Application of a novel screening workflow for the detection of illicit and medicinal drugs in human hair

Significance of the Topic

Hair analysis extends the detection window of drug intake from days to months, providing invaluable information for forensic toxicology, clinical monitoring, occupational health and anti‐doping control. By capturing long‐term exposure profiles, hair screening reveals patterns of illicit and medicinal drug use that cannot be discerned from blood or urine testing.

Objectives and Study Overview

This work evaluates a novel non‐targeted screening workflow combining high‐resolution quadrupole time‐of‐flight LC–DIA–MS/MS with an advanced component detection algorithm in Insight Discovery software. The primary goals were to detect single and multiple drug use in human hair extracts with high confidence, automate data processing, and demonstrate the ability to identify both known and unexpected analytes.

Methodology

An untargeted LC–DIA–MS/MS method was developed for hair extracts:

• Chromatography: Shim-pack Velox Biphenyl column (2.1 × 100 mm, 2.7 µm) at 40 °C, 17 min gradient; mobile phases water and methanol, each with 2 mM ammonium formate and 0.002 % formic acid.
• Mass spectrometry: Shimadzu LCMS-9030 QTOF in positive ESI; TOF MS scan m/z 100–1000 (100 ms), 17 DIA MS/MS scans (m/z 40–500, 25 Da isolation, 40 ms) and 12 DIA MS/MS scans (m/z 40–900, 35 Da, 25 ms) with 5–55 V collision energy spread; external mass calibration.
• Data processing: Insight Discovery research application was used for second‐generation untargeted component detection, MS/MS library matching, suspect screening and formula prediction in batch mode.

Applied Instrumentation

• Shimadzu LCMS-9030 high‐resolution QTOF mass spectrometer
• Shim-pack Velox Biphenyl UHPLC column
• Insight Discovery software within LabSolutions Insight

Main Results and Discussion

In a batch of 24 hair samples, the workflow detected 3 384 chromatographic components and screened them against a forensic toxicology library of over 1 200 compounds. Key findings included:

• Four samples positive for cocaine and its primary metabolite benzoylecgonine; two samples contained low levels of codeine.
• Widespread detection of caffeine, nicotine and DEET as common co‐analytes.
• Identification of polydrug markers such as cocaethylene, ecgonine methyl ester, levamisole, MDMA, sildenafil and quinine.
• Thirteen precursor matches at user-defined low thresholds; eleven targets confirmed by high‐confidence MS/MS library matching.

The high‐resolution DIA–MS/MS approach delivered library‐searchable spectra despite sample complexity, and formula prediction provided additional confirmation for unknown components.

Benefits and Practical Applications

The automated Insight Discovery workflow enables rapid, reproducible non‐targeted screening of hair samples with minimal manual intervention. High reporting confidence, combined with formula prediction, supports forensic casework, clinical toxicology assessments and compliance testing in workplace and sports settings.

Future Trends and Possibilities

Advances in spectral libraries, machine learning–driven component detection and cloud‐based data processing will further enhance sensitivity and throughput. Expanding suspect screening to emerging psychoactive substances and integrating quantitative capabilities may broaden applications to environmental monitoring and personalized medicine.

Conclusion

The integration of high‐resolution LC–DIA–MS/MS with Insight Discovery software provides a robust, automated non‐targeted screening platform for detecting illicit and medicinal drugs in human hair. The method achieved reliable identification of single and polydrug use, demonstrating its utility for forensic and clinical laboratories.

Reference

• Armitage EG, Brema T, Bowen CA, Barnes NJ, Steel R, Loftus L. Application of a novel screening workflow for the detection of illicit and medicinal drugs in human hair. Shimadzu White Paper, 2023.
• Shimadzu High Resolution Accurate Mass Library for Forensic Toxicology.
• HighResNPS library (https://highresnps.com/).
• Wiley Registry of Tandem Mass Spectral Data: MS for ID.
• Maurer/Meyer/Helfer/Weber LC–HR–MS/MS Library of Drugs, Poisons, and Their Metabolites.