Cannabis cultivars were usually categorized based on their genetic profile as sativa, indica, or hybrid types. However, these three criteria do not allow sufficient differentiation between the numerous varieties of cannabis strains. Furthermore, this classification is based on morphological and bio-geographical properties of the plants and does not represent the chemical composition of different cultivars. The concentration of cannabinoids and terpenes are crucial for the pharmacological effect, not only because of the known entourage effect, and therefore needs to be considered by categorization. A total of 140 medicinal cannabis flowers available on the German market were analyzed regarding their individual terpene profile using GC-MS analysis. Statistical evaluation was performed to investigate correlations and data relations as well as for clustering. Multivariate analysis showed correlations between individual terpenes. However, there was no statistical correlation between terpene profiles and their respective genetic profile. Terpene profiles of sativa, indica, and hybrid strains are quite heterogenous and clearly showed that there is no relation between terpenes and the estimated pharmacological effect. As a result, we suggest a new classification system based on individual terpene profiles to faster a comprehensive understanding of the expected medical effect. Considering main terpenes, we established a concept of six clusters with various terpene profiles being attributed to different medicinal applications. We excluded tetrahydrocannabinol (THC) and cannabidiol (CBD) content from clustering as most of the strains were THC dominant and therefore distort the results. Our pattern of strains with similar terpene profiles might refine the existing classes of chemotypes with different THC:CBD content. The categorization of cannabis strains based on their terpene profiles allows a clearer, finer and, above all, more meaningful classification than the existing sativa/indica classification. Due to the entourage effect and the interactions between cannabinoids and terpenes, this group of substances is also given the necessary consideration when selecting the right medicine for the individual. Within the next steps, further studies are needed with the aim of mapping clinical validated effects to our chemovars. If it is possible to correlate therapy of symptoms to specific chemical profiles personalized cannabinoid therapy will be possible.

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