Extended Stability Evaluation of Selected Cathinones

Rutter, L.; Nisbet, Lorna A.; Scott, Karen S.

doi:10.3389/fchem.2020.597726

Cited by 20 publications

(6 citation statements)

References 41 publications

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“…Key examples are the new psychoactive drugs belonging to the cathinone family that contain a keto moiety adjacent to the benzene ring. Many of these drugs show significant losses over several hours, let alone days, if not stored frozen as the keto group oxidizes (Adamowicz & Malczyk, 2019; Busardo et al, 2015; Ciallella et al, 2020).…”

Section: Post‐mortem Biotransformationmentioning

confidence: 99%

Post‐mortem redistribution of drugs and other factors affecting interpretation: A review

Drummer

Gerostamoulos

2023

WIREs Forensic Science

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Changes in the post-mortem concentration of drugs, such as through redistributive processes are well known, although not well understood in terms of the mechanisms operating in particular cases and the extent it influences an interpretation of the reported concentrations. This advanced review outlines the mechanisms known to potentially alter blood and tissue concentrations and focuses on publications over the last decade that attempt to quantify the extent of changes occurring for specific drugs or drug classes. Most of the more recent studies show time-dependent changes that do not always alter concentrations in one direction, let alone to the same extent. This increases the uncertainty of interpretation, particularly for drugs with a narrow therapeutic index. Nevertheless, guidelines are provided in this review to improve interpretation of post-mortem drug concentrations in cases where a psychoactive substance(s) are a possible contribution to death.

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Section: Post‐mortem Biotransformationmentioning

confidence: 99%

Post‐mortem redistribution of drugs and other factors affecting interpretation: A review

Drummer

Gerostamoulos

2023

WIREs Forensic Science

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“…The stability of mephedrone, naphyrone, methylenedioxypyrovalerone (MDPV), and (α‐pyrrolidinopentiophenone) α‐PVP in MeOH and ACN solutions was examined when stored at 20, 4, and −20°C (Ciallella et al, 2020). Mephedrone was unstable on Day 3 when stored at 20°C and on Day 14 when stored at 4°C in MeOH.…”

Section: Stability Of Forensically Relevant Drugs In Solventsmentioning

confidence: 99%

“…Ciallella et al evaluated the stability of mephedrone, MDPV, naphyrone, and α-PVP stored at À20, 4, and 20 C (light protected) in fortified blood and urine samples (Ciallella et al, 2020). Samples were stored for a period of 30 days and analyzed in triplicate.…”

Section: Novel Drugsmentioning

confidence: 99%

Drug stability in forensic toxicology

Nisbet

DiEmma

Scott

2023

WIREs Forensic Science

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Knowledge of the stability of analytes in solvents and biological matrices is of high importance in the field of forensic toxicology. This is particularly true where quantitative analysis is undertaken; degradation of analytes will result in under-estimation of concentrations, whereas the production of analytes/ metabolites will lead to over-estimation. Although stability is included as part of method validation, this typically focuses on processed sample stability, and the impact of freeze/thaw cycles upon analytes. Although beneficial for method evaluation, this does not assist laboratory analysts with the short-and long-term storage of samples prior to this step and does not consider the impact the biological matrix may have on the degradation or production of the analyte in question. The timeframe for these studies is also relatively short (typically 72 h), which does not cover the time frame between sample receivership and analysis for many forensic cases. This review collects previously published work on long-term stability studies, grouping compounds into their associated drug classes and matrices. Research shows that the majority of compounds are more stable at lower storage temperatures, and that analysis should be completed as quickly as possible. It is advised that analyte stability be considered prior to any interpretation of concentrations in a forensic setting.

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“…Solutions were prepared as the hydrochloride salt at a base concentration of 0.1 mg/mL. The phenethylamines were prepared in chloroform, while the cathinones were prepared in methanol per recommendations from Ciallella et al 29 All solutions were stored at −20 °C when not in use.…”

Section: Experimental Sectionmentioning

confidence: 99%

Utilization of Machine Learning for the Differentiation of Positional NPS Isomers with Direct Analysis in Real Time Mass Spectrometry

Bonetti

Samanipour

Asten³

2022

Anal. Chem.

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The differentiation of positional isomers is a well established analytical challenge for forensic laboratories. As more novel psychoactive substances (NPSs) are introduced to the illicit drug market, robust yet efficient methods of isomer identification are needed. Although current literature suggests that Direct Analysis in Real Time–Time-of-Flight mass spectrometry (DART-ToF) with in-source collision induced dissociation (is-CID) can be used to differentiate positional isomers, it is currently unclear whether this capability extends to positional isomers whose only structural difference is the precise location of a single substitution on an aromatic ring. The aim of this work was to determine whether chemometric analysis of DART-ToF data could offer forensic laboratories an alternative rapid and robust method of differentiating NPS positional ring isomers. To test the feasibility of this technique, three positional isomer sets (fluoroamphetamine, fluoromethamphetamine, and methylmethcathinone) were analyzed. Using a linear rail for consistent sample introduction, the three isomers of each type were analyzed 96 times over an eight-week timespan. The classification methods investigated included a univariate approach, the Welch t test at each included ion; a multivariate approach, linear discriminant analysis; and a machine learning approach, the Random Forest classifier. For each method, multiple validation techniques were used including restricting the classifier to data that was only generated on one day. Of these classification methods, the Random Forest algorithm was ultimately the most accurate and robust, consistently achieving out-of-bag error rates below 5%. At an inconclusive rate of approximately 5%, a success rate of 100% was obtained for isomer identification when applied to a randomly selected test set. The model was further tested with data acquired as a part of a different batch. The highest classification success rate was 93.9%, and error rates under 5% were consistently achieved.

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Extended Stability Evaluation of Selected Cathinones

Cited by 20 publications

References 41 publications

Post‐mortem redistribution of drugs and other factors affecting interpretation: A review

Post‐mortem redistribution of drugs and other factors affecting interpretation: A review

Drug stability in forensic toxicology

Utilization of Machine Learning for the Differentiation of Positional NPS Isomers with Direct Analysis in Real Time Mass Spectrometry

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