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Journal Article

Citation

Ovenden SPB, McDowall LJ, McKeown HE, McGill NW, Jones OAH, Pearson JR, Petricevic M, Rogers ML, Rook TJ, Williams J, Webster RL, Zanatta SD. Forensic Sci. Int. 2021; 321: e110742.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.forsciint.2021.110742

PMID

unavailable

Abstract

From an analytical chemistry standpoint, determining the chemical attribution signatures (CAS) of synthetic reaction mixtures is an impurity profiling exercise. Identifying and understanding the impurity profile and CAS of these chemical agents would allow them to be exploited for chemical forensic information, such as how a particular chemical agent was synthesised. Being able to determine the synthetic route used to make a chemical agent allows for the possibility of batches of the agent, and individual incidents using that agent, to be forensically linked. This information is of particular benefit to agencies investigating the nefarious and illicit use of chemical agents. One such chemical agent of interest to law enforcement and national security agencies is fentanyl. In this study two acylation methods for the final step of fentanyl production, herein termed the Janssen and Siegfried methods, were investigated by liquid chromatography- high resolution mass spectrometry (LC-HRMS) and multivariate statistical analysis (MVA). From these data, fifty-five chemical impurities were identified. Of these, ten were specific CAS for the Janssen method, and five for the Siegfried method. Additionally, analytical data from four different literature methods for production of the fentanyl precursor 4-anilino-N-phenethylpiperidine (ANPP), were compared to the results obtained from the method of production (Valdez) used in this study. Comparison of the LC-HRMS data for these five methods allowed for four Valdez specific impurities to be identified. These may be useful CAS for the Valdez method of ANPP production.


Language: en

Keywords

Fentanyl; Chemical attribution signatures; Chemical forensics; Impurity profiling; LC-HRMS; Method attribution

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