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Integrated Enzyme-Logic systems for Monitoring and Treating Autonomously Injured Soldiers. Joseph Wang (UCSD) and Evgeny Katz (Clarkson University). Project Objectives:.
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Integrated Enzyme-Logic systems for Monitoring and Treating Autonomously Injured Soldiers Joseph Wang (UCSD) and Evgeny Katz (Clarkson University) Project Objectives: To develop next-generation ‘sense and treat’autonomous devices for enhancing the survival rate among injured soldiers in the battlefield. Accomplishments/Impact/Transitions: Technical Approach: • Extend enzyme logic gate functionality towards relevant injuries in undiluted human serum samples with high fidelity • Developed enzymatic filters to enhance separation in readouts of different input combinations. • First demonstration of the applicability of enzyme gates in a porcine model of blunt liver injury • First demonstration of minimally-invasive microneedle sensor arrays for monitoring fluctuations in key metabolites within the transdermal fluid • Developed wearable textile-based electronic transducers, μ-electronic backbone to control logic gates • Developed signal-responsive materials and interfaces actuated by enzyme-based injury related gates for targeted drug delivery and sustained drug release formulation • Impact – Development of autonomous body-worn devices /systems for minimally-invasive biomarker sampling • Transitioning towards ‘Pharmacy-on-Demand’ paradigm for the controlled release of a therapeutic intervention in response to signals generated by enzyme logic sensor • Our approach involves the design, optimization, and evaluation of novel biochemical cascades composed of concatenated enzyme-based logic gates capable of performingBoolean logic operations on biomarker inputs. • This system will be applied to the autonomous processing of physiological information and interfaced with electronic transducers & signal-responsive drug-delivery materials / actuators. • By using multiple key injury biomarkers as inputs for the enzyme gates, the biochemical logic system provides high-fidelity diagnostics when compared with single biomarker sensors.