Extraction Yields of Psilocybin and Psilocin: A Short Review of Current Methods and Their Implications - Galdino, Taynah P.; Oliveira, Lucas C.; Luz, Mateus A.; Jesus, Raquel A.; Lima, Eunice P. N.; Torres, Maria C. M.; Sivieri, Katia [UNESP]; Afonso, Victor I.; Delgado, João M. P. Q.; Lima, Antonio G. B.; Silva, Suédina M. L.; Fook, Marcus V. L. (MDPI, 2025)
The growing body of evidence supporting the therapeutic efficacy of psychoactive substances, like psilocybin, has driven significant interest in recent decades due to their low toxicity and potential applications in treating various mental health disorders. However, producing pharmaceutical-grade psilocybin remains challenging, with three primary approaches: chemical synthesis, biosynthesis, and extraction from Psilocybe mushroom fruiting bodies. This systematic review evaluates the extraction and quantification methods for psilocybin and psilocin, aiming to contribute to the development of standardized protocols that ensure compound quality and purity. A total of 25 relevant studies were selected from an initial pool of 9152 publications indexed in platforms such as Scopus, ScienceDirect, Web of Science, and PubMed. The findings indicate that both the extraction method and the choice of mushroom species significantly influence compound yields. Ultrasonic bath extraction was identified as the most efficient technique, particularly for species including Psilocybe cyanescens and Psilocybe cubensis. High-performance liquid chromatography (HPLC) was the most-used method for identifying and quantifying these compounds. Furthermore, polar solvents were critical for effective solubilization, with parameters such as temperature, solvent-to-material ratio, and extraction time playing key roles in optimizing yields. This review serves as a key scientific reference for advancing research, enhancing analytical precision, and ensuring reproducibility through the standardization of extraction and quantification protocols.
Keywords: extraction methods; psychoactive compounds; yield optimization