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Updated: Jun 3, 2025

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From Spectra to Signatures: Detecting Fentanyl in Human Nails with ATR-FTIR and Machine Learning.

Aubrey Barney1, Václav Trojan2,3, Radovan Hrib2,4

  • 1Department of Environmental Toxicology, Texas Tech University, Lubbock, TX 79409, USA.

Sensors (Basel, Switzerland)
|January 11, 2025
PubMed
Summary
This summary is machine-generated.

Human nail analysis can detect fentanyl use. Combining ATR-FTIR spectroscopy and machine learning accurately distinguished fentanyl users from non-users, showing nails are a viable toxicological sample.

Keywords:
ATR–FTIRPLS-DASVM-DAfentanylfingernailsmachine learningtoenails

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Area of Science:

  • Forensic toxicology
  • Analytical chemistry
  • Machine learning applications

Background:

  • Human nails are increasingly recognized as a valuable matrix for toxicological analysis due to their keratin composition.
  • Fentanyl abuse poses a significant public health crisis, necessitating reliable detection methods.

Purpose of the Study:

  • To investigate the efficacy of Attenuated Total Reflectance Fourier-Transform Infrared (ATR-FTIR) spectroscopy combined with machine learning for differentiating fentanyl use from nail samples.
  • To establish human nails as a viable sample type for fentanyl toxicology.

Main Methods:

  • Utilized ATR-FTIR spectroscopy to analyze fentanyl in human nail samples.
  • Developed and applied machine learning models, specifically Partial Least Squares Discriminant Analysis (PLS-DA) and Support Vector Machine Discriminant Analysis (SVM-DA), for sample classification.
  • Evaluated model performance based on overall accuracy and donor-level classification.

Main Results:

  • Achieved high accuracy rates: 84.8% with PLS-DA and 81.4% with SVM-DA in differentiating samples.
  • Attained perfect classification (100%) at the donor level, successfully distinguishing individuals who used fentanyl from those who did not.
  • Demonstrated the potential of the combined technique for identifying fentanyl exposure through nail analysis.

Conclusions:

  • ATR-FTIR spectroscopy coupled with machine learning provides an effective method for differentiating fentanyl use via nail analysis.
  • Human nail samples are a suitable and viable matrix for toxicological screening of fentanyl.
  • This approach offers a promising tool for forensic and clinical toxicology, aiding in the detection of fentanyl abuse.