为公共毒理学实验室提供计算支持的苯并二氮杂卓设计策略。

IF 2.3 3区 医学 Q3 CHEMISTRY, ANALYTICAL
Heather L Ciallella, Danai T Taruvinga, Kimberly Yacoub, Szabolcs Sofalvi, Samantha M Delor, Claire K Kaspar, Christie L Mitchell-Mata, Shelby Travaglianti, Eric S Lavins, Luigino G Apollonio
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引用次数: 0

摘要

公共实验室必须在创新方法和现有方法之间取得平衡,以跟上设计药物的发展趋势。本文介绍了一种从筛选到解释的个案工作中处理特制苯并二氮杂卓(DBZD)的策略。用 Immunalysis™ 苯二氮卓直接酶联免疫吸附测定试剂盒测试了 22 种 DBZD 和代谢物的交叉反应。该试剂盒的分析物内精密度很高(变异系数小于 15%)。分析物之间的性能各不相同,在浓度为 35 至 460 μg/L 时会触发确认测试。CCRFSL 于 2019 年实施了 40 个分析物的苯并二氮杂卓和 Z-药物确认方法。随后又对另外10种分析物进行了定性报告验证,13种分析物的检出限(LOD)降低了60%。此外,还优化了标准添加方法,以便按需定量。等权重因子和 1/x 权重因子与目标浓度的相关性很好(决定系数 (r2) > 0.98),但 1/x 权重因子提供的浓度最稳定准确。开发了六个计算模型来预测 DBZD 与γ-氨基丁酸-A 受体的结合亲和力,以协助病例解释(交叉验证和测试集预测的 r2 > 0.7)。这些模型用于预测确认方法中分析物的结合亲和力。其他公共实验室也可以使用相同的实用策略来适应任何设计药物类别(如苯二氮卓类、阿片类、大麻类和兴奋剂)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A computationally supported designer benzodiazepine strategy for public toxicology laboratories.

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).

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来源期刊
CiteScore
5.10
自引率
20.00%
发文量
92
审稿时长
6-12 weeks
期刊介绍: The Journal of Analytical Toxicology (JAT) is an international toxicology journal devoted to the timely dissemination of scientific communications concerning potentially toxic substances and drug identification, isolation, and quantitation. Since its inception in 1977, the Journal of Analytical Toxicology has striven to present state-of-the-art techniques used in toxicology labs. The peer-review process provided by the distinguished members of the Editorial Advisory Board ensures the high-quality and integrity of articles published in the Journal of Analytical Toxicology. Timely presentation of the latest toxicology developments is ensured through Technical Notes, Case Reports, and Letters to the Editor.
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