MSACL 2018 US Abstract

Topic: Cannabinoids

The Utility of LC-QTOF/MS in Proactive Synthetic Cannabinoid Testing in the Psychoactives Surveillance Consortium and Analysis Network (P SCAN)

Roy Gerona (Presenter)
University of California, San Francisco

Bio: Roy Gerona is a biochemist and clinical chemist by training and is an Assistant Professor at the University of California, San Francisco. He directs and manages the Clinical Toxicology and Environmental Biomonitoring Laboratory at UCSF. His laboratory works on three major research areas, all utilizing LC-MS- new psychoactive substance surveillance, environmental biomonitoring, and therapeutic drug monitoring in HIV patients. In his NPS surveillance work, he has partnered with collaborators from the US Drug Enforcement Administration (DEA), Centers for Disease Control and Prevention (CDC) and Department of Homeland Security (DHS) to respond to mass casualty events involving synthetic cannabinoids. Most recently he has established a more comprehensive NPS surveillance network by partnering with collaborators from Stanford University and ten medical centers across the United States. In his spare time, Roy is an avid grass (not related to "weed"!) volleyball player.

Authorship: Roy Gerona (1), Axel Adams (1), Samuel Douglas Banister (2)
(1) University of California, San Francisco (2) Stanford University

Short Abstract

The ability to identify previously unreported new psychoactive substance (NPS) is a challenging task even for well-equipped laboratories. We developed a proactive approach to NPS testing that couple metabolite prediction and proactive synthesis of "prophetic" synthetic cannabinoid reference standards with targeted and suspect screening using LC-QTOF/MS in a recently established NPS surveillance network, the Psychoactives Surveillance Consortium And Analysis Network (P SCAN). We will present initial data to illustrate how this approach is used to identify, confirm and quantify analytes in biological samples in cases involving synthetic cannabinoids in the first 100 P SCAN cases.

Long Abstract

Introduction

Surveillance studies on New Psychoactive Substances (NPS) have become the most rapid source of information on new designer drugs released into illicit and “grey” drug markets. The ability of laboratories involved in this work to identify new compounds heavily relies on suspect screening facilitated through high-resolution mass spectrometry. We recently established the Psychoactives Surveillance Consortium and Analysis Network (P SCAN), a surveillance network comprised of ten medical centers across the United States, Stanford University, and the Clinical Toxicology and Environmental Biomonitoring (CTEB) Lab at UCSF. Unlike other surveillance studies, the consortium prospectively enrolls cases with potential NPS etiology, collects comprehensive clinical and toxicological data, and pair those with quantitative analysis of biological samples obtained from the cases. The goal is to create a massive database of cases that can be queried for defining toxidrome and effective regimen for specific NPS and class of NPS, an aim that has never been addressed by other surveillance studies.This will be very useful to emergency physicians who have been wanting of accurate data for identifiable toxidrome that can be reliably used in NPS diagnosis.

Methods

We developed targeted and suspect screening workflows using liquid chromatography-quadrupole time-of-flight mass spectrometry (Agilent LC 1260- QTOF/MS 6550). We have a comprehensive targeted drug panel consisting of more than 750 drugs of which ~470 are NPS as well as suspect databases of four NPS classes with hundreds of entries- stimulants, depressants, hallucinogens, and cannabinoids- generated from compiling NPS that are reported in the scientific literature, NPS surveillance websites and drug blogs. These databases are constantly revised with most up-to-date data on NPS. We are also able to perform suspect screening of predicted NPS metabolites. For synthetic cannabinoids, we are able to synthesize our own reference standard for those that are not available from manufacturers and proactively synthesize a library of “prophetic” cannabinoids- that is, cannabinoids that we predict can be synthesized by clandestine laboratories based on structural modifications that appear in cannabinoids that are released in the grey market- to proactively use and perform rapid and timely confirmatory runs for tentative matches we generate in our surveillance work.

Results

We will present data involving synthetic cannabinoids obtained from our first 100 cases in P SCAN. We will demonstrate how we apply our targeted, suspect screening, metabolite prediction, and “prophetic” synthetic cannabinoid library generation workflows to generate quantitative LC-QTOF/MS data for P SCAN. More than 25% of the first 100 cases involved synthetic cannabinoids. Trends and challenges on sample and data analysis for both targeted and suspect screening workflows, detectable targets in the analysis, and metabolite prediction and confirmation will be presented as well as the developing trends in clinical data and some ethnographic data that correlate with synthetic cannabinoid data.

Conclusions & Discussion

The use of proactive reference standard synthesis of “prophetic” cannabinoids and metabolite prediction greatly enhances the ability of LC-QTOF/MS targeted and suspect screening workflows to facilitate identification and confirmation of synthetic cannabinoids in our surveillance study, P SCAN. Although this may not necessarily be applicable to all clinical and forensic labs, big reference laboratories and surveillance networks may benefit from the workflows we have developed. Ultimately, this will lessen false negative rates generated by these laboratories that hinder resolution of a significant number of cases.


References & Acknowledgements:


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