The Opioid Detection Challenge

A $1.55 million competition for rapid, nonintrusive detection tools that will help find illicit opioids in international mail.

Meet the Finalists


  • Call for stage 1 submissions
    February 27, 2019
  • Stage 1 submission deadline
    April 24, 2019
  • Stage 1 finalists announced
    June 2019
  • Stage 2 prototyping accelerator
    June - September 2019
  • current stageStage 2 live test event
    October 2019
  • Stage 2 winner(s) announced
    December 2019
Detailed Schedule


The opioid crisis

The abuse of opioids such as fentanyl has created an unprecedented public health crisis across the United States. In 2017, approximately 50,000 Americans died from opioid overdoses. International mail has been identified as a route for illicit opioids entering the United States, commonly transported in nearly pure, powdered form. Consequently, large-scale drug trafficking can occur via small packages sent in the mail.

A collaborative effort

As part of the comprehensive government effort to address the opioid crisis, the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) and U.S. Customs and Border Protection (CBP), along with the United States Postal Inspection Service (USPIS) and the Office of National Drug Control Policy (ONDCP), are seeking new tools and technologies to detect opioids in parcels moving through international service centers and express consignment facilities.

Seeking solutions

The Challenge called on innovators in a wide range of fields, from forensic science to industrial quality assurance to artificial intelligence, to help disrupt the flow of opioids into the United States by participating in this Challenge. The Challenge seeks novel, automated, nonintrusive, user-friendly and well-developed designs for tools and technologies that have the potential to quickly and accurately detect opioids in parcels, without disrupting the flow of mail.

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Judges helped select eight (8) finalists according to the Stage 1 selection criteria. The total Stage 1 prize pool of $800,000 was distributed evenly across Stage 1 finalists.


Atomic-level Drug Detection

A solution to use high-frequency radio waves in a particle accelerator technology developed by the European Organization for Nuclear Research (known as CERN). As neutrons and gamma rays pass through parcels, the solution analyzes the energy spectra produced.


Automated Multimodal Opioid Detection

A layered approach to opioid detection. Machine learning algorithms are applied to images captured through dual-energy radiography and hyperspectral imaging.

HALO X-ray Technologies

Enhanced X-ray Diffraction

A solution to detect the presence of opioids by measuring how X-rays are diffracted when they pass through a parcel. By emitting the X-rays in a conical structure, this solution generates a stronger signal and improves the accuracy and speed of detection.

One Resonance

Nonimaging Concealed Drug Detector

A quadrupole resonance technology that uses radio-frequency signals to search for specific materials. An alarm is triggered when a signal associated with an illicit substance is detected.

GTBM, Inc.

Noninvasive Detection Using Molecular Signatures

A solution to use ultrasound technology in a molecular resonance detector that transmits sound waves and analyzes the returned frequencies. These frequencies are analyzed to define the distinct atomic/molecular signature of the target sample.

Vadum, Inc.

NQR Detection of Nitrogen-Containing Substances

A nuclear quadrupole resonance (NQR) technology that emits radio-frequency pulses to detect specific nitrogen-containing molecules. Illicit substances resonate at different frequencies, allowing detection of targeted compounds.


Operator-free X-ray Diffraction

An energy dispersive X-ray diffraction (EDXRD) technology that uses a polychromatic beam to increase signal strength and detection speed. Diffraction patterns are compared with a library of known threats.

IDSS Holdings

Scanner and Algorithms for Automatic Opioid Detection

A solution that combines a 3D X-ray computed tomography (CT) scanner with automated detection algorithms. It detects anomalies in X-ray images based on the scanned item’s features and physical properties.
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$1.55 million

The judges helped select eight (8) finalists according to official Stage 1 selection criteria, with each finalist to be awarded $100,000 in Stage 1.

During Stage 2, the finalists from Stage 1 will compete for an additional $750,000 in cash prizes. The grand prize winner is expected to be awarded $500,000, and the runner-up to be awarded $250,000.

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