A computationally supported designer benzodiazepine strategy for public toxicology laboratories

Author:

Ciallella Heather L1ORCID,Taruvinga Danai T1,Yacoub Kimberly1ORCID,Sofalvi Szabolcs1ORCID,Delor Samantha M1,Kaspar Claire K1,Mitchell-Mata Christie L1,Travaglianti Shelby12,Lavins Eric S1,Apollonio Luigino G1

Affiliation:

1. Toxicology Unit, Cuyahoga County Medical Examiner’s Office and Regional Forensic Science Laboratory , 11001 Cedar Ave., Cleveland, OH 44106, USA

2. Department of Pharmacology and Toxicology, University of Toledo , 2801 Bancroft St., Toledo, OH 43606, USA

Abstract

Abstract Public laboratories must balance innovative and existing methods to keep up with designer drug trends. This article presents a strategy for handling designer benzodiazepines (DBZDs) in casework from screening to interpretation. The cross-reactivity of 22 DBZDs and metabolites was tested against the Immunalysis™ benzodiazepine (BZD) direct enzyme-linked immunosorbent assay kit. The kit had high intra-analyte precision (coefficients of variation <15%). Inter-analyte performance varied, triggering confirmation testing at concentrations ranging from 35 to 460 μg/L. The Cuyahoga County Regional Forensic Science Laboratory implemented a 40-analyte BZD and Z-drug confirmation method in 2019. Ten additional analytes were later validated for qualitative reporting, and the limits of detection for 13 analytes were lowered by 60%. The method of standard addition was also optimized for as-needed quantitation. Equal and 1/x weighting factors correlated well with target concentrations (coefficients of determination (r2) > 0.98), but 1/x weighting provided the most consistently accurate concentrations. Six computational models were developed to predict γ-aminobutyric acid-A receptor binding affinity to assist in case interpretation (r2 > 0.70 for cross-validation and test set prediction). These models were used to predict the binding affinity of analytes in the confirmation method. Other public laboratories can use this same practical strategy to adapt to any designer drug class (e.g., BZDs, opioids, cannabinoids and stimulants).

Publisher

Oxford University Press (OUP)

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