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The coefficient of correlation (r) and the coefficient of determination (R2 or r2) have long been used in analytical chemistry, bioanalysis and forensic toxicology as figures demonstrating linearity of the calibration data in method validation. We clarify here what these two figures are and why they should not be used for this purpose in the context of model fitting for prediction. R2 evaluates whether the data are better explained by the regression model used than by no model at all (i.e., a flat line of slope = 0 and intercept $\bar y$), and to what degree. Hopefully, in the context of calibration curves, the fact that a linear regression better explains the data than no model at all should not be a point of contention. Upon closer examination, a series of restrictions appear in the interpretation of these coefficients. They cannot indicate whether the dataset at hand is linear or not, because they assume that the regression model used is an adequate model for the data. For the same reason, they cannot disprove the existence of another functional relationship in the data. By definition, they are influenced by the variability of the data. The slope of the calibration curve will also change their value. Finally, when heteroscedastic data are analyzed, the coefficients will be influenced by calibration levels spacing within the dynamic range, unless a weighted version of the equations is used. With these considerations in mind, we suggest to stop using r and R2 as figures of merit to demonstrate linearity of calibration curves in method validations. Of course, this does not preclude their use in other contexts. Alternative paths for evaluation of linearity and calibration model validity are summarily presented.

Qualitative methods hold an important place in drug testing, filling central needs in screening and analyses, among others, linked to per se legislation. Nevertheless, the bioanalytical method validation guidelines do not discuss this type of method or describe method validation procedures ill-adapted to qualitative methods. The output of qualitative methods are typically categorical, binary results, such as presence/absence or above cut-off/below cut-off. As the goal of any method validation is to demonstrate fitness for use under production conditions, qualitative validation guidelines should evaluate performance based on discrete, binary results instead of the continuous measurements obtained from the instrument (e.g. area). A tentative validation guideline for threshold qualitative methods was developed by in silico modelling of measurements and derived binary results. This preliminary guideline was applied to a liquid chromatography-tandem mass spectrometry method for 40 analytes, each with a defined threshold concentration. Validation parameters calculated from the analysis of 30 samples spiked above and below the threshold concentration (false negative rate, false positive rate, selectivity rate, sensitivity rate and reliability rate) showed a surprisingly high failure rate. Overall, 13 out of the 40 analytes were not considered validated. A subsequent examination found that this was attributable to an appreciable shift in the standard deviation of the area ratio on a day-to-day basis, a previously undescribed and unaccounted-for behaviour in the qualitative threshold method validation literature. Consequently, the developed guideline was modified and used to validate a qualitative threshold method, based on the binary results for performance evaluation and incorporating measurement uncertainty.

Abstract: The use of High Resolution Mass Spectrometry (HRMS) has increased over the past decade in clinical and forensic toxicology, especially for comprehensive screening approaches. Despite this, few guidelines of this field have specifically addressed HRMS issues concerning compound identification, validation, measurement uncertainty and quality assurance. To fully implement this technique, certainly in an era in which the quality demands for laboratories are ever increasing due to various norms (e.g. the International Organization for Standardization’s ISO 17025), these specific issues need to be addressed. This manuscript reviews 26 HRMS-based methods for qualitative systematic toxicological analysis (STA) published between 2011 and 2021. Key analytical data such as samples matrices, analytical platforms, numbers of analytes and employed mass spectral reference databases/libraries as well as the studied validation parameters are summarized and discussed. The article further includes a critical review of targeted and untargeted data acquisition approaches, available HRMS reference databases and libraries as well as current guidelines for HRMS data interpretation with a particular focus on identification criteria. Moreover, it provides an overview on current recommendations for the validation and determination measurement uncertainty of qualitative methods. Finally, the article aims to put forward suggestions for method development, compound identification, validation experiments to be performed, and adequate determination of measurement uncertainty for this type of wide-range qualitative HRMS-based methods.

The validation of analytical methods is of crucial importance in several fields of application. A new protocol for the validation of chromatographic methods has been proposed. The overall protocol is described in a parallel paper, where the case of a multi-targeted gas chromatography – mass spectrometry (GC–MS) method for the determination of androgens in human urine is in-depth discussed. The purpose of this paper is to report the details about the GC–MS separation and detection of the target analytes, and to provide the mathematical formulas needed to perform the validation of the principal parameters. Briefly, the validation protocol foresees the repetition of three calibration curves in three different days, providing a total amount of nine replicates. Such a structured design allows to use the same experiments to•perform a rigorous calibration study, by the evaluation of heteroscedasticity, comparison of several weights and linear/quadratic calibration curves.•determine several parameters which are traditionally computed from dedicated experiments, namely intra- and inter-day accuracy and precision, limit of detection, specificity, selectivity, ion abundance repeatability, and carry over.•Finally, few further experiments are necessary to evaluate the retention time repeatability, matrix effect and extraction recovery., Graphical abstract Image, graphical abstract

In the last two decades, a large increase in opioid overdose death rates has been recorded in North America. This phenomenon, related to the misuse of prescription opioids, has been dubbed an "opioids crisis". Recent years have seen the entrance of novel synthetic opioids (NSO) on the market, compounding the fatal intoxications issue. This brings several challenges for forensic toxicology laboratories: an increased number of cases, a large number of novel structurally similar compounds to include in screening analytical methods, the low concentration of drugs in biological fluids, and the challenging interpretation in the absence of sufficient literature. Three cases of fatal intoxication highlighting those challenges are presented, complete with post-mortem concentrations in cardiac blood, femoral blood and urine. Toxicological screening and quantitative analyses were performed on the biological specimens. In the first and second cases, furanylfentanyl, U-47700 and 4-anilino-N-phenethylpiperidine (4-ANPP) were detected at similar concentrations in cardiac blood. In the third case, a total of seventeen different NSO were detected. All intoxications showed a combination of NSO and other drugs. These three cases appear to be the harbinger of an increased NSO prevalence in the province of Québec, Canada.

Several New Psychoactive Substances (NPS) enter the illicit drug market each year. This constant evolution of compounds to screen is challenging to law enforcement and drug chemists, and even more so to forensic toxicologists, who need to detect such compounds which might be at low concentrations in complex biological matrices. While some technological solutions are better suited than others to address such a challenge (e.g., high resolution mass spectrometry), laboratories with limited instrumental and financial resources are faced with a complex task: systematically screening for a rapidly evolving NPS panel using an accredited method run on standard equipment (e.g., liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS)). This work presents a solution to this challenge: a complete workflow from the detection of a regional NPS threat to its implementation in a method accredited under the ISO 17025:2017 norm. Initial LC-MS/MS method included 55 NPS and metabolites (31 Novel Synthetic Opioids (NSO), 22 NSO metabolites and 2 designer benzodiazepines). Following their identification as relevant territorial threats, flualprazolam, then isotonitazene, were added to the contingent. By relying on development aiming for maximal integration to the current analysis workflow, systematic NPS screening using this method was easily implemented. Between March 2019 and March 2020, the 5 079 forensic cases analyzed in the province of Québec (Canada) revealed a NPS positivity rate of 3.4%. While 94% involved designer benzodiazepines, 5% involved NSO. This process, combining high efficiency, simple detection technology, ISO accreditation and rapid response to new threats resulted in a four-fold increase in NPS detection.

Objectives To examine alleged drug-impaired driving in the province of Quebec (Canada), including drug use profile amongst suspected impaired drivers, prior to recreational cannabis legalization and major modifications to the legislation regarding driving under the influence of drugs (DUID). Methods The Laboratoire de sciences judiciaires et de medecine legale (LSJML) performs toxicological analyses on all biological samples collected during a Drug Evaluation and Classification Program (DECP) evaluation by a Drug Recognition Expert (DRE). A targeted analysis of 137 drugs and metabolites by liquid chromatography – tandem mass spectrometry (LC–MS/MS) is systematically carried out, enhanced by gas chromatography – mass spectrometry (GC–MS) general unknown screening if deemed necessary. Data from all DECP cases analyzed from January 2014 to December 2018 was compiled and summarized. Results In the 5-year period studied, a total of 2 982 DECP cases underwent toxicological analysis. Age of the intercepted drivers varied between 14–82 years old (average 33 years old), with 79 % men and 21 % women. At least one substance with impairing potential was detected in 98 % of cases. In 89 % of cases (n = 2 640), at least one substance detected matched a category of drug suspected of causing impairment. At the other end of the spectrum, there were 270 cases (9%) where the findings did not match any of the categorie(s) suspected by the DRE, 66 negative cases (2%) and 6 incomplete evaluations. Substances most commonly detected belonged to the central nervous system (CNS) stimulants (72 %), CNS depressants (61 %) and cannabis (48 %) categories. Most prevalent substances were methamphetamine (54%), cannabis (11-nor-9-carboxy-tetrahydrocannabinol or THC−COOH, 48 %), cocaine (29 %) and gamma-hydroxybutyrate (GHB, 24 %). Polydrug consumption was common, with two or more substances with impairing potential detected in 79 % of cases. There were 113 occurrences of new psychoactive substances (NPS), the most prevalent being rolicyclidine (PCPy, 47 %), methylenedioxypyrovalerone (MDPV, 17 %), methylbenzylpiperazine (MBZP, 13 %) and flubromazolam (10 %). Drug prevalence patterns varied geographically, as well as with age and gender. Indeed, methamphetamine and GHB were more popular amongst women, whereas cannabis and cocaine were more prevalent amongst men. Cannabis and CNS stimulants were more common amongst younger drivers (14–34 years old); CNS depressants, dissociative anesthetics and non-psychoactive drugs prevalence increased with age. Conclusions An up-to-date database of DUID cases is a powerful tool in identifying trends and threats, focusing resources and orienting research and development activities. Such a database, combined with the data presented in the current study, will be key in evaluating the impact of new regulations, i.e., recreational cannabis legalization and modifications to the DUID legislation.

A study of impaired driving rates in the province of Québec is currently planned following the legalization of recreational cannabis in Canada. Oral fluid (OF) samples are to be collected with a Quantisal® device and sent to the laboratory for analysis. In order to prepare for this project, a qualitative decision point analysis method monitoring for the presence of 97 drugs and metabolites in OF was developed and validated. This high throughput method uses incubation with a precipitation solvent (acetone:acetonitrile 30:70 v:v) to boost drug recovery from the collecting device and improve stability of benzodiazepines (e.g., α-hydroxyalprazolam, clonazepam, 7-aminoclonazepam, flunitrazepam, 7-aminoflunitrazepam, N-desmethylflunitrazepam, nitrazepam). The Quantisal® device has polyglycol in its stabilizing buffer, but timed use of the mass spectrometer waste valve proved sufficient to avoid the glycol interferences for nearly all analytes. Interferences from OF matrices and 140 potentially interfering compounds, carryover, ion ratios, stability, recovery, reproducibility, robustness, false positive rate, false negative rate, selectivity, sensitivity and reliability rates were tested in the validation process. Five of the targeted analytes (olanzapine, oxazepam, 7-aminoclonazepam, flunitrazepam and nitrazepam) did not meet the set validation criteria but will be monitored for identification purposes (no comparison to a cut-off level). Blind internal proficiency testing was performed, where six OF samples were tested and analytes were classified as "negative", "likely positive" or "positive" with success. The final validated OF qualitative decision point method covers 92 analytes, and the presence of 5 additional analytes is screened in this high throughput analysis.

Several substances relevant for forensic toxicology purposes have an endogenous presence in biological matrices: beta-hydroxybutyric acid (BHB), gamma-hydroxybutyric acid (GHB), steroids and human insulin, to name only a few. The presence of significant amounts of these endogenous substances in the biological matrix used to prepare calibration standards and quality control samples (QCs) can compromise validation steps and quantitative analyses. Several approaches to overcome this problem have been suggested, including using an analog matrix or analyte, relying entirely on standard addition analyses for these analytes, or simply ignoring the endogenous contribution provided that it is small enough. Although these approaches side-step the issue of endogenous analyte presence in spiked matrix-matched samples, they create serious problems with regards to the accuracy of the analyses or production capacity. We present here a solution that addresses head-on the problem of endogenous concentrations in matrices used for calibration standards and quality control purposes. The endogenous analyte concentration is estimated via a standard-addition type process. This estimated concentration, plus the spiked concentration are then used as the de facto analyte concentration present in the sample. These de facto concentrations are then used in data analysis software (MultiQuant, Mass Hunter, etc.) as the sample’s concentration. This yields an accurate quantification of the analyte, free from interference of the endogenous contribution. This de facto correction has been applied in a production setting on two BHB quantification methods (GC-MS and LC–MS-MS), allowing the rectification of BHB biases of up to 30 μg/mL. The additional error introduced by this correction procedure is minimal, although the exact amount will be highly method-dependent. The endogenous concentration correction process has been automated with an R script. The final procedure is therefore highly efficient, only adding four mouse clicks to the data analysis operations.

Determination of carboxyhemoglobin (HbCO) is routinely performed in suspected cases of carbon monoxide intoxication and unexplained deaths. However, some authors have suggested that measured HbCO may be falsely elevated in infants (0–12 months) due to the presence of fetal hemoglobin (HbF). The purpose of this study was to evaluate the impact of fetal hemoglobin on the spectro-photometric determination of carboxyhemoglobin. The interference of HbF in the determination of HbCO in infants aged from 0 to 12 months was evaluated using 16 ante-mortem and 19 post-mortem blood samples. The %HbCO was quantified spectrophotometrically by calculating the 560 nm/530 nm absorbance ratio, using a dual-beam spectrophotometer. The average measured HbCO in infants of 3 months of age or under was 17%, which is abnormally elevated. No significant difference in HbCO measurement was found between ante-mortem and post-mortem samples. These results highlight the fact that care must be taken in interpretation of carboxy...

The stimulant designer drug 3,4-methylenedioxypyrovalerone (MDPV) was first synthesized by Boehringer Ingelheim in 1969 and introduced on the black market in 2006. Only a small number of fatal intoxication cases have been reported in the literature, all with significant blood MDPV concentrations. In this report, we describe one fatality attributed to an idiosyncratic reaction to MDPV. The victim displayed agitation, violent behavior and delirium followed by cardiac arrest. Hyperthermia was observed at the hospital. The MDPV cardiac and femoral blood concentrations were 6 ng/mL. The presence of excited delirium syndrome and MDPV, a drug with a pharmacology similar to cocaine, leads to the conclusion that the victim suffered a fatal adverse reaction to MDPV. This is the first published case of idiosyncratic reaction to MDPV.

Calculating the confidence interval is a common procedure in data analysis and is readily obtained from normally distributed populations with the familiar [Formula: see text] formula. However, when working with non-normally distributed data, determining the confidence interval is not as obvious. For this type of data, there are fewer references in the literature, and they are much less accessible. We describe, in simple language, the percentile and bias-corrected and accelerated variations of the bootstrap method to calculate confidence intervals. This method can be applied to a wide variety of parameters (mean, median, slope of a calibration curve, etc.) and is appropriate for normal and non-normal data sets. As a worked example, the confidence interval around the median concentration of cocaine in femoral blood is calculated using bootstrap techniques. The median of the non-toxic concentrations was 46.7 ng/mL with a 95% confidence interval of 23.9-85.8 ng/mL in the non-normally distributed set of 45 postmortem cases. This method should be used to lead to more statistically sound and accurate confidence intervals for non-normally distributed populations, such as reference values of therapeutic and toxic drug concentration, as well as situations of truncated concentration values near the limit of quantification or cutoff of a method.

In 2014, Quebec's forensic science laboratory (Laboratoire de sciences judiciaires et de medicine legale) is celebrating its 100th anniversary. Since its foundation by Dr. Derome in 1914, scientific techniques in the various areas of forensic science have greatly evolved. Not only was the Laboratory the first forensic science institution in North America, it has been a pioneer for several analytical methods. The early days of the Laboratory as well as the specific evolution of the departments and divisions of biology, chemistry, arson and explosion, questioned documents, forensic pathology, odontology and anthropology, toxicology and administration will be reviewed here.

ResumeEn 2014, le Laboratoire de sciences judiciaires et de medicine legale du Quebec celebre son 100ieme anniversaire. Depuis sa fondation par Dr Wilfrid Derome en 1914, les techniques scientifiques ont grandement evolue dans les differents domaines des sciences judiciaires. Non seulement le laboratoire fut la premiere institution de sciences judiciaires en Amerique du Nord, mais plusieurs methodes analytiques y furent aussi developpees. Les debuts du Laboratoire ainsi que l'evolution specifique des differentes directions et divisions de la biologie, chimie, incendies et explosions, documents, pathologie judiciaire, odontologie et anthropologie, toxicologie et administration seront relates ici.

Herein is described the full scope of a desulfinylative cross-coupling of aryl sulfinates with aryl bromides. Optimized conditions were established and a bidentate phosphine ligand was found to be the key in obtaining good cross-coupling yields. Preliminary efforts to elucidate the reaction mechanism suggest that a Pd(0)-catalyzed mechanism is operative.

Calibration model selection is required for all quantitative methods in toxicology and more broadly in bioanalysis. This typically involves selecting the equation order (quadratic or linear) and weighting factor correctly modelizing the data. A mis-selection of the calibration model will generate lower quality control (QC) accuracy, with an error up to 154%. Unfortunately, simple tools to perform this selection and tests to validate the resulting model are lacking. We present a stepwise, analyst-independent scheme for selection and validation of calibration models. The success rate of this scheme is on average 40% higher than a traditional "fit and check the QCs accuracy" method of selecting the calibration model. Moreover, the process was completely automated through a script (available in Supplemental Data 3) running in RStudio (free, open-source software). The need for weighting was assessed through an F-test using the variances of the upper limit of quantification and lower limit of quantification replicate measurements. When weighting was required, the choice between 1/x and 1/x2 was determined by calculating which option generated the smallest spread of weighted normalized variances. Finally, model order was selected through a partial F-test. The chosen calibration model was validated through Cramer-von Mises or Kolmogorov-Smirnov normality testing of the standardized residuals. Performance of the different tests was assessed using 50 simulated data sets per possible calibration model (e.g., linear-no weight, quadratic-no weight, linear-1/x, etc.). This first of two papers describes the tests, procedures and outcomes of the developed procedure using real LC-MS-MS results for the quantification of cocaine and naltrexone.

In the first part of this paper (I — Description and application), an automated, stepwise and analyst independent process for the selection and validation of calibration models was put forward and applied to two model analytes. This second part presents the mathematical reasoning and experimental work underlying the selection of the different components of this procedure. Different replicate analysis designs (intra/inter-day and intra/interextraction) were tested and their impact on test results was evaluated. For most methods, the use of intra-day/intra-extraction measurement replicates is recommended due to its decreased variability. This process should be repeated three times during the validation process in order to assess the time stability of the underlying model. Strategies for identification of heteroscedasticity and their potential weaknesses were examined and a unilateral F-test using the lower limit of quantification and upper limit of quantification replicates was chosen. Three different options for model selection were examined and tested: ANOVA lack-of-fit (LOF), partial F-test and significance of the second-order term. Examination of mathematical assumptions for each test and LC-MS/MS experimental results lead to selection of the partial F-test as being the most suitable. The advantages and drawbacks of ANOVA-LOF, examination of the standardized residuals graph and residuals normality testing (Kolmogorov-Smirnov or Cramer-Von Mises) for validation of the calibration model were examined with the last option proving the best in light of its robustness and accuracy. Choosing the correct calibration model improves QC accuracy, and simulations have shown that this automated scheme has a much better performance than a more traditional method of fitting with increasingly complex models until QC accuracies pass below a threshold.

Optimized conditions are developed to provide the synthesis of biphenyls by Pd(0)-catalyzed coupling.

Cyanide is a powerful chemical asphyxiant found in some forensic cases following voluntary (suicide) or involuntary ingestion (fire, accidental exposure). A quantification method for cyanide that is specifically suited to post-mortem forensic purposes was developed. Determination was performed by headspace gas chromatography coupled to mass spectrometry using a GS-GASPRO column on an HP-6890 gas chromatograph with an HP-5973N mass detector. The biological sample was treated with an internal standard, frozen, glacial acetic acid was added and the sample was then incubated at 60°C for 15 min. The headspace was sampled with a disposable syringe, and analyzed to quantify hydrogen cyanide. Isotopically labeled cyanide ((13)C(15)N) was used as the internal standard to minimize matrix effect and sampling error. The method produced an extended linear dynamic range (0.07-50 μg/mL), and a method detection limit of 0.02 μg/mL. Identical calibration curves were obtained when blood, gastric contents and aqueous solutions were used as the calibration standard matrix. This method was also successful in quantitating cyanide in gastric contents, one of the most variable biological fluids. The method has been validated and is being used for current forensic cases such as fire victims and suicides.