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Detection of Fentanyl Analogues in Illicit Drug Samples Using Surface-Enhanced Raman Spectroscopy and Random Forest

Ella Newman1, Rebecca R Martens1, Lea Gozdzialski1

  • 1Department of Chemistry, University of Victoria, Victoria, British Columbia, Canada.

Applied Spectroscopy
|June 4, 2026
PubMed
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This summary is machine-generated.

New drug checking methods accurately detect fentanyl analogues below 5% w/w, crucial for harm reduction. Surface-enhanced Raman scattering shows promise, but challenges remain with analogue mixtures.

Area of Science:

  • Analytical Chemistry
  • Forensic Science
  • Public Health

Background:

  • The overdose crisis is driven by unregulated opioids, necessitating advanced drug checking.
  • Fentanyl and its analogues pose significant risks, even at low concentrations.
  • Current detection methods struggle with low concentrations and complex mixtures.

Purpose of the Study:

  • To evaluate surface-enhanced Raman scattering (SERS) combined with random forest classifiers for detecting fentanyl analogues.
  • To assess the accuracy and precision of this method for real-world samples.
  • To address the challenge of detecting analogues below 5% w/w.

Main Methods:

  • Utilized surface-enhanced Raman scattering (SERS) spectroscopy.
  • Employed random forest binary classifiers for data analysis.
Keywords:
FT-IRFentanyl analoguesFourier transform infrared spectroscopySERSdrug checkingmachine learningrandom forest classificationsurfance-enhance Raman spectroscopy

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  • Tested the method on real-world samples containing fentanyl, para-fluorofentanyl, and ortho-methyl fentanyl.

    • Main Results:

    • Achieved high accuracy (0.93-0.93) and precision (0.96-0.96) for single-analogue detection.
    • Successfully detected fentanyl analogues in the range of 0.2-29.4% w/w.
    • Observed signal suppression in mixtures, complicating the identification of lower-concentration analogues.

    Conclusions:

    • SERS and random forest classification are effective for detecting single fentanyl analogues in real-world samples.
    • There is a critical need for methods to detect fentanyl analogues below 5% w/w.
    • Further research is required to address signal suppression in analogue mixtures.