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Tuesday, November 5th, 2024

Smiths Detection adapts three technologies for fentanyl identification

As dangerous opioids like fentanyl continue to be an increasing issue for law enforcement, Smiths Detection, Inc. (SDI) recently announced that it has adapted three of its technologies in order to detect and identify fentanyl to limit officers’ exposure to the drug on duty.

Unlike more common opioids like oxycontin and Vicodin, fentanyl, if inhaled, could lead to respiratory arrest. According to CNN, the drug can be up to 50 times more powerful than heroin and 50 to 100 times more potent than morphine, prompting fears of a public health crisis and for the safety of first responders.

“The new fentanyl threat to first responders is real and severe since accidental contact with- or inhalation-of very small amounts can be life threatening,” Shan Hood, vice president of Product and Technology for Smiths Detection, said. “The right technology can help first responders make better informed decisions about how best to protect themselves from fentanyl and its analogues during emergencies.”

To address concerns over exposure to the drug, Smiths announced it has adapted its IONSCAN 600, a scanner currently used in airports, corrections facilities and security checkpoints to detect trace amount of narcotics and explosives in a matter of seconds.

Additionally, the company’s HazMatID Elite/Target ID technology was also adapted for fentanyl identification and works by utilizing infrared handheld chemical identifiers to perform chemical analysis on bulk amounts of solids and liquids, which could be used as court-admissible evidence.

A third technology, called ACE-ID, uses laser Raman technology to test bulk quantities of unknown substances without contact, including through plastic and glass.

According to the company, the technologies were designed to complement one another in response scenarios, but can work independently. SDI also enhanced its ReachBackID 24/7 hotline in order to give first responders access to Ph.D. scientists to support field-based analysis.