Principal investigator
Jun Ye

Air Force Office of Scientific Research (AFOSR); National Institute of Standards and Technology (NIST); National Science Foundation (NSF)

Collaboration + support
BioFrontiers Institute; Physics; Chemistry; Molecular, Cellular and Developmental Biology; JILA; Venture Partners at 鶹ѰBoulder; NIST; University of Colorado Anschutz Medical Campus

Breathalyzer based on frequency comb spectroscopy quantum tech shows promise as a non-invasive diagnostic test for an array of diseases

With each breath, humans exhale more than 1,000 distinct molecules, producing a unique chemical “breathprint” rich with clues about what’s happening inside the body.

For decades, scientists have sought to harness that information, even turning to dogs to literally sniff out cancer, diabetes, tuberculosis and more.

Now, scientists have developed a new laser-based “nose” powered by quantum technology and artificial intelligence (AI) that could someday diagnose an array of diseases swiftly and cheaply.

Already, research shows, the high-tech breathalyzer can detect COVID-19 in minutes with excellent accuracy.

“There is a real, foreseeable future in which you could go to the doctor and have your breath measured along with your height and weight . . . or you could blow into a mouthpiece integrated into your phone and get information about your health in real-time,” said senior author Jun Ye, a fellow and adjoint professor of physics at 鶹ѰBoulder.

As far back as 2008, Ye’s lab reported that a technique called frequency comb spectroscopy—essentially using laser light to distinguish one molecule from another—could potentially identify biomarkers of disease in human breath.

Ye’s team has since improved the sensitivity more than a thousandfold, enabling detection of trace molecules at the parts-per-trillion level. They’ve also increased the number of colors the laser emits, enabling them to detect more species of molecule. And they’ve harnessed the power of AI.

“Molecules increase or decrease in concentrations when associated with specific health conditions,” said first author Qizhong Liang, a PhD candidate in JILA and the Department of Physics. “Machine learning analyzes this information, identifies patterns and develops criteria we can use to predict a diagnosis.”

Mid-pandemic Liang and Ye collaborated with scientists at the BioFrontiers Institute, which headed up the campus COVID-19 testing program, to see how well the system did in detecting the virus.

Between May 2021 and January 2022, the team collected breath samples from 170 鶹ѰBoulder students who had, in the previous 48 hours, taken a polymerase chain reaction (PCR) test by submitting a saliva or a nasal sample. Half had tested positive, half negative. The breathalyzer process took less than one hour from collection to result.

When compared to PCR, the gold standard test, breathalyzer results matched 85% of the time. For medical diagnostics, accuracy of 80% or greater is considered “excellent.” The future health applications are huge, the authors said.

“What if you could find a signature in breath that could detect pancreatic cancer before you were even symptomatic? That would be the home run,” said collaborator Leslie Leinwand, chief scientific officer for the BioFrontiers Institute.

Unlike other diagnostic tests, the breathalyzer is non-invasive and doesn’t require costly chemicals to break down the sample. But there is still much to learn before it can be commercialized.

Today, the system consists of a complex array of lasers and mirrors about the size of a banquet table.

A breath sample is piped in through a tube as lasers fire invisible mid-infrared light at it at thousands of different frequencies. Dozens of tiny mirrors bounce the light back and forth through the molecules.

Because each kind of molecule absorbs light differently, breath samples with a different molecular makeup cast distinct shadows. The machine can distinguish between those different shadows, boiling millions of data points down to a simple positive or negative in seconds.

Efforts are now underway to miniaturize such systems, allowing for “real-time, self-health monitoring on the go.” And the team plans to soon collaborate with colleagues at the Anschutz Medical Campus to see if their system can detect other diseases.

“If you think about dogs, they evolved over thousands of years to smell many different things with remarkable sensitivity,” said Ye. “The more we teach our laser-based nose, the smarter it will become.”

Photo: Qizhong Liang, a PhD candidate in JILA and the Department of Physics, demonstrates how the laser-based breathalyzer works, in the Ye lab at JILA.Photo: Patrick Campbell/University of Colorado.