Neurochemical profiling in urine: Multiplexed detection of dopamine and serotonin using ML-integrated laser-induced graphene biosensors

Abstract

Simultaneous monitoring of dopamine (DA) and serotonin (SER) in urine offers a non-invasive route for diagnosing neurological, psychiatric, and metabolic disorders. However, their multiplexed detection at the point-of-care remains challenging due to matrix complexity, low analyte concentrations, and overlapping oxidation potentials which complicates electrochemical testing. In this work, we developed laser-induced graphene (LIG)-based electrochemical sensors for multiplexed detection of clinically-relevant concentrations of DA and SER in undiluted human urine. We first optimized the number of laser passes and electrode size, showing that two-pass LIG improves the sensor performance compared to one-pass LIG. Additionally, Nafion-coated LIG electrodes exhibited high selectivity for DA and SER – over 88% relative to various interfering molecules – while further reducing LODs for both analytes by approximately 10 × compared to uncoated electrodes. While electrode engineering and single-mode voltammetry enabled detection of sub-micromolar DA and SER, we combined multimodal voltammetry with machine learning and achieved detection down to 5 nM for both analytes, corresponding to >60-fold and >120-fold improvements over single-mode voltammetry. The sensors were validated against high-performance liquid chromatography, showing a good agreement with less than 10% relative error. In addition, the sensors achieved recovery rates of 91%–108% which fall within the United States Food and Drug Administration regulatory requirements, highlighting the potential of the developed device for advancing urine analysis at the point-of-need, neuroscience research, and clinical care.