Microenvironment-optimized GelMA microneedles for interstitial fluid extraction and real-time glucose detection

Abstract

Microneedle (MN) patches have shown great potential for interstitial fluid (ISF) sampling and subsequent analytes detection, providing an alternative pathway for clinical diagnosis based on blood tests. However, MNs based detection is generally based on separate downstream assays, which cannot provide the detection in real-time. Specifically in the context of glucose monitoring, it is desirable to know the glucose level rapidly so as to guide the subsequent treatment in patients. Here, we designed a double layer MNs patch with the crosslinked gelatin methacryloyl (GelMA) tips loaded with glucose oxidase (GOx), whereas the substrate loaded with horseradish peroxidase (HRP), and 3,3′,5,5′-tetramethylbenzidine (TMB). The MNs tips allow for the ISF sampling and detect the glucose in situ via an enzymatic cascade reaction. We used 3D printing technology for MNs molding, which facilitate the customizable MNs design and optimization. Furthermore, we improved the detection sensitivity and accuracy by optimizing the microenvironment of the GelMA and the concentration of each enzymes. The performance of this MNs patch is validated in extracting and detecting glucose using an agarose gel based skin model. The results showed that within the glucose concentration range of 1.7–21 mmol/L, the MNs patch could accurately measure the unknown glucose concentration through the color values of red, green, and blue (RGB) obtained from scanned images. The all-in-one MNs patch with colorimetric functionality is easy to use and does not require specialized personnel or large-scale equipment support, making it highly promising for clinical translation and providing real -time blood glucose monitoring for patients.