A Tool for Automatic Correction of Endogenous Concentrations: Application to BHB Analysis by LC–MS-MS and GC-MS

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

Qualitative method validation and uncertainty evaluation via the binary output: I – Validation guidelines and theoretical foundations

Qualitative methods have an important place in forensic toxicology, filling central needs in, amongst others, screening and analyses linked to per se legislation. Nevertheless, bioanalytical method validation guidelines either 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”. Since the goal of any method validation is to demonstrate fitness for use under production conditions, guidelines should evaluate performance by relying on the discrete results, instead of the continuous measurements obtained (e.g. peak height, area ratio). We have developed a tentative validation guideline for decision point qualitative methods by modeling measurements and derived binary results behaviour, based on the literature and experimental results. This preliminary guideline was applied to an LC-MS/MS method for 40 analytes, each with a defined cut-off concentration. The standard deviation of measurements at cut-off ( ) was estimated based on 10 spiked samples. Analytes were binned according to their %RSD (8.00%, 16.5%, 25.0%). Validation parameters calculated from the analysis of 30 samples spiked at and (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. Subsequent examination found that this was attributable to an appreciable shift in the standard deviation of the area ratio between different batches of samples analyzed. Keeping this behaviour in mind when setting the validation concentrations, the developed guideline can be used to validate qualitative decision point methods, relying on binary results for performance evaluation and taking into account measurement uncertainty. An application of this method validation scheme is presented in the accompanying paper (II – Application to a multi-analyte LC-MS/MS method for oral fluid)

A threshold LC–MS/MS method for 92 analytes in oral fluid collected with the Quantisal® device

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

Qualitative method validation and uncertainty evaluation via the binary output: II - Application to a multi-analyte LC-MS/MS method for oral fluid

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 validated according to the guidelines presented in the first part of this paper (I – Validation guidelines and statistical foundations). 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 teting 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 hroughput analysis

Qualitative threshold method validation and uncertainty evaluation: A theoretical framework and application to a 40 analytes liquid chromatography–tandem mass spectrometry method

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

Qualitative threshold method validation and uncertainty evaluation: A theoretical framework and application to a 40 analytes liquid chromatography–tandem mass spectrometry method

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

Mémoire concernant les effets néfastes de l’exposition au bruit chez les travailleurs au Québec

1) personne contact parmi le groupe [email protected] 2) adresse URL : https://www.facebook.com/bruitsanteeTravail réalisé dans le cadre du cours PHA1415Résumé La limite actuelle de bruit au Québec se situe à 90 dBA pour une exposition quotidienne de 8 heures, selon un facteur de bissection de 5. Elle a été fixée en 1979 dans le règlement sur la santé et la sécurité au travail (RSST), article 223 de la Loi sur la santé et la sécurité au travail (LSST), et n’a jamais été modifiée par la suite, malgré le fait qu’il avait été prévu de la diminuer de moitié ultérieurement. Ainsi, le Québec accuse un retard par rapport aux autres provinces canadiennes, et même par rapport à plusieurs autres pays industrialisés, qui ont adopté une limite de 85 dBA pour une exposition de 8 heures, avec un facteur de bissection de 3. Une réduction de la limite québécoise actuelle vers cette dernière limite permettrait de réduire l’incidence des problèmes de santé chez les travailleurs exposés à de hauts niveaux de bruit. En effet, le bruit peut causer des problèmes de santé auditifs, tels que la surdité et les acouphènes, ainsi que des problèmes extra-auditifs, comme les problèmes cardiovasculaires, les troubles du sommeil et le stress professionnel. Par ailleurs, il pose aussi des risques pour la sécurité des travailleurs, entraînant notamment une augmentation des accidents de travail menant à une hospitalisation. D’ailleurs, les coûts grandissants reliés aux indemnités des travailleurs démontrent un réel problème au Québec. Nous recommandons entre autres au gouvernement d’amender le règlement sur la santé et la sécurité au travail (RSST) afin de se conformer à la limite de bruit des autres provinces canadiennes, en tenant compte des techniques actuelles de réduction du bruit et du rôle limité qu’ont les protecteurs auditifs dans la protection des travailleurs.