The clinical translation of plant-derived anti-inflammatory agents is hindered by the disconnect between high-throughput in vitro assays and low-throughput, costly mammalian models. This review posits the zebrafish ( Danio rerio ) not merely as an alternative model, but as a central integrating platform that bridge this translational chasm through multimodal technological convergence. We first synthesize how zebrafish inflammation models—established via chemical, physical, or infectious stimuli—enable rapid, whole-organism efficacy and safety profiling of phytochemicals. We then dissect the conserved molecuar circuitry (NF-κB, MAPK, Nrf2) through which standardized extracts and isolated compounds exert their anti-inflammatory effects, visualized dynamically in transgenic lines. Crucially, we move beyond descriptive cataloguing to critically evaluate the integration of zebrafish with microfluidics-enabled high-content screening, AI-driven phenotypic analytics, CRISPR/Cas9 gene editing, network pharmacology, and humanized xenograft models. We argue that this convergent multimodal strategy transforms zebrafish from a correlative screening tool into a predictive, mechanism-resolving, and patient-relevant avatar system. We conclude that zebrafish-centric platforms furnish a robust, mechanism-driven, and scalable framework to accelerate the discovery, mechanistic elucidation, and rational preclinical development of safer, multi-target phytotherapeutics, thereby catalyzing the evolution of plant-based medicine from empirical discovery to precision anti-inflammatory therapy guided by a systems-level, mechanism-driven paradigm. This framework positions zebrafish-centered platforms as a cornerstone of next-generation anti-inflammatory precision medicine.
Tan et al. (2026) studied this question.