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Abstract INTRODUCTION: Novel psychoactive substances (NPS) have created a challenge for toxicology laboratories. New NPS are constantly disappearing as fast as they emerge, making it difficult to stay on top of which compounds are necessary to add to laboratory testing scopes. The development and optimization of liquid chromatography (LC) separations is time consuming and costly, often requiring several steps including literature research, column selection, method scouting, method development, and method optimization. To alleviate the burden of sacrificing instrument-uptime, labor and materials, an instrument-free software modeling tool was developed to include a comprehensive drugs of abuse (DoA) library. This online tool allows users to obtain optimized separations while maintaining critical pair resolution by adjusting parameters such as column dimension, mobile phase, gradient programs, and more for almost 300 compounds including the 38 newly added NPS drugs.
OBJECTIVES: The primary objective of this study is to use a chromatographic modeling tool to develop effective LC-MS/MS methods for various NPS compounds including synthetic opioids, designer benzodiazepines, synthetic cathinones, synthetic cannabinoids, and toxic adulterants.
METHODS: The NPS library utilized the same design space as the existing DoA library. Retention times were collected using method conditions consisting of a fast (5 minute) and slow (15 minute) gradient, 30°C/60°C temperature points, and ACN/MeOH mobile phases on Raptor Biphenyl and Raptor C18 columns in a 50 x 2.1, 2.7 µm dimension. The 38 NPS compounds were divided into three small groups to account for the separation of isobars and to generate the optimal points per peak for instrument analysis. A set of 8 compounds, referred to as “meld compounds”, were then added to each group. These meld compounds spanned the chromatographic space and were used to verify instrument performance from injection to injection. Data was collected and input into the platform. Results of retention times between experimental and modeled data were compared. To verify the ability of the modeler to develop methods for NPS, three methods were developed and optimized using the chromatogram modeler for the following NPS subclasses: 1) synthetic opioids and toxic adulterants 2) designer benzodiazepines 3) stimulants and synthetic cannabinoids. All methods utilized a Raptor Biphenyl 100 x 2.1, 2.7 µm column with a MPA of water and MPB of methanol, both acidified with 0.1% formic acid. The flow rate was 0.6 mL/min and the column temperature was 40°C. The developed methods were transferred to an LC-MS/MS system and the experimental results were compared with the modeler.
RESULTS: The online chromatogram modeling tool successfully developed methods for NPS compounds. Developing the methods using the virtual chromatography tool was completed in under ten minutes per method. The acceptance criteria for retention time agreement between experimental and modeled values was set at +/- 15 seconds, chosen to represent a typical MRM window. All analytes in all three methods fell within this window, as well as maintaining elution order and resolution. For example, Isotonitazene had a predicted retention time of 2.86 minuntes and an experimental retention time 2.75 minutes, for a difference of 6.6 seconds. Eutylone had a predicted retention time of 4.42 minutes and an experimental retention time of 4.18 minutes, for a difference of 14.4 seconds. Based on the acceptance criteria as defined, each NPS method was successfully transferred from the virtual model to an LC-MS/MS instrument.
CONCLUSION: As NPS continue to proliferate the illicit drug market, the burden of adding these compounds to laboratory testing scopes becomes the obligation of LC method developers. Utilizing tools such as a virtual chromatography modeler can help method developers deal with the challenges these emerging compounds present.
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= Discovery stage. (16.60%, 2024)
= Translation stage. (37.02%, 2024)
= Clinically available. (46.38%, 2024)
