Integrated electronic/fluidic microneedle system for glucose sensing and insulin delivery

Abstract

Background: Precise and dynamic blood glucose regulation is paramount for both diagnosing and managing diabetes. Continuous glucose monitoring (CGM) coupled with insulin pumps forms an artificial pancreas, enabling closed-loop control of blood glucose levels. Indeed, this integration necessitates advanced micro-nano fabrication techniques to miniaturize and combine sensing and delivery modules on a single electrode. While microneedle technology can mitigate discomfort, concerns remain regarding infection risk and potential sensitivity limitations due to their short needle length. Methods: This study presents the development of an integrated electronic/fluidic microneedle patch (IEFMN) designed for both glucose sensing and insulin delivery. The use of minimally invasive microneedles mitigates nerve contact and reduces infection risks. The incorporation of wired enzymes addresses the issue of "oxygen deprivation" during glucose detection by decreasing the reliance on oxygen. The glucose-sensing electrodes employ wired enzyme functionalization to achieve lower operating voltages and enhanced resilience to sensor interference. The hollow microneedles' inner channel facilitates precise drug delivery for blood glucose regulation. Results: Our IEFMN-based system demonstrated high sensitivity, selectivity, and a wide response range in glucose detection at relatively low voltages. This effectively reduced interference from both external and internal active substances. The microneedle array ensured painless and minimally invasive skin penetration, while wired enzyme functionalization not only lowered sensing potential but also improved glucose detection accuracy. In vivo, experiments conducted in rats showed that the device could track subcutaneous glucose fluctuations in real-time and deliver insulin to regulate blood glucose levels. Conclusions: Our work suggests that the IEFMN-based system, developed for glucose sensing and insulin delivery, exhibits good performance during in vivo glucose detection and drug delivery. It holds the potential to contribute to real-time, intelligent, and controllable diabetes management.