Exact mass, retention time (RT), and collision cross section (CCS) are used as identification parameters in liquid chromatography coupled to ion mobility high resolution accurate mass spectrometry (LC-IM-HRMS). Targeted screening analyses are now more flexible and can be expanded for suspect and non-targeted screening. These allow for tentative identification of new compounds, and in-silico predicted reference values are used for improving confidence and filtering false-positive identifications. In this work, predictions of both RT and CCS values are performed with machine learning using artificial neural networks (ANNs). Prediction was based on molecular descriptors, 827 RTs, and 357 CCS values from pharmaceuticals, drugs of abuse, and their metabolites. ANN models for the prediction of RT or CCS separately were examined, and the potential to predict both from a single model was investigated for the first time. The optimized combined RT-CCS model was a four-layered multi-layer perceptron ANN, and the 95th prediction error percentiles were within 2 min RT error and 5% relative CCS error for the external validation set (n = 36) and the full RT-CCS dataset (n = 357). 88.6% (n = 733) of predicted RTs were within 2 min error for the full dataset. Overall, when using 2 min RT error and 5% relative CCS error, 91.9% (n = 328) of compounds were retained, while 99.4% (n = 355) were retained when using at least one of these thresholds. This combined prediction approach can therefore be useful for rapid suspect/non-targeted screening involving HRMS, and will support current workflows.

High-resolution mass spectrometry (HRMS) is widely used for the drug screening of biological samples in clinical and forensic laboratories. With the continuous addition of new psychoactive substances (NPS), keeping such methods updated is challenging. HRMS allows for combined targeted and non-targeted screening. First, peaks are identified by software algorithms, and identifications are based on reference standard data. Attempts are made to identify the remaining unknown peaks with in silico and literature data. However, several thousand peaks remain where most are unidentifiable or uninteresting in drug screening. The aims of the study were to apply a combined targeted and non-targeted screening approach to authentic driving-under-the-influence-of-drugs (DUID) samples (n = 44) and further validate the approach using whole-blood samples spiked with 11 low-dose synthetic benzodiazepine analogues (SBAs). Analytical data were acquired using ultra-high-performance liquid chromatography coupled with a time-of-flight mass spectrometer (UHPLC-TOF-MS) with data-independent acquisition (DIA). We present a combined targeted and non-targeted screening, where peak deconvolution and filtering reduced the number of peaks to inspect by three orders of magnitude, down to four peaks per DUID sample. The screening allowed for tentative identification of metabolites and drugs not included in the initial screening; 3 drugs and 14 metabolites were tentatively identified in the authentic DUID samples. Running targeted-screening true-positive identifications through the filters retained 73% of identifications. In the non-targeted screening, nine of the spiked SBAs were identified in the concentration range of 0.005-0.1 mg/kg, of which three were tentatively identified at concentrations below those reported in the literature. Copyright © 2016 John Wiley & Sons, Ltd.

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Synthetic cannabinoids (SCs) represented 45% of new psychoactive substances seizures in Europe (data from 2016). The consumption of SCs is an issue of concern due to their still unknown toxicity and effects on human health, the great variety of compounds synthetized, and the continuous modifications being made to their chemical structure to avoid regulatory issues. These compounds are extensively metabolized in the organism and often cannot be detected as the intact molecule in human urine. The monitoring of SCs in forensic samples must be performed by the analysis of their metabolites. In this work, a workflow for the comprehensive study of SC consumption is proposed and applied to 5F‐APP‐PICA (also known as PX 1 or SRF‐30) and AMB‐FUBINACA (also known as FUB‐AMB or MMB‐FUBINACA), based not only on the elucidation of their metabolites but also including functional data using the NanoLuc approach, previously published. Both cannabinoids were completely metabolized by human hepatocytes (12 and 8 metabolites were elucidated by high resolution mass spectrometry for 5F‐APP‐PICA and AMB‐FUBINACA, respectively) and therefore suitable consumption markers are proposed. The bioassays revealed that 5F‐APP‐PICA presented lower activity than AMB‐FUBINACA at CB1 and CB2 receptors, based on the half maximal effective concentration (EC50) and the maximum response (Emax). These results are in agreement with the different intoxication cases found in the literature for AMB‐FUBINACA.

The number of new psychoactive substances (NPS) is constantly increasing. However, although the number might be large, most NPS have a low prevalence of use, so keeping screening libraries updated with the relevant analytical targets becomes a challenge. One way to ensure sufficient screening coverage is to use shared high resolution-mass spectrometry (HR-MS) databases, such as HighResNPS.com: a free, online, spreadsheet-format, crowd-sourced HR-MS database for NPS screening. The aims of this study were (i) to present the database to the scientific community and (ii) to verify that the HighResNPS database can be utilized in suspect screening workflows for LC–HR-MS instruments and software from four different instrument vendors. A sample was spiked with 10 NPS, and participating laboratories then analyzed the sample with their respective HR-MS vendor platforms and the HighResNPS database. The HighResNPS data were obtained via a spreadsheet converted to fit the import specifications of the different vendor platforms. Suspect screening was performed using LC–HR-MS vendor platforms from Thermo Fisher, Waters, Bruker and Agilent. All 10 NPS were identified in at least three workflows used for the four different vendor platforms. Multiple users have submitted data to HighResNPS for the same NPS, which resulted in multiple true-positive identifications for these NPS. Suspect screening with LC–HR-MS can be based on diagnostic fragment ions reported by users of different vendor platforms and can support NPS identification in biological samples and/or seizure analyses when no reference standard is available in-house. The present work clearly demonstrates that HighResNPS data is compatible with instruments and screening software from at least four different vendor platforms. The database can thus serve as a useful add-on in LC–HR-MS screening workflows.

Flubromazolam is a triazole benzodiazepine with high potency and long-lasting central nervous system depressant effects; however, limited data about its pharmacokinetics are available. Here, we report in vitro studies of the human flubromazolam metabolism analyzed by liquid chromatography high-resolution mass spectrometry (LC-HRMS). In vitro investigations were carried out in pooled human liver microsomes (pHLM) and recombinant cytochrome P450 (CYP)-enzymes. To confirm those metabolites detected in vitro, authentic samples obtained from two forensic cases were also analyzed by LC-HRMS. Additionally, determination of the unbound fraction of flubromazolam in pHLM and in plasma was performed by equilibrium dialysis with subsequent prediction of its hepatic clearance (CL ) using well-stirred and parallel-tube models. Additional findings obtained by routine screening methods of these forensic cases are also reported. Studies using incubations with nicotinamide adenine dinucleotide phosphate-fortified pHLM with or without uridine 5'-diphosphoglucuronic acid and incubations with CYP-enzymes identified the main metabolic pathway of flubromazolam as hydroxylation on the α- and/or 4-position mediated by CYP3A4 and CYP3A5, with subsequent glucuronidation of the hydroxylated metabolites as well as of the parent drug. Further, α-hydroxy-flubromazolam and its corresponding glucuronide were detected in vivo together with the N-glucuronide of flubromazolam. The predicted CL of flubromazolam using the well-stirred and parallel-tube models were 0.42 and 0.43 mL/min/kg, respectively. Based on the data presented here, flubromazolam is primarily metabolized by CYP3A4/5 with a high protein-binding and a predicted low clearance. Analysis of authentic samples suggested that analytical targets for flubromazolam should be the compound itself and α-hydroxy-flubromazolam. Copyright © 2016 John Wiley & Sons, Ltd.

Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS)is an important analytical tool in the systematic toxicological analysis performed in forensic toxicology. However, some important compounds, such as the antiepileptic drug valproate (valproic acid; VPA), cannot be directly detected with positive electrospray ionization (ESI + ) due to poor ionization. Here we demonstrate an omics-based retrospective analysis for the identification of indirect screening targets for VPA in whole blood with LC-ESI + -HRMS. Analysis was performed utilizing data acquired across four years from LC-ESI + -HRMS, with VPA results from a quantitative LC-MS/MS method. The combined data with VPA results were split into an exploration set (n = 68; 28% positive) and a test set (n = 37; 32% positive). Eight indirect targets for VPA were identified in the exploration set. The evaluation of these targets was confirmed with retrospective target analysis of the test set. Using a combination of two out of the eight indirect targets, we attained a sensitivity of 92% (n = 12; VPA concentration range: 4.4-29.7 mg/kg) and 100% specificity (n = 25) for VPA with LC-ESI + -HRMS. VPA screening targets were identified with retrospective data analysis and could be appended to the existing screening procedure. A sensitive and specific screening with LC-ESI + -HRMS was achieved with targets corresponding to the sodium adducts of C 7 H 14 O 3 and C 8 H 14 O 3 . Three chromatographic resolved isomer peaks were observed for the latter, and the consistently most intense peak was tentatively identified as 3-hydroxy-4-en-VPA. KEYWORDS biomarker, forensic toxicology screening, indirect screening, retrospective analysis, untargeted high-resolution mass spectrometry screening

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