From microfluidics to nanodelivery: artificial intelligence reshapes neuropharmacology research strategies

Neurological diseases are characterized by complex etiology, heterogeneity, and significant differences in therapeutic responses, which severely constrain the efficiency of new drug development and the success rate of clinical translation. In recent years, micro- and nanotechnology (micro/nanotechnology) technologies have made breakthroughs in vitro disease modeling, drug delivery, and high-throughput screening, while artificial intelligence (AI) has shown strong advantages in big data analysis, pattern recognition, and predictive modeling, and the deep integration of the two has provided a new technological paradigm for neuropharmacology research. In this review, we systematically review the key applications of micro- and nanotechnology in neuropharmacology, including microfluidic brain chips, nanodelivery systems, and multiscale biosensing platforms, and focus on the central role of AI in drug screening, efficacy assessment, and personalized therapeutic decision-making.