DiscoverThis Week in Addiction Medicine from ASAMLead: Machine learning– and multilayer molecular network–assisted screening hunts fentanyl compound
Lead: Machine learning– and multilayer molecular network–assisted screening hunts fentanyl compound

Lead: Machine learning– and multilayer molecular network–assisted screening hunts fentanyl compound

Update: 2025-09-16
Share

Description

Machine learning– and multilayer molecular network–assisted screening hunts fentanyl compounds


Science Advances


Fentanyl and its analogs are a global concern, making their accurate identification essential for public health. This article introduces Fentanyl-Hunter, a screening platform that uses a machine learning classifier and multilayer molecular network that covers more than 87% of known fentanyls to select and annotate fentanyl compounds using mass spectrometry (MS). Fentanyl-Hunter identified fentanyl members in biological and environmental samples. During biotransformation, 35 metabolites from four widely consumed fentanyl derivatives were identified. Norfentanyl was the major fentanyl compound in wastewater. Retrospective screening of these biomarkers across more than 605,000 MS files in public datasets revealed fentanyl, sufentanil, norfentanyl, or remifentanil acid in more than 250 samples from eight major countries, indicating the potential widespread presence of fentanyl.


 


Read this issue of the ASAM Weekly


Subscribe to the ASAM Weekly


Visit ASAM

Comments 
loading
In Channel
loading
00:00
00:00
1.0x

0.5x

0.8x

1.0x

1.25x

1.5x

2.0x

3.0x

Sleep Timer

Off

End of Episode

5 Minutes

10 Minutes

15 Minutes

30 Minutes

45 Minutes

60 Minutes

120 Minutes

Lead: Machine learning– and multilayer molecular network–assisted screening hunts fentanyl compound

Lead: Machine learning– and multilayer molecular network–assisted screening hunts fentanyl compound

American Society of Addiction Medicine