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Updated: Jan 10, 2026

Author Spotlight: An Efficient Methodology to Confidently Differentiate and Characterize Fentanyl Analogs
Published on: November 8, 2024
A Novel and Validated GC-MS/MS Method for the Detection of Four Opioids and Seven Fentanoids in Oral Fluid for
Roberta Tittarelli1, Davide Filardi1,2, Federico Mineo1
1Laboratory of Forensic Toxicology, Section of Legal Medicine, Social Security and Forensic Toxicology, Department of Biomedicine and Prevention, Faculty of Medicine and Surgery, University of Rome Tor Vergata, Via Montpellier 1, 00133 Rome, Italy.
Abstract:
In recent years, the marked increase in the abuse of fentanyl and its analogues has emphasized the importance of developing highly sensitive and selective analytical methods for their detection in biological matrices. Oral fluid (OF) has emerged as a useful alternative to blood in forensic toxicology, offering a non-invasive and easily accessible matrix for the identification of a recent drug intake. However, its composition requires rigorous sample preparation and robust analytical techniques. A gas chromatography-tandem mass spectrometry (GC-MS/MS) method was developed and validated for the quantification of four opioids and seven fentanyl analogues. A fast and simple solid-phase extraction (SPE) procedure was optimized, enabling the identification and quantification of all analytes in 11 min. The method was validated according to international guidelines, showing a satisfactory degree of linearity (R2 ≥ 0.993), precision, accuracy, and sensitivity, with limit of detections (LODs) ranging from 0.10 to 0.20 ng/mL. The method was then successfully applied to n = 10 real OF samples collected during traffic stops set up by police forces which tested negative at the screening tests. Two samples tested positive for codeine and morphine, and one was positive for fentanyl and norfentanyl. The small number of samples currently limits the interpretation of the results. However, our study represents a good starting point for further application of this method to a wider population of real samples.
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