Development and Validation of a UPLC-MS/MS Method for the Determination of Emerging Synthetic, Semi-Synthetic and Related Cannabinoids in Human Hair
- 1Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Via Montpellier, 1, 00133 Rome, Italy
Abstract
Synthetic cannabinoids (SCs) are an evolving group of new psychoactive substances (NPSs), characterized by structural diversity and continuously emerging analogues. Their detection in biological matrices is challenging because of low concentrations, rapid metabolism, and incomplete coverage by routine methods. Hair analysis offers a detection window for retrospective exposure assessment. This study aimed to develop and validate an ultra-performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) method for simultaneous identification and quantification of 26 synthetic, semi-synthetic, and related cannabinoids in human hair and to assess its applicability to authentic forensic samples. The method was validated for linearity, limits of detection (LOD) and quantification (LLOQ), accuracy, precision, matrix effect, recovery and process efficiency, with additional robustness assessments under freeze–thaw and processed-extract conditions, and was then applied to n = 100 hair samples collected from subjects tested positive for Δ9-tetrahydrocannabinol (Δ9-THC) during forensic assessments following driving license suspension. LODs were 1.56–3.13 pg/mg, LLOQs 6.25–12.5 pg/mg, and R2 ≥ 0.992; accuracy and precision met the predefined acceptance criteria, while ME, RE, and PE showed generally consistent mean performance with wider level-specific variability for selected analytes. Target cannabinoids were detected in 23/100 samples, with 14 different compounds identified. MDMB-4en-PINACA, 9R-HHC-O, and ADB-BUTINACA were the most frequently detected compounds. The method enabled sensitive and reliable detection of multiple emerging cannabinoid classes in hair, supporting the continuous updating of targeted analytical panels in response to the evolving NPS landscape.
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BibTeX
@article{romani2026development,
title = {{Development and Validation of a UPLC-MS/MS Method for the Determination of Emerging Synthetic, Semi-Synthetic and Related Cannabinoids in Human Hair}},
author = {Leonardo Romani and Giulio Mannocchi and Lucrezia Stefani and Luigi Tonino Marsella and Roberta Tittarelli},
journal = {Molecules},
year = {2026},
month = oct,
doi = {10.3390/molecules31213816},
url = {https://www.mdpi.com/1420-3049/31/21/3816},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Development and Validation of a UPLC-MS/MS Method for the Determination of Emerging Synthetic, Semi-Synthetic and Related Cannabinoids in Human Hair
AU - Leonardo Romani
AU - Giulio Mannocchi
AU - Lucrezia Stefani
AU - Luigi Tonino Marsella
AU - Roberta Tittarelli
PY - 2026
DA - 2026/10/22
JO - Molecules
DO - 10.3390/molecules31213816
UR - https://www.mdpi.com/1420-3049/31/21/3816
AB - Synthetic cannabinoids (SCs) are an evolving group of new psychoactive substances (NPSs), characterized by structural diversity and continuously emerging analogues. Their detection in biological matrices is challenging because of low concentrations, rapid metabolism, and incomplete coverage by routine methods. Hair analysis offers a detection window for retrospective exposure assessment. This study aimed to develop and validate an ultra-performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) method for simultaneous identification and quantification of 26 synthetic, semi-synthetic, and related cannabinoids in human hair and to assess its applicability to authentic forensic samples. The method was validated for linearity, limits of detection (LOD) and quantification (LLOQ), accuracy, precision, matrix effect, recovery and process efficiency, with additional robustness assessments under freeze–thaw and processed-extract conditions, and was then applied to n = 100 hair samples collected from subjects tested positive for Δ9-tetrahydrocannabinol (Δ9-THC) during forensic assessments following driving license suspension. LODs were 1.56–3.13 pg/mg, LLOQs 6.25–12.5 pg/mg, and R2 ≥ 0.992; accuracy and precision met the predefined acceptance criteria, while ME, RE, and PE showed generally consistent mean performance with wider level-specific variability for selected analytes. Target cannabinoids were detected in 23/100 samples, with 14 different compounds identified. MDMB-4en-PINACA, 9R-HHC-O, and ADB-BUTINACA were the most frequently detected compounds. The method enabled sensitive and reliable detection of multiple emerging cannabinoid classes in hair, supporting the continuous updating of targeted analytical panels in response to the evolving NPS landscape.
SN - 1420-3049
ER -