Abstract
Organ-on-a-Chip (OoC) integrates advanced biomaterials, microfluidics, and cell biology to simulate organ structures and dynamic microenvironments, offering a vital platform for drug development and disease modeling. The miniature scale, structural precision, high biomimetic fidelity, and inherent dynamic complexity of OoCs pose challenges for conventional offline detection methods, including molecular-specific detection and omics analysis. Online detection technologies, particularly fluorescence probes and biosensors, address this limitation by enabling in situ, non-invasive, and real-time monitoring with high spatiotemporal resolution. As the core platform for microphysiological systems, the accuracy with which OoCs replicate human organ function and its capability for dynamic characterization are depend on breakthroughs in the performance of current probe and sensing materials. Now, comprehensive reviews specifically dedicated to fluorescence probe techniques and its application in real-time characterization of OoCs remain lacking. Herein, to address this gap, we establish an offline-online detection technologies multidimensional evaluation framework in OoCs characterization. Furthermore, we integrate the burgeoning application of image recognition technologies and artificial intelligence (AI) within the OoCs. Our aim is to provide methodological support for advancing OoCs standardization and industrial quality control, and to stimulate the development of OoCs into more reliable and effective tools for biomedical research and applications. The ongoing maturation and industrialization of OoC technology will solidify its role as a transformative tool, bridging foundational research and clinical applications with enhanced reliability and efficacy.