Recent advancements in dual modality biosensors for detecting disease causing pathogens

Abstract

Early detection of infectious diseases is crucial for timely therapeutic intervention. Biosensors have emerged as vital tools for analyte detection across biomedical, food safety, and clinical diagnostics. Despite their promising advancement, conventional biosensors face challenges such as signal noise and environmental variability. Additionally, issues like cross-reactivity and calibration difficulties in miniaturized devices compromise their accuracy and reliability. To address these limitations, dual modal biosensors have been developed, integrating two complementary detection techniques to enhance applicability. By cross-validating data, these biosensors can significantly reduce false positive and negative results while providing reliable measurements in complex biological matrices. Furthermore, dual modal biosensors expand the range of analytes and improve detection limits. This review explores the fundamental principles of various biosensing modalities and highlights their collaborative integration as a promising disease diagnostics approach. Translation challenges are also discussed, and future directions are proposed to bridge the gap between laboratory research and real-world applications.