Mayer Brian P, DeHope Alan J, Mew Daniel A, Spackman Paul E, Williams Audrey M
Forensic Science Center, Lawrence Livermore National Laboratory , 7000 East Avenue L-091, Livermore, California 94550, United States.
Materials Science Division, Lawrence Livermore National Laboratory , 7000 East Avenue L-382, Livermore, California 94550, United States.
Anal Chem. 2016 Apr 19;88(8):4303-10. doi: 10.1021/acs.analchem.5b04434. Epub 2016 Mar 30.
Attribution of the origin of an illicit drug relies on identification of compounds indicative of its clandestine production and is a key component of many modern forensic investigations. The results of these studies can yield detailed information on method of manufacture, starting material source, and final product, all critical forensic evidence. In the present work, chemical attribution signatures (CAS) associated with the synthesis of the analgesic fentanyl, N-(1-phenylethylpiperidin-4-yl)-N-phenylpropanamide, were investigated. Six synthesis methods, all previously published fentanyl synthetic routes or hybrid versions thereof, were studied in an effort to identify and classify route-specific signatures. A total of 160 distinct compounds and inorganic species were identified using gas and liquid chromatographies combined with mass spectrometric methods (gas chromatography/mass spectrometry (GC/MS) and liquid chromatography-tandem mass spectrometry-time of-flight (LC-MS/MS-TOF)) in conjunction with inductively coupled plasma mass spectrometry (ICPMS). The complexity of the resultant data matrix urged the use of multivariate statistical analysis. Using partial least-squares-discriminant analysis (PLS-DA), 87 route-specific CAS were classified and a statistical model capable of predicting the method of fentanyl synthesis was validated and tested against CAS profiles from crude fentanyl products deposited and later extracted from two operationally relevant surfaces: stainless steel and vinyl tile. This work provides the most detailed fentanyl CAS investigation to date by using orthogonal mass spectral data to identify CAS of forensic significance for illicit drug detection, profiling, and attribution.
非法药物来源的归因依赖于对表明其秘密生产的化合物的鉴定，并且是许多现代法医调查的关键组成部分。这些研究的结果可以产生关于制造方法、起始原料来源和最终产品的详细信息，所有这些都是关键的法医证据。在本工作中，对与镇痛剂芬太尼（N-(1-苯乙基哌啶-4-基)-N-苯基丙酰胺）合成相关的化学归因特征（CAS）进行了研究。研究了六种合成方法，所有这些方法均为先前发表的芬太尼合成路线或其混合版本，以努力识别和分类特定路线的特征。使用气相色谱和液相色谱结合质谱方法（气相色谱/质谱联用（GC/MS）和液相色谱-串联质谱-飞行时间质谱（LC-MS/MS-TOF））并结合电感耦合等离子体质谱（ICPMS），共鉴定出160种不同的化合物和无机物种。所得数据矩阵的复杂性促使使用多元统计分析。使用偏最小二乘判别分析（PLS-DA），对87个特定路线的CAS进行了分类，并验证了一个能够预测芬太尼合成方法的统计模型，并针对从两个与实际操作相关的表面（不锈钢和乙烯基地板）上沉积并随后提取的粗制芬太尼产品的CAS谱进行了测试。这项工作通过使用正交质谱数据来识别对非法药物检测、分析和归因具有法医意义的CAS，提供了迄今为止最详细的芬太尼CAS研究。
