Theory of nanostructured sensors integrated in/on microneedles for diagnostics and therapy.

Efficient real-time diagnostics and on-demand drug delivery are essential components in modern healthcare, especially for managing chronic diseases. The lack of a rapid and effective sensing and therapeutic system can result in analyte level deviations, leading to severe complications. Minimally invasive microneedle (MN)-based patches integrating nanostructures (NSs) in their volume or on their surface have emerged as a biocompatible technology for delay-free analyte sensing and therapy. However, a quantitative relationship for the signal response in NS-assisted reactions remains elusive. Existing generalized formalisms are derived for in-vitro applications, raising questions about their direct applicability to in-situ wearable sensors. In this study, we apply the reaction-diffusion theory to establish a generalized physics-guided framework for NS-in-MN platforms in wearable applications. The model relates the signal response to analyte concentration, incorporating geometric, physical, and catalytic platform properties. Approximating the model under NS (binding or catalytic) and environmental (mass transport) limitations, we validate it against numerical simulations and various experimental results from diverse conditions - analyte sensing (glucose, lactic acid, pyocyanin, miRNA, etc.) in artificial and in-vivo environments (humans, mice, pigs, plants, etc.) through electrochemical and optical/colorimetric, enzymatic and non-enzymatic platforms. The results plotted in the scaled response show that (a) NS-limited platforms exhibit a linear dependence, (b) Mass transport-limited platforms saturate to 1, (c) a one-to-one mapping against traditional sensitivity plots unifies the scattered data points reported in literature. The universality of the model provides insightful perspectives for the design and optimization of MN-based sensing technologies, with potential extensions to dissolvable MNs as part of analyte-responsive closed-loop therapeutic applications.