Machine learning program accurately predicts structure of unknown psychoactive substances from mass spectra alone
Novel psychoactive substances (NPS) – designer drugs like ‘bath salts’ and synthetic opioids – are a scourge of our times. Law enforcement agencies that try to control them and medics who treat their consequences are locked in a cat-and-mouse game with clandestine chemists who quickly devise new compounds, typically by modifying known molecules, to skirt the law and create new ‘legal highs’. Authorities see more than a dozen new designer drugs every month, and identifying their structures can take many weeks using techniques like nuclear magnetic resonance (NMR) , by which time they may have already been used by thousands of people.
Now a new artificial intelligence system could change the game. Dubbed DarkNPS, it’s based on a recurrent neural network that can accurately predict NPS structures from their mass spectra alone. The process is relatively quick, taking just a few days, and that could give medics an edge in their battle against new designer drugs, and give law enforcement agencies a faster way to deal with them.