To help keep first responders safe, University of Central Florida researchers have developed an artificial intelligence method that not only rapidly and remotely detects the powerful drug fentanyl, but also teaches itself to detect any previously unknown derivatives made in clandestine batches. The method, published recently in the journal Scientific Reports, uses infrared light spectroscopy and can be used in a portable, tabletop device. Fentanyl is a leading cause of drug overdose death in the U.S. It and its derivatives have a low lethal dose and may lead to death of the user, could pose hazards for first responders and even be weaponized in an aerosol." Fentanyl, which is 50 to 100 times more potent than morphine according to the U.S. Centers for Disease Control and Prevention, can be prescribed legally to treat patients who have severe pain, but it also is sometimes made and used illegally. He said that rapid identification methods of both known and emerging opioid fentanyl substances can aid in the safety of law enforcement and military personnel who must minimize their contact with the substances.

A patient's own molecular data can be used to identify, with the use of artificial intelligence methods, the best combinatorial multi-drug therapy for that patient. Network modeling plays a major role in this line of work. The ongoing research on artificial intelligence methods for precision cancer medicine at the Computational Biomodeling (Combio) Laboratory of Åbo Akademi and Turku Centre for Computer Science (TUCS) got a major boost with renewed funding from Business Finland. The concept of this project is that a patient's own molecular data can be used to identify, with the use of artificial intelligence methods, the best combinatorial multi-drug therapy for that patient. Network modeling plays a major role in this line of work, integrating genome-scale patient data into detailed interaction networks, that can be analyzed by Combio's recently developed algorithms to identify combinations of drugs and inhibitors that are likely to be therapeutically effective.