Point-of-need and portable sensing strategies for quality and safety assessment of Traditional Chinese Medicine products: A critical analytical review.

Sensor technology has emerged as a transformative tool for point-of-need and portable quality control and safety assessment of Traditional Chinese Medicine (TCM) products. Although separation and detection technologies have improved, there is still a strong need to critically evaluate the entire analytical workflow from sample preparation to data interpretation to meet regulatory and routine monitoring requirements. This review critically evaluates the complete analytical workflow, from sample pretreatment to intelligent data interpretation, necessary to bridge the gap between laboratory prototypes and real-world deployment. Additionally, it provides a systematic summary of the mechanisms and applications of common types of sensors, utilising nanomaterials and molecular recognition elements to overcome the specific challenge of complex TCM matrices. A particular focus is placed on the emerging roles of Artificial Intelligence (AI) and Machine Learning (ML) in resolving high-dimensional spectral data and enhancing pattern recognition accuracy. Furthermore, we critically analyze current bottlenecks, including matrix interference, the lack of standardized validation protocols, and the reliability of portable devices in uncontrolled environments. Future directions are highlighted towards the development of self-validating, cloud-integrated (IoT), and eco-friendly sensing systems, aiming to support the global standardization and safety assurance of TCM products.