Researchers at MIT have developed PlasmoSniff, a breath test that uses nanoparticles and enhanced Raman spectroscopy to detect pneumonia and other lung conditions in minutes, potentially enabling rapid at-home or clinical diagnosis.
<p>With a test being developed at MIT, diagnosing pneumonia and other lung conditions could someday be as easy as breathing into a tube. </p>
<p>The test, dubbed PlasmoSniff, is a portable, chip-scale sensor that traps and detects biomarkers, synthetic compounds indicating disease. The idea is that a person would first breathe in nanoparticles that are specially designed to attach to these biomarkers, detaching from them only in the presence of specific enzymes that the body produces during an infection. Professor Sangeeta Bhatia, SM ’93, PhD ’97, and her lab have been working on such nanoparticle sensors for years.</p>
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<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="2500" height="1667" src="https://wp.technologyreview.com/wp-content/uploads/2026/06/MIT-PlasmoSniff-02-press.jpg?w=2500" alt="a penny next to the PlasmoSniff chip for scale shows the penny's diameter to be almost 7 times the chip's diameter" class="wp-image-1138345" srcset="https://wp.technologyreview.com/wp-content/uploads/2026/06/MIT-PlasmoSniff-02-press.jpg 2500w, https://wp.technologyreview.com/wp-content/uploads/2026/06/MIT-PlasmoSniff-02-press.jpg?resize=300,200 300w, https://wp.technologyreview.com/wp-content/uploads/2026/06/MIT-PlasmoSniff-02-press.jpg?resize=768,512 768w, https://wp.technologyreview.com/wp-content/uploads/2026/06/MIT-PlasmoSniff-02-press.jpg?resize=1536,1024 1536w, https://wp.technologyreview.com/wp-content/uploads/2026/06/MIT-PlasmoSniff-02-press.jpg?resize=2048,1366 2048w" sizes="auto, (max-width: 2500px) 100vw, 2500px" /><div class="image-credit">TONY PULSONE</div>
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<p>If the person is healthy, the particles would eventually circulate out of the body intact. In someone with a disease such as pneumonia, however, the enzymes would snip off the biomarkers, freeing them to be exhaled and measured.</p>
<p>In a 2020 paper, Bhatia’s lab demonstrated that the nanoparticles could be used to detect pneumonia in the breath of mice, but the measurements required laboratory-grade instruments not available in most doctor’s offices. Now Loza Tadesse, an assistant professor of mechanical engineering, and her colleagues have shown they can detect exhaled biomarkers of pneumonia at extremely low concentrations using an enhanced form of Raman spectroscopy, an optical technique in which molecules are illuminated with light.</p>
<p>They plan to incorporate the new sensor into a handheld instrument that could be used in clinical settings or at home. “We envision that a patient would inhale nanoparticles and, within about 10 minutes, exhale a synthetic biomarker that reports on lung status,” says Aditya Garg, an MIT postdoc and lead author of a paper on the work.</p>
<p>Detecting diseases like pneumonia is not the system’s only potential application. “It can sniff out industrial chemicals or airborne pollutants as well,” Tadesse says.</p>
# A breath test could diagnose pneumonia in minutes
Source: [https://www.technologyreview.com/2026/06/23/1138291/a-breath-test-could-diagnose-pneumonia-in-minutes](https://www.technologyreview.com/2026/06/23/1138291/a-breath-test-could-diagnose-pneumonia-in-minutes)
With a test being developed at MIT, diagnosing pneumonia and other lung conditions could someday be as easy as breathing into a tube\.
The test, dubbed PlasmoSniff, is a portable, chip\-scale sensor that traps and detects biomarkers, synthetic compounds indicating disease\. The idea is that a person would first breathe in nanoparticles that are specially designed to attach to these biomarkers, detaching from them only in the presence of specific enzymes that the body produces during an infection\. Professor Sangeeta Bhatia, SM ’93, PhD ’97, and her lab have been working on such nanoparticle sensors for years\.
TONY PULSONE
If the person is healthy, the particles would eventually circulate out of the body intact\. In someone with a disease such as pneumonia, however, the enzymes would snip off the biomarkers, freeing them to be exhaled and measured\.
In a 2020 paper, Bhatia’s lab demonstrated that the nanoparticles could be used to detect pneumonia in the breath of mice, but the measurements required laboratory\-grade instruments not available in most doctor’s offices\. Now Loza Tadesse, an assistant professor of mechanical engineering, and her colleagues have shown they can detect exhaled biomarkers of pneumonia at extremely low concentrations using an enhanced form of Raman spectroscopy, an optical technique in which molecules are illuminated with light\.
They plan to incorporate the new sensor into a handheld instrument that could be used in clinical settings or at home\. “We envision that a patient would inhale nanoparticles and, within about 10 minutes, exhale a synthetic biomarker that reports on lung status,” says Aditya Garg, an MIT postdoc and lead author of a paper on the work\.
Detecting diseases like pneumonia is not the system’s only potential application\. “It can sniff out industrial chemicals or airborne pollutants as well,” Tadesse says\.
LMU researchers developed a Quantum Boltzmann Machine model for pneumonia detection from chest X-rays. Using fewer than 9,000 parameters (vs. millions in classical CNNs), the model achieves 84–86% accuracy, demonstrating potential advantages of quantum machine learning for small medical datasets.
A Japanese company called Iris has developed Nodoca, an AI-powered device that analyzes throat images to diagnose influenza in seconds, eliminating uncomfortable nasal swabs. Already approved in Japan and used at over 2,000 institutions, it is expanding to detect other conditions like Covid-19 and potentially lifestyle diseases.
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Intercept, a $500 million philanthropic initiative, aims to use new platform technologies and air cleaning to reduce or eliminate respiratory infections like colds and influenza, citing the significant health and economic burdens they cause.
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