Cocaine profiling method retrospectively developed with nontargeted discovery of markers using liquid chromatography with time-of-flight mass spectrometry data

Characterization of 17 unknown ketamine manufacturing by-product impurities by UHPLC-QTOF-MS

This study initially reported the selection and characterization of 17 unknown impurities attributed to the manufacture process of ketamine. A total of 150 seized ketamine samples were investigated through ultra-high-performance liquid chromatography-quadrupole-time of flight (UHPLC-Q-TOF). Seventeen characteristic impurities were selected in accordance with four criteria: The compound was detected in over 10% of all 150 seized ketamine samples, the compound had at least one nitrogen, the unsaturation of the compound was more than 5, and the compound was stable in the dilution solvent solution for 48 h. The accurate masses of the protonated molecules and product ions of the target impurities were obtained based on the full scan mode and the product ion mode of Q-TOF, respectively. Lastly, the possible structures of the above impurities were tentatively elucidated in accordance with the synthetic route of ketamine, protonated molecules, and MS2 product ions. All 17 impurities had the same skeleton of deschloroketamine (DCK), but were substituted with additional chlorine, hydroxyl, methyl, cyclohexane, and o-chlorophenyl cyclopentyl ketone substituents. Under the electrospray ionization (ESI), the above impurities showed similar characteristic fragment ions through the dissociation of the CH3NH2, C2H6NH, H2O, CO, C2H4O, C4H6, and C2H2 moieties. The above impurities have been routinely used for the profiling analysis of seized ketamine samples in the National Narcotics Laboratory of China and employed to establish the tactical intelligence for law enforcement agencies.

Cannabis profiling of seized samples: An intra-location variability study using gas chromatography-mass spectrometry profiles and multivariate data analysis

Yearly, cannabis belongs to the most seized drugs worldwide. During judicial investigations, illicit cannabis profiling can be performed to compare seized herbal material. However, comparison is challenging because of the natural heterogeneity of the psychoactive crop. Gas chromatography-mass spectrometry (GC-MS) profiles, consisting of eight cannabinoids, were used to study the intra-location (within) and inter-location (between) variabilities. Decision thresholds were derived from the 95% and 99% confidence limits, applying Pearson correlation coefficients for the intra-location samples. The false negatives and false positives (FPs) determined the discriminative power of different pretreatments applied to obtain the lowest FP error rate possible. Initially, a 97 samples data set was used and with log transformation as pretreatment, a decrease in FPs from 38% and 45% FPs to 17% and 22%, for both confidence limits, respectively, was seen relative to internal standard normalization that was used as reference. An additional intra-plantation variability study with 130 samples verified whether the initial model contained sufficient within-location information, but this was not the case. Hence, a combined data matrix was constructed with all seized samples. Log transformation provided the best FP results for both limits, that is, an improvement from 58% and 64% to 21% and 26%, respectively, was seen. The representativeness of these 'linked' thresholds was demonstrated using both cross-validation and an external set, for which similar FP results as for the calibration set were obtained. By applying data pretreatment, a significant improvement was observed to distinguish seized samples. However, the FP rate is still not at an acceptable level to defend in court.