Automated dip-coating surface modification system for microneedle sensors

Microneedle (MN)-based electrochemical sensors enable minimally invasive, real-time monitoring of interstitial fluid biomarkers. While tremendous attention has been given to the fabrication of MNs, little attention has been given to the critical surface functionalization of the MN electrode transducers. Current modification methods often suffer from poor reproducibility and excessive consumption of costly reagents. In this study, we introduce an automated dip-coating system designed for scalable, rapid, and reproducible functionalization of MN electrode transducers with different bioreceptors. Such an automated system, in combination with the 3D-printed electrochemical cell (EC cell) and the low-volume aptamer deposition chamber, leads to scalable surface modification, highly reproducible MN sensors, dramatic reduction in the costs of expensive biorecognition materials, and a highly reliable analytical performance toward diverse wearable sensing applications. Such integration of automation eliminates common errors associated with common drop casting and manual incubations, paving the way for advanced, scalable, and large-scale manufacturing of MN-based electrochemical biosensors. • Automated dip coating enables scalable microneedle electrode functionalization • Reproducible microneedle sensors with dramatic cuts in costly biorecognition use • Advancing scalable microneedle biosensor production for wearable applications Microneedle-based electrochemical sensors are small, minimally invasive devices that can measure important health markers in the fluid just beneath the skin. They are being developed for wearable technologies such as continuous glucose monitoring, fitness tracking, and point-of-care health testing. Much research has focused on designing microneedles from different shapes and materials, but less attention has been given to how their surfaces are prepared, a step that is crucial for accurate and consistent results. Traditional methods often waste large amounts of expensive biological materials, give variable results, and are not suited for large-scale production. To overcome these challenges, an automated dip-coating system has been created. This approach makes it possible to modify microneedles quickly, consistently, and with far less use of costly reagents. When combined with simple 3D-printed tools, the system improves reliability and reduces errors from manual handling. Overall, it offers a pathway to affordable, scalable microneedle sensors for future wearable health monitoring. Reynoso et al. introduce an automated dip-coating system, enabling scalable microneedle electrode functionalization. This innovation achieves rapid, reproducible biosensor fabrication with diverse bioreceptors, reduces costly biorecognition use, and advances large-scale manufacturing of reliable microneedle-based biosensors for wearable applications.