Cannabis sativa L is one of the most used drugs in the world. Information about the plant’s age and storage can help forensic scientists to identify and to track samples. The ratio between the cannabinoids tetrahydrocannabinol (THC) and cannabinol (CBN) has been related to the degradation of cannabis with time. Thus, this study aimed to test Multivariate Image Analysis (MIA) to evaluate cannabis extracts concerning its colors. Initially, 52 samples of Cannabis sativa L. extracts were analyzed by Gas Chromatography coupled to Flame Ionization Detector (GC/FID) to quantify THC and CBN. Afterwards, the extract samples were photographed and analyzed by two different multivariate analysis tools: ChemoStat®, a free chemometrics software, and PhotoMetrix PRO®, an app for mobile devices. Using exploratory analysis of principal component analysis (PCA) and hierarchical cluster analysis (HCA). It was observed that the more intense the color for an extract, the higher concentration of THC and CBN it has, while the lighter color extracts correspond to samples with no THC. The results suggest to propose a simple method for previous clustering of samples that may precede chromatographic analyzes, assist in chemical profile studies or simply aggregate samples of similar profiles for analyzed together.

Gas chromatography (GC) is a gold standard technique used in forensic laboratories, including for the characterization of counterfeit medicines. When coupled simultaneously to flame ionization (FID) and mass detector (MS) allow the identification and quantification of medicines and drugs employing a single method, besides permitting the application of chemometric tools for forensic intelligence purposes. Here is presented a pilot project that developed and applied a qualitative method for the analysis of counterfeit medicines comprised by amphetamine-type stimulants and antidepressants, through a simple extraction procedure followed by GC-FID/MS analysis, with application of exploratory tools by Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA). The main purpose was to identify similarities between the all compounds detected in the irregular medicines allowing the traceability of illicit producers with the creation of a common data base. Through the analyses it was verified that different producers of counterfeit medicines labeled as Sibutramine, added a mixture of Caffeine and Benzocaine in their formulation, respecting the same ratio of 2.2:1. HCA was able to confirm these results, showing the presence of both falsifications in the same cluster, representing the best tool to identify similar characteristics among the samples – when compared to PCA. Other interesting finding was the use of Fluoxetine as a falsification of counterfeit medicines labeled as Sibutramine and Diethylpropion. Another seized sample labeled as “Nobesio Forte”, marketed as a mix of stimulants, showed only Caffeine and Lidocaine in its formulation. The pilot project applied primarily to 45 samples of counterfeit medicines containing amphetamine-type stimulants and antidepressants, showed the capability of perform the chemical profiling of counterfeit medicines in the solid form - powder, capsules and tablets. Further analysis can be performed for different types of medicines in solid form using the developed method, allowing the construction of a single database to perform the chemical profiling of counterfeit medicines, enabling the traceability of illicit producers.