen with the electrical charge given by Poisson’s equation across physiologic pH ranges. The MDE pO2 sensor was modeled as a voltametric sensor using the microelectrode form of the Randles-Sevcik equation that was linked to a Langmuir adsorption of O2 to nano-enabled Pt. The effect of overlapping electric fields and minimum feature size were examined to determine the smallest possible biochip footprint. All systems showed excellent agreement (p>0.05) with previously published data. Figures of merit include limit of detection, sensitivity, dynamic range, and response time are being explored as a function of design parameters.
References
1. A. Bhat et al., Journal of Translational Medicine 18, 1-17 (2020).
2. A. Guiseppi-Elie, Analytical and Bioanalytical Chemistry 399, 403-419 (2011).
3. J. R. Aggas et al., Bioengineering 10, 434 (2023).

Acknowledgements (Optional): Funding support of the Texas Engineering Experiment Station (TEES) through a TEES Research Professorship to AG-E (TEES-246413).