<![CDATA[Sphagneticola trilobata (L.) Pruski (Asteraceae) has attracted increasing scientific interest due to its rich phytochemical diversity and reported biological activities. This review systematically evaluates published literature retrieved from major scientific databases (including PubMed, Scopus, and Web of Science) covering studies, using defined inclusion and exclusion criteria focused on phytochemical identification and bioactivity assessment. Available evidence indicates that S. trilobata contains multiple classes of secondary metabolites, including terpenoids, flavonoids, alkaloids, steroids, and saponins. Among these, terpenoids emerge as the most frequently reported and quantitatively dominant constituents, particularly in aerial parts, and are consistently associated with antimicrobial, anti-inflammatory, and cytotoxic activities. Flavonoids and alkaloids, though less abundant, contribute complementary antioxidant and pharmacological effects. The review synthesizes current findings to prioritize phytochemical groups based on abundance and bioactivity rather than simple classification. While several compounds demonstrate promising bioactivities, most evidence remains limited to in vitro and preclinical studies. Consequently, the potential of S. trilobata–derived metabolites for drug discovery should be interpreted cautiously, highlighting the need for further mechanistic, toxicological, and clinical investigations. Future research should emphasize standardized extraction protocols, advanced analytical techniques such as LC-MS/MS and NMR, and robust bioassay-guided fractionation to accurately link specific compounds with observed biological effects. In addition, structure–activity relationship studies and molecular docking approaches may help elucidate mechanisms of action and identify lead candidates. Importantly, well-designed in vivo experiments and controlled clinical trials are essential to validate safety, efficacy, and pharmacokinetic profiles before therapeutic application can be considered viable across diverse populations and disease models in translational research.]]>
