Biosensor and Artificial Intelligence Technologies for the Discovery, Quality Control, And Authentication of Natural Bioactive Compounds: A Biomedical Engineering and Biophysics Perspective

Abstract

The discovery, quality control, and clinical translation of bioactive compounds derived from medicinal plants and other natural resources increasingly depend not on botany or pharmacology alone, but on the convergence of biomedical engineering, biophysical sensing, and computational informatics. Biosensors, analytical devices that couple a biological recognition element with a physical or electrochemical transducer, and artificial intelligence, which increasingly assists compound identification, extraction optimization, and bioactivity prediction, together constitute a rapidly advancing methodological toolkit for natural-product research. This review examines recent evidence on biosensor platforms applied to natural medicine research, including electrochemical, optical, and piezoelectric quartz crystal microbalance sensors, and on the current applications and limitations of artificial intelligence across the medicinal plant drug discovery pipeline. The reviewed literature indicates that nanomaterial-enhanced biosensors can achieve femtomolar-to-picogram sensitivity for herb authentication, active-compound screening, and quality-control contaminant detection, that quartz crystal microbalance platforms in particular offer a direct, label-free route to real-time monitoring of natural-compound binding events, and that artificial intelligence tools, while not yet delivering a fully AI-derived approved botanical drug, meaningfully accelerate compound identification, extraction optimization, and virtual screening. These findings position biomedical engineering, biophysics, and informatics as indispensable, integrative disciplines for advancing natural resources toward validated human health applications, while also highlighting substantial translational and standardization challenges that remain.