The viability of Parkinson's monitoring by microneedle patches: A theory-guided critical analysis

Diagnosis and treatment of Parkinson's disease (PD) are challenging because levodopa (LD)-dependent therapies primarily rely on symptom observation and management. More sophisticated methods for LD tracking, namely, high-performance liquid chromatography, UV, and mass spectrometry, etc., are expensive and slow. As a potential alternative, wearable microneedle (MN)-based patches, coated with nanodendrites (NDs), offer promising, continuous, and minimally invasive LD monitoring. Laboratory-based platforms show high sensitivity and sub-micrometer detection, but a predictive design framework does not exist. Here, we report an analytical framework I=f(LD) for ND-on-MNs, quantifying the amperometric response I of an ND-on-MN platform in terms of geometric, catalytic sensor parameters, and environmental conditions. We find the counter-intuitive results that the environmental factors (e.g., low medium diffusivity and LD fluctuation), rather than the details of sensor geometry, dictate the sensitivity limits. A scaled response against platform parameters provides key insights: (a) A maximum enhancement factor for this platform is around 12%, emphasizing the importance of optimizing sensor parameters; (b) Design strategies focusing on high-density sensing sites and efficient LD-ND binding offer the most effective solutions for improved detection; and (c) Increasing geometric dimensions is not recommended due to potential patient discomfort. The model, validated against experimental data, highlights the limitations of ND-on-MN technology for LD tracking and suggests directions for optimizing MN-based devices for PD management, including enhancing selectivity.