Nanophotonic Biosensors and the Paradigm of Trans-Scale Autonomous Bio-Integrated Diagnostics for Addressing Health Complexities

Abstract

Public health emergencies and the escalating burden of chronic diseases necessitate a paradigm shift from centralized laboratory testing to rapid, decentralized, and point-of-care (POC) diagnostics. Optical nanobiosensors have emerged as transformative tools, exhibiting high sensitivity, label-free detection, and real-time monitoring efficacies essential for addressing biomedical complexities. In this review, we critically examined the evolution of optical POC nanobiosensors from fundamental nanomaterial engineering to trans-scale autonomous bio-integrated systems. We discussed the physicochemical engineering of advanced nanomaterials, such as plasmonic nanomaterials, quantum dots, metal–organic frameworks, and 2D materials like MXenes, which considerably improved signal amplification and detection limits. It is attributed to the ability of nanomaterials to modulate light–matter interaction at the nanoscale using various physics principles such as fluorescence, photonics, plasmonic, fiber optics, interferometry, and spectrometry. Furthermore, we critically examined the convergence of nanophotonics with microfluidics, artificial intelligence, and 5G-supported Internet of Medical Things to develop smart and data-driven diagnostics. Innovative POC modules are explored, ranging from lab-on-chip and hospital-on-chip platforms to wearable, skin-embedded, and tattoo-based biosensors capable of continuous physiological monitoring. Besides, we address translational challenges related to scalability and biocompatibility, providing sustainable frameworks using green nanotechnology and self-powered triboelectric technologies to reduce ecological footprints. Future advancements depend on interdisciplinary collaboration to bridge the gap between laboratory innovations and clinical implementation. It will pave the way for sustainable, POC, and smart global healthcare solutions, raising an era of sensor intelligence.