Screening for synthetic cannabinoids in human urine samples by LC-QToF-MS using software assisted metabolite identification for method updating

Objectives New synthetic cannabinoids (SC) frequently appear on the markets challenging toxicologists. Perceived as a legal alternative to cannabis a growing number of SCs is available. Consequently, analytical methods have to be adapted frequently to include newly emerging compounds. Since most SC are metabolized extensively metabolite identification prior to analyzing urine samples is inevitable. The presented study aimed at the development and implementation of a workflow allowing for the identification of the major in vitro phase I metabolites of new compounds by using dedicated software to mine analytical data of pooled human liver microsome (pHLM) incubations. The identified metabolites and their respective MSMS fragment information are utilized to update analytical methods for the reliable identification of SC uptake in human urine samples. Methods The performed pHLM assay was according to an in-house protocol. The MS was operated in positive ESI with data-dependent MSMS fragmentation. MassMetaSite software (Molecular Discovery) was used to analyze HPLC-MSMS datasets of the incubations sampled at time points zero and one hour. Precursor and fragment information of the identified metabolites as well as their retention times were collected and added to a database used for LC-QToF-MS screening of urine samples for SC uptake. To allow for retrospective data evaluation authentic urine samples were analyzed in data independent broad-band-CID mode (bbCID). Results The highly potent and prevalent synthetic cannabinoid MDMB-CHMICA was chosen as a model compound. Analysis of the pHLM incubations of MDMB-CHMICA with MassMetaSite revealed 10 metabolites with at least two fragment masses each. Although in-depth manual data evaluation lead to the identification of 15 phase I metabolites, all main in vitro phase I metabolites were detected with the software. Authentic forensic case samples were screened after enzymatic cleavage of glucuronides and processed with the updated TASQ method. Despite varying relative abundances of the detected metabolites, the in vitro and in vivo data showed good agreement with respect to the chosen MDMB-CHMICA metabolites. Conclusion Using MassMetaSite software and the described workflow proved to be a suitable procedure to identify metabolites and subsequently update analytical method to account for the rapid fluctuation of compounds among the group of new psychoactive substances (NPS). The here described approach can be helpful for updating screening methods with metabolite information. This is necessary whenever dealing with analytes that are extensively metabolized such as SCs. With other NPS the identification of metabolites along with the parent compound can serve as a plausibility check and may help in estimating the time of the last drug uptake. The use of dedicated software to help with metabolite identification is less time consuming thus providing a useful alternative for the rapid method update in routine forensic toxicology.