Strategies for passivating microneedle-based sensors: development, characterization and comparison

• To our knowledge, first dedicated paper on passivation methods for microneedles-based biosensor. • Characterization and comparison of different passivation techniques and materials completed. • Base for future work aiming at optimizing sensor passivations for specific applications. Microneedles (MNs) are sharp, pillar-like structures shorter than 1 mm. They can painlessly pierce the stratum corneum (SC), the outermost layer of the skin, and interface with the underlying dermal interstitial fluid, rich in biomarkers. Due to these properties, MNs have been widely investigated for several diagnostic applications. In particular, MN-based biosensors could enable the development of the new generation of minimally invasive continuous monitoring systems. To become a biosensor, the body or the tip of the needles must be functionalized. In addition, the area surrounding the MNs is usually passivated to prevent substrate interferences. Although passivation layers are widely used, there is a lack of characterization of such layers. This work aims at filling this gap, by developing, characterizing, and comparing six different passivation techniques. These include the application of polymethyl methacrylate (PMMA), Epotek 353ND, silicon oxide (SiO 2 ), parylene, varnish and an adhesive film to microneedle arrays. The performance of each method was then assessed using electrochemical measurements, optical and SEM imaging, and contact angle analysis. Significant variability was observed across the various methods and materials. When assessed in terms of the electrochemically active area available after passivation, the tape and parylene were the most promising layers, while varnish and epoxy were the worst performing materials. The PMMA performed better than the other liquid passivations, but still requires refinement due to the high degree of unwanted coverage of the needles. Finally, the SiO 2 layer seemed to be a viable option, but also remains in need of additional optimization.