Opioids are drugs whose use has increased dramatically over the last two decades. Opioids are a family of drugs that includes the illegal drug heroin, synthetic opioids such as fentanyl, and painkillers that are legally available on prescription. Unfortunately, too long use of these drugs can lead to addiction, which might cause disturbed physiological and mental effects. Regular opioid usage might cause common mental disorders such as depression, anxiety, and panic disorder. However, there is still no rapid detection method to describe the chemical changes caused by the Opioid use disorder. For this reason, this study used conventional FT-Raman spectroscopic techniques with multivariate analysis to detect chemical changes in serum following opiate administration. In the FT-Raman spectrum collected from opioid-addicted patients, significant shifts of peaks at 892 cm−1, 966 cm−1, 1286 cm−1, 1459 cm−1 and 2940 cm−1 were visible in comparison with the spectrum of serum collected from the control group. Furthermore, changes in the ratio of amides and lipids were observed in the non-control group, suggesting that opioids could cause structural changes in the compounds. Synchronous spectra show auto peaks at 2914 cm−1, 3415 cm−1 while asynchronous negative cross area between 1005 cm−1 and 1800 cm−1 and around 3000 cm−1 indicate higher presence of polysaccharides and amides in comparison with other compounds in serum collected from non-control group. Finally, the PCA model, utilizing three components that explain 94.89 % of the data variation within the 300–3700 cm⁻¹ range, demonstrates excellent performance. The ensemble classification method achieves accuracies of 97.96 % and 95.00 % on the training and test datasets, respectively. Furthermore, the method achieves AUC-ROC scores of 1.00 and 0.99 for the training and test sets, effectively distinguishing between control and opioid-addicted individuals.
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