Passive Sweat-Based Pruritic Cytokine Detection and Monitoring System

Abstract

Interleukin-31 has been reported to be involved with chronic skin conditions like atopic dermatitis (AD). This work focuses on the development of a portable IL-31 detection system that works with passive sweat over the physiologically relevant range-150-620 pg ml−1. Four simulated flaring profiles were used to benchmark the IL-31 rise and fall detection capabilities of the sensor. These temporal profiles were generated according to the SCORAD range for severity of AD and were spanned across different dosing regimens. The sensing platform displays good sensitivity with a limit of detection of 50 pg ml−1 and dynamic range of 50-750 pg ml−1 for the flaring profiles in synthetic and human sweat, and with coupled portable electronics. Furthermore, in order to create a robust and predictive system, a machine learning algorithm was incorporated to create a flare prediction system. This algorithm shows high accuracy for the test data sets and provides the proof-of-concept for the use of ml coupled electrochemical systems for chronic diseases like AD.