Deep Learning-Enabled MS/MS Spectrum Prediction Facilitates Automated Identification Of Novel Psychoactive Substances.

The market for illicit drugs has been reshaped by the emergence of more than 1100 new psychoactive substances (NPS) over the past decade, posing a major challenge to the forensic and toxicological laboratories tasked with detecting and identifying them. Tandem mass spectrometry (MS/MS) is the primary method used to screen for NPS within seized materials or biological samples. The most contemporary workflows necessitate labor-intensive and expensive MS/MS reference standards, which may not be available for recently emerged NPS on the illicit market. Here, we present NPS-MS, a deep learning method capable of accurately predicting the MS/MS spectra of known and hypothesized NPS from their chemical structures alone. NPS-MS is trained by transfer learning from a generic MS/MS prediction model on a large data set of MS/MS spectra. We show that this approach enables a more accurate identification of NPS from experimentally acquired MS/MS spectra than any existing method. We demonstrate the application of NPS-MS to identify a novel derivative of phencyclidine (PCP) within an unknown powder seized in Denmark without the use of any reference standards. We anticipate that NPS-MS will allow forensic laboratories to identify more rapidly both known and newly emerging NPS. NPS-MS is available as a web server at https://nps-ms.ca/, which provides MS/MS spectra prediction capabilities for given NPS compounds. Additionally, it offers MS/MS spectra identification against a vast database comprising approximately 8.7 million predicted NPS compounds from DarkNPS and 24.5 million predicted ESI-QToF-MS/MS spectra for these compounds.

Quantification of 31 illicit and medicinal drugs and metabolites in whole blood by fully automated solid-phase extraction and ultra-performance liquid chromatography-tandem mass spectrometry.

An efficient method for analyzing illegal and medicinal drugs in whole blood using fully automated sample preparation and short ultra-high-performance liquid chromatography-tandem mass spectrometry (MS/MS) run time is presented. A selection of 31 drugs, including amphetamines, cocaine, opioids, and benzodiazepines, was used. In order to increase the efficiency of routine analysis, a robotic system based on automated liquid handling and capable of handling all unit operation for sample preparation was built on a Freedom Evo 200 platform with several add-ons from Tecan and third-party vendors. Solid-phase extraction was performed using Strata X-C plates. Extraction time for 96 samples was less than 3 h. Chromatography was performed using an ACQUITY UPLC system (Waters Corporation, Milford, USA). Analytes were separated on a 100 mm × 2.1 mm, 1.7 µm Acquity UPLC CSH C(18) column using a 6.5 min 0.1 % ammonia (25 %) in water/0.1 % ammonia (25 %) in methanol gradient and quantified by MS/MS (Waters Quattro Premier XE) in multiple-reaction monitoring mode. Full validation, including linearity, precision and trueness, matrix effect, ion suppression/enhancement of co-eluting analytes, recovery, and specificity, was performed. The method was employed successfully in the laboratory and used for routine analysis of forensic material. In combination with tetrahydrocannabinol analysis, the method covered 96 % of cases involving driving under the influence of drugs. The manual labor involved in preparing blood samples, solvents, etc., was reduced to a half an hour per batch. The automated sample preparation setup also minimized human exposure to hazardous materials, provided highly improved ergonomics, and eliminated manual pipetting.

Screening for illicit and medicinal drugs in whole blood using fully automated SPE and ultra-high-performance liquid chromatography with TOF-MS with data-independent acquisition.

A broad forensic screening method for 256 analytes in whole blood based on a fully automated SPE robotic extraction and ultra-high-performance liquid chromatography (UHPLC) with TOF-MS with data-independent acquisition has been developed. The limit of identification was evaluated for all 256 compounds and 95 of these compounds were validated with regard to matrix effects, extraction recovery, and process efficiency. The limit of identification ranged from 0.001 to 0.1 mg/kg, and the process efficiency exceeded 50% for 73 of the 95 analytes. As an example of application, 1335 forensic traffic cases were analyzed with the presented screening method. Of these, 992 cases (74%) were positive for one or more traffic-relevant drugs above the Danish legal limits. Commonly abused drugs such as amphetamine, cocaine, and frequent types of benzodiazepines were the major findings. Nineteen less frequently encountered drugs were detected e.g. buprenorphine, butylone, cathine, fentanyl, lysergic acid diethylamide, m-chlorophenylpiperazine, 3,4-methylenedioxypyrovalerone, mephedrone, 4-methylamphetamine, p-fluoroamphetamine, and p-methoxy-N-methylamphetamine. In conclusion, using UHPLC-TOF-MS screening with data-independent acquisition resulted in the detection of common drugs of abuse as well as new designer drugs and more rarely occurring drugs. Thus, TOF-MS screening of blood samples constitutes a practical way for screening traffic cases, with the exception of δ-9-tetrahydrocannabinol, which should be handled in a separate method.

Comparison of Comprehensive Screening Results in Postmortem Blood and Brain Tissue by UHPLC-QTOF-MS.

Alternative specimens collected during autopsies can be valuable in postmortem toxicology in cases where peripheral blood is not available. The applicability of brain tissue as an alternative matrix for drug screening by ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry was investigated in this study. Results of the 50 most frequently detected drugs and metabolites of toxicological interest in blood and brain tissue samples from 1,719 autopsy cases were compared. Examination of the results in paired blood and brain tissue samples revealed that the two matrices were in general comparable, as the majority of the 50 analytes were observed in a high number of the examined cases in both blood and brain tissue. This demonstrates the potential of brain tissue as an alternative matrix for drug screening in postmortem toxicology or as a secondary matrix for confirmation.

Overview of systematic toxicological analysis strategies and their coverage of substances in forensic toxicology.

Systematic toxicological analysis (STA) is the process of using an adequate analytical methodology to detect and identify as many potentially toxicologically relevant compounds as possible in biological samples. STA is an important part of everyday routine work within forensic toxicology, and several methods for STA have frequently been published and reviewed independently. However, the many drugs and other substances involved, as well as the constant emergence of new ones, may pose a major challenge in STA, which often demands a strategy involving multiple analytical methods in parallel. Such strategies have been published and evaluated less frequently despite their relevance in forensic toxicology. This mini-review briefly summarizes commonly applied methods for STA in forensic toxicology, including gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-MS (LC-MS) methods, and highlights some of their potential pitfalls. Second, it provides an overview of previously reported strategies to conduct STA, including a presentation of the STA strategy applied in the authors' laboratory. This involves broad drug screening by LC-high-resolution MS, supported by targeted screening and quantification using LC-tandem MS, headspace (HS)-GC-MS, HS-GC-flame ionization detector and other complementary methods. The STA strategy aims to cover as many potentially relevant drugs as possible and seeks to reduce potential pitfalls arising in forensic casework. The review underlines that not every substance can be identified in all circumstances even with a comprehensive STA strategy.

Metabolomics-driven determination of targets for salicylic acid and ibuprofen in positive electrospray ionization using LC-HRMS.

Due to the large number of basic therapeutic and illicit drugs, systematic toxicological analysis has widely been performed with liquid chromatography coupled to mass spectrometry using positive electrospray ionization. However, there exist a smaller number of drugs, typically acidic drugs, which require the use of negative electrospray ionization either via a separate analysis or polarity switching. Here, targets relating to salicylic acid and ibuprofen in positive electrospray ionization were determined through a metabolomics-driven retrospective investigation of forensic casework. Samples were previously screened using liquid chromatography coupled with high-resolution mass spectrometry with quantification of target analytes performed using liquid chromatography with tandem mass spectrometry. Of the 1,717 whole-blood samples submitted between 2014 and 2019, 48 were positive for salicylic acid (1.1-1,400 mg/kg) and 78 for ibuprofen (1-46 mg/kg). Based on the retrospective analysis, 19 and 90 targets were identified for salicylic acid and ibuprofen, respectively. For targets of salicylic acid, the protonated adduct of salicyluric acid ([M + H]+ , m/z 196.0605) was present in 89.6% (n = 32) of the salicylic acid positive cases, while the [M + HCOOH + CH3 CN + Ca - H]+ adduct (m/z 264.0179) of salicylic acid was present in all positive samples with concentrations above 66 mg/kg salicylic acid. Similarly, the [M + 2Na - H]+ adduct (m/z 251.1018) of ibuprofen was present in 98.7% (n = 77) of positive cases and was present in all samples with concentrations above 3 mg/kg ibuprofen.

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

Illicit drug profiling performed by forensic laboratories assists law enforcement agencies through providing information about chemical and/or physical characteristics of seized specimens. In this article, a model was developed for the comparison of seized cocaine based on retrospective analysis of data generated from ultrahigh performance liquid chromatography with time-of-flight mass spectrometry (UHPLC-TOF-MS) comprehensive drug screening. A nontargeted approach to discover target compounds was employed, which generated 53 potential markers using data from cocaine positive samples. Twelve marker compounds were selected for the development of the final profiling model. The selection included a mixture of commonly used cocaine profiling targets and other cocaine-related compounds. Combinations of pretreatments and comparison metrics were assessed using receiver operating characteristic curves to determine the combination with the best discrimination between linked and unlinked populations. Using data from 382 linked and 34,519 unlinked distances, a classification model was developed using a combination of the standardization and normalization transformations with Canberra distance, resulting in a linked cut-off with a 0.5% false positive rate. The present study demonstrates the applicability of retrospectively developing a cocaine profiling model using data generated from UHPLC-TOF-MS nontargeted drug screening without pre-existing information about cocaine impurities. The developed workflow was not specific to cocaine and thus could potentially be applied to any seized drug in which there are both sufficient data and impurities present.

Identification of the synthetic cannabinoid-type new psychoactive substance, CH-PIACA, in seized material.

Synthetic cannabinoids (SCs) remain the largest class of new psychoactive substances (NPS), and while the number of NPS that are reported to the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) for the first time each year declines, the number of newly reported SCs still exceeds other NPS classes. This decline can be seen as a result of legislative changes by different jurisdictions which have sometimes transitioned to a more generalized approach when controlling substances by defining common structural scaffolds rather than explicit structures. While the consequences of such legislative changes have been expected over the years, the introduction of so-called "class-wide" bans puts further pressure on clandestine laboratories to synthesize compounds which are out of the scope of the legislation, and thus, these compounds are initially harder to detect and/or identify in the absence of analytical data. Recently, a SC with an indole-3-acetamide core-linker scaffold, AD-18 (i.e., ADB-FUBIATA or ADB-FUBIACA), was reported for the first time in China in 2021. Here, an additional cannabinoid with the indole-3-acetamide scaffold, N-cyclohexyl-2-(1-pentyl-1H-indol-3-yl)acetamide (CH-PIACA), is reported which was identified for the first time in a seized material in Denmark. Structural characterization was performed using gas chromatography-mass spectrometry (GC-MS), liquid chromatography-high-resolution mass spectrometry (LC-HRMS), and nuclear magnetic resonance (NMR) spectroscopy.

A New Strategy for Efficient Retrospective Data Analyses for Designer Benzodiazepines in Large LC-HRMS Datasets.

The expanding and dynamic market of new psychoactive substances (NPSs) poses challenges for laboratories worldwide. The retrospective data analysis (RDA) of previously analyzed samples for new targets can be used to investigate analytes missed in the first data analysis. However, RDA has historically been unsuitable for routine evaluation because reprocessing and reevaluating large numbers of forensic samples are highly work- and time-consuming. In this project, we developed an efficient and scalable retrospective data analysis workflow that can easily be tailored and optimized for groups of NPSs. The objectives of the study were to establish a retrospective data analysis workflow for benzodiazepines in whole blood samples and apply it on previously analyzed driving-under-the-influence-of-drugs (DUID) cases. The RDA workflow was based on a training set of hits in ultrahigh-performance liquid chromatography-quadrupole time-of-flight-mass spectrometry (UHPLC-QTOF-MS) data files, corresponding to common benzodiazepines that also had been analyzed with a complementary UHPLC-tandem mass spectrometry (MS/MS) method. Quantitative results in the training set were used as the true condition to evaluate whether a hit in the UHPLC-QTOF-MS data file was true or false positive. The training set was used to evaluate and set filters. The RDA was used to extract information from 47 DBZDs in 13,514 UHPLC-QTOF-MS data files from DUID cases analyzed from 2014 to 2020, with filters on the retention time window, count level, and mass error. Sixteen designer and uncommon benzodiazepines (DBZDs) were detected, where 47 identifications had been confirmed by using complementary methods when the case was open (confirmed positive finding), and 43 targets were not reported when the case was open (tentative positive finding). The most common tentative and confirmed findings were etizolam (n = 26), phenazepam (n = 13), lorazepam (n = 9), and flualprazolam (n = 8). This method efficiently found DBZDs in previously acquired UHPLC-QTOF-MS data files, with only nine false-positive hits. When the standard of an emerging DBZD becomes available, all previously acquired DUID data files can be screened in less than 1 min. Being able to perform a fast and accurate retrospective data analysis across previously acquired data files is a major technological advancement in monitoring NPS abuse.

Comprehensive UHPLC-HR-MSE screening workflow optimized for use in routine laboratory medicine: Four workflows in one analytical method.

A comprehensive HR-MS screening can be used to identify thousands of drugs from a single analysis, which makes it a valuable tool for broad-scope component-resolved toxicological analysis. However, it is common practice in clinical toxicology to perform restricted data analysis to avoid examining and/or reporting data not requested for examination. In this study, a HR-MS screening workflow was developed to allow a comprehensive toxicological evaluation, but also restricted and levelled data analysis to fit in a clinical setting. Following precipitation and reconstitution, samples were injected on an UHPLC-HR-MS and data were analyzed with the data processing software UNIFI. Analytical validation of 38 selected drugs of abuse (DoA), included determination of matrix effect, recovery, process efficiency, and limit of identification (LOI). The method was tested on 49 authentic samples and matrix-matched ranges of calibrators for 95 drugs. The LOI ranged from 0.3 to 1426.7 ng mL-1 for most analytes which was within expected concentration range for authentic samples with THC-COOH (>1722.0 ng mL-1) and morphine (1426.7 ng mL-1) as notable exceptions. Four individual screening workflows were developed: 1) a targeted workflow to serve as orthogonal identification of the 38 selected DOAs from another in-house method, 2) a general toxicology workflow, 3) an extended toxicology workflow including new psychoactive substances (NPS), and 4) a workflow for NPS based on the online HighResNPS library. Our study presents a comprehensive LC-HR-MS toxicology screening method optimized for laboratory medicine. The workflow allows for levelled data reviewing when requested without compromising the ability to perform full toxicological analyses.

Identification of New Psychoactive Substances in Seized material Using UHPLC-QTOF-MS and An Online Mass Spectral Database.

The unpredictable pharmacological and toxicological effects associated with the recreational use of new psychoactive substances (NPS) represent a threat to the public health. Analysts are constantly facing a challenge to identify these designer drugs. In this article, five seized samples were submitted for analysis using ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS). To tentatively identify the NPS in the samples, the potential usage of an online mass spectral database (HighResNPS.com) was explored by searching the exact mass of the precursor ion and evaluating the fragmentation profile. This approach successfully identified a suspected candidate compound present in three of the five samples. However, conclusive identification of the remaining two was not possible, due to indistinguishable fragmentation profiles of positional isomers. Therefore, complementary analytical methodologies are of paramount importance. In light of the above, HighResNPS.com is a useful tool in presumptively identifying an NPS without a reference standard.

Analysis of seized peptide and protein-based doping agents using four complimentary methods: Liquid chromatography coupled with time of flight mass spectrometry, liquid chromatography-ultraviolet, Bradford, and immunoassays.

Analysis and identification of seized doping-related products are important tasks for customs or forensic laboratories in order to prevent potentially dangerous and illegal compounds to go into circulation. At the Section of Forensic Chemistry in Copenhagen, we have a workflow consisting of four complimentary validated methods to identify common doping-related substances: liquid chromatography-ultraviolet (LC-UV), LC coupled with time of flight mass spectrometry (LC-TOF-MS), the colorimetric Bradford assay, and an immunoassay. The Bradford assay screens for peptide or proteins in the sample, and the immunoassay confirmed human chorionic gonadotropin (hCG). LC-UV was carried out with a C4 protein column for identification of peptides and proteins from a standard reference library, based on retention times and ratios between peak areas at 220, 254, and 280 nm. LC-TOF-MS was performed using a C18 column, and identification was based on comparison of the retention time and the accurate mass with those of reference standards. In 2019, we received 36 samples for peptide/protein analysis, all of which were tested using the LC-UV, LC-TOF-MS, and colorimetric method, and samples suspected of containing hCG were confirmed with an immunoassay. We found a total of 15 samples containing an illegal doping substance, 12 samples containing substances not prohibited by the Danish Doping List, and nine samples containing no peptides or proteins. In conclusion, the four complimentary methods constitute a suitable approach for identifying common peptide/protein doping substances in the day-to-day routine of a forensic laboratory, with limited sample preparation and interpretation of data.

Development of a single retention time prediction model integrating multiple liquid chromatography systems: Application to new psychoactive substances.

Database-driven suspect screening has proven to be a useful tool to detect new psychoactive substances (NPS) outside the scope of targeted screening; however, the lack of retention times specific to a liquid chromatography (LC) system can result in a large number of false positives. A singular stream-lined, quantitative structure-retention relationship (QSRR)-based retention time prediction model integrating multiple LC systems with different elution conditions is presented using retention time data (n = 1281) from the online crowd-sourced database, HighResNPS. Modelling was performed using an artificial neural network (ANN), specifically a multi-layer perceptron (MLP), using four molecular descriptors and one-hot encoding of categorical labels. Evaluation of test set predictions (n = 193) yielded coefficient of determination (R2) and mean absolute error (MAE) values of 0.942 and 0.583 min, respectively. The model successfully differentiated between LC systems, predicting 54%, 81% and 97% of the test set within ±0.5, ±1 and ±2 min, respectively. Additionally, retention times for an analyte not previously observed by the model were predicted within ±1 min for each LC system. The developed model can be used to predict retention times for all analytes on HighResNPS for each participating laboratory's LC system to further support suspect screening.

How to perform spectrum-based LC-HR-MS screening for more than 1,000 NPS with HighResNPS consensus fragment ions.

INTRODUCTION: The ever-changing market of new psychoactive substances (NPS) poses challenges for laboratories worldwide. Analytical toxicologists are constantly working to keep high-resolution mass spectrometry (HR-MS) screening libraries updated for NPS. This study sought to use the online crowd-sourced HighResNPS database for spectrum comparison screening, thereby broadening its utility to all HR-MS instruments. METHOD: HighResNPS allows formation of a set of consensus fragment ions for a NPS and prioritises among multiple entries of collision-induced fragment ions. A subset of 42 NPS samples was analysed in data-independent acquisition (DIA) and data-dependent acquisition (DDA) modes on two different instruments. HighResNPS-computed spectra were generated with either Absolute (all fragment ions set to 100%) or Fractional (50% intensity reduction of former fragment ion) intensity. The acquired NPS data were analysed using the consensus library with computed ion intensities and evaluated with vendor-neutral screening software. RESULTS: Overall, of the 42 samples, 100% were identified, with 88% identified as the top candidate. Three samples had the correct candidate proposed as the second highest ranking NPS. In all three of those samples, the top proposed candidate was a positional isomer or closely related compound. Absolute intensity assignment provided identical scoring between the top two proposed compounds in two samples with DIA. DDA had a slightly higher identification rate in the spectra comparison screening with fractional intensity assignment, but no major differences were observed. CONCLUSION: The fractional intensity assignment was slightly more advantageous than the absolute assignment. It was selective between proposed candidates, showed a high identification rate and had an overall higher fragmentation scoring. The candidates proposed by the HighResNPS library spectra comparison simplify the determination of NPS for researchers and toxicologists. The database provides free monthly updates of consensus spectra, thereby enabling laboratories to stay at the forefront of NPS screening by LC-HR-MS with spectra screening software.

In vitro and in vivo metabolism and detection of 3-HO-PCP, a synthetic phencyclidine, in human samples and pooled human hepatocytes using high resolution mass spectrometry.

The new psychoactive substance (NPS) 3-HO-PCP, a phencyclidine (PCP) analog, was detected in a law enforcement seizure and in forensic samples in Denmark. Compared with PCP, 3-HO-PCP is known to be a more potent dissociative NPS, but no toxicokinetic investigations of 3-HO-PCP are yet available. Therefore, 3-HO-PCP was quantified in in vivo samples, and the following were investigated: plasma protein binding, in vitro and in vivo metabolites, and metabolic targets. All samples were separated by liquid chromatography and analyzed by mass spectrometry. The unbound fraction in plasma was determined as 0.72 ± 0.09. After in vitro incubation with pooled human hepatocytes, four metabolites were identified: a piperidine-hydroxyl-and piperidine ring opened N-dealkyl-COOH metabolite, and O-glucuronidated- and O-sulfate-conjugated metabolites. In vivo, depending on the sample and sample preparation, fewer metabolites were detected, as the O-sulfate-conjugated metabolite was not detected. The N-dealkylated-COOH metabolite was the main metabolite in the deconjugated urine sample. in vivo analytical targets in blood and brain samples were 3-HO-PCP and the O-glucuronidated metabolite, with 3-HO-PCP having the highest relative signal intensity. The drug levels of 3-HO-PCP quantified in blood were 0.013 and 0.095 mg/kg in a living and a deceased subject, respectively. The 3-HO-PCP concentrations in deconjugated urine in a sample from a living subject and in post-mortem brain were 7.8 and 0.16 mg/kg, respectively. The post mortem results showed a 1.5-fold higher concentration of 3-HO-PCP in the brain tissue than in the post mortem blood sample.

Identification of phenobarbital and other barbiturates in forensic drug screening using positive electrospray ionization liquid chromatography-high resolution mass spectrometry.

Comprehensive drug-screening performed by liquid chromatography-high resolution mass spectrometry (LC-HRMS) enables identification of hundreds to thousands of drug compounds in a single analysis. Forensic drug screening is generally performed with positive electrospray ionization (ESI+ ), targeting basic drugs; however, a few toxicologically important drugs such as barbiturates, may require analysis by negative ESI. In this work, screening targets for barbiturates were determined using our LC-HRMS screening with ESI+ . For several years, our forensic whole blood samples have been analyzed using the LC-HRMS-ESI+ screening in parallel with a multi-target LC-MS/MS-ESI- method. From 2014 to 2018, 23 samples were positive for phenobarbital (0.5-81 mg/kg). Retrospective data analysis of 4816 blood samples (15 positive) revealed several potential screening targets for phenobarbital. The targets were tentatively identified by exact mass and isotopic pattern as uncommon adducts of phenobarbital and as a decomposition product of phenobarbital N-glucoside (C17 H24 N2 O7 ). Analysis of a test set containing eight positive (0.5-65 mg/kg phenobarbital) and 31 negative samples supported the use of the observed target m/z 323.0614 at 5.14 minutes, corresponding to the [M + HCOONa+Na]+ adduct of phenobarbital. The [M + HCOONa+Na]+ adduct was confirmed as a screening target for common barbiturates, by analysis of barbiturate reference standards in ESI+ /ESI- . The [M + HCOONa+Na]+ adduct allowed retrospective analysis with 91% sensitivity (n = 23) and 100% specificity (n = 4855) for phenobarbital in our existing LC-HRMS-ESI+ screening. The two negative results were the two whole-blood samples with the lowest phenobarbital concentration (<1.8 mg/kg). Thus, a specialized screening is not necessary and use of this adduct likely enables screening for other barbiturates.

Glycine-modified growth hormone secretagogues identified in seized doping material.

A number of unknown pharmaceutical preparations seized by Danish customs authorities were submitted for liquid chromatography-high resolution mass spectrometry (LC-HRMS) analysis. Comparison with reference standards unequivocally identified the content of the powders as analogs of the growth hormone secretagogues GHRP-2 (Pralmorelin), GHRP-6, Ipamorelin, and modified growth hormone releasing factor (modified GRF 1-29), which can be used as performance-enhancing substances in sports. In all cases, the detected modification involved the addition of an extra glycine amino acid at the N-terminus, and analytical methods targeting growth hormone secretagogues should hence be updated accordingly.

Retrospective analysis for valproate screening targets with liquid chromatography-high resolution mass spectrometry with positive electrospray ionization: An omics-based approach.

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 C7 H14 O3 and C8 H14 O3 . 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.

HighResNPS.com: An Online Crowd-Sourced HR-MS Database for Suspect and Non-targeted Screening of New Psychoactive Substances.

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.

Prediction of collision cross section and retention time for broad scope screening in gradient reversed-phase liquid chromatography-ion mobility-high resolution accurate mass spectrometry.

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.