Clinical Biosensors: Emerging Technologies, Applications, and Translational Horizons

Biosensors have become indispensable tools in clinical diagnostics, transforming how diseases are detected, monitored, and managed. In this review, we survey six key emerging platform classes: engineered biorecognition biosensors (CRISPR-Cas, aptamer, molecularly imprinted polymers); electrochemical and electrical biosensors (graphene/MXene/quantum-dot nanomaterial transducers, field-effect, electrochemical impedance spectroscopy, photoelectrochemical sensing); optical and plasmonic biosensors (SPR, LSPR, SERS); lateral flow and paper-based assays; artificial intelligence-integrated smart diagnostics; and lab-on-chip microfluidic systems. For each, we analyze the recognition chemistry, transduction strategy, and reported clinical performance. We then map these technologies onto high-impact clinical domains: infectious disease, oncology, cardiovascular medicine, diabetes and metabolic monitoring, critical care and sepsis, and neurodegenerative disease—highlighting representative and quantitative performance metrics and explicitly distinguishing analytical performance from clinical validation status using a six-level validation framework. Finally, we discuss the translational barriers (reproducibility, matrix complexity, manufacturing scalability, regulatory pathways, and biocompatibility) and the opportunities that health-economic evidence for microfluidic platforms, AI integration, and wearable and implantable form factors offer for closing the gap between analytical performance demonstrated in laboratory settings and real-world clinical adoption.