Synergistic development of micro/nano fabrication for lab-on-the-needle devices: Recent advances, biomedical applications, and challenges

Lab-on-the-needle (LON) devices fabricated with micro/nanotechnology-derived methods have shown considerable attention towards the development a new type of biosensor and diagnostic device that addresses the challenges and limitations that remain in the conventional system. In particular, these LON devices, consisting of either a LON patch or a micro/nanopipette tip (M/NPT), have been emerging as a new technological frontier in biomedical analysis. This phenomenon is because of their high aspect ratio and geometrical dimensions, as well as their needle-like biomimetic structural strategy, portability, and functionalization with nanomaterials and coatings. Moreover, by leveraging recent advances in the LON patch and M/NPT platforms, they have received significant attention in biomedical and clinical settings, particularly for biomolecule and neurochemical detection, disease diagnosis, and bioimaging. This review article provides a comprehensive analysis of recent advancements to the fabrication of the LON patch and M/NPT platform, including the focus on 3D printing and pulling approaches, followed by the functionalization and coating with nanomaterials. Furthermore, it analyzes and discusses the improved detection of specific biomolecules and neurochemicals through colorimetric, electrochemical, and Surface Enhanced Raman Scattering (SERS) methods utilizing the LON patch and M/NPT platform. This approach results in low cost, minimal invasiveness, and increased patient comfort. Nevertheless, it is essential to address the challenges of its unique capabilities and the gap between the LON patch and the M/NPT platform to design a hybrid system that integrates detection, diagnostics, and treatment technologies on a single LON platform. Therefore, we present a forward-looking view on next-generation hybrid LON systems, which utilize functionalized nanomaterials and coatings. Furthermore, we have discussed the challenges of incorporating nanomaterials with LON by using the AI/ML predictive analysis model tool and translational approach for real-time detection and diagnosis in future biomedical and clinical settings.