UCSD - University of California - San Diego

04/13/2026 | Press release | Distributed by Public on 04/13/2026 09:06

Using Physics, Engineers Create Fentanyl Test Strips That Are 100 Times More Sensitive

Published Date

April 13, 2026

Article Content

Engineers at the University of California San Diego have developed fentanyl test strips that are about 100 times more sensitive than current commercial versions. They achieved this feat by creating a new physics-based model that explains, for the first time, how these widely used paper-strip tests work and how to systematically improve them.

The findings were published in Biophysics Reviews and featured by the American Institute of Physics (AIP).

Test strips known as lateral flow assays, which are simple, low-cost tests that show results as visible lines on a strip, became household tools during the COVID-19 pandemic. But despite widespread use and decades of development, scientists have lacked a clear, quantitative way to predict these test strips' performance or understand what limits their sensitivity. As a result, improving these tests has largely relied on trial and error.

A research team led by Yuhwa Lo, professor in the Department of Electrical and Computer Engineering at the UC San Diego Jacobs School of Engineering, tackled this hurdle by building a model based on fundamental physics. The model captures how particles move through the strip; how molecules compete to bind; and how subtle electrical interactions influence the outcome. The model then uses these factors to determine whether a test produces a visible signal and, moreover, how faint a signal it can reliably detect.

The team applied the model to a specific class of tests known as competitive lateral flow assays (cLFAs), which are commonly used to detect small molecules like fentanyl. In these tests, a positive result appears as the absence of a line. If fentanyl is present, it binds to antibodies attached to gold nanoparticles and prevents them from producing a visible line at the test region. If fentanyl is absent, the nanoparticles bind at the test line and produce a signal to indicate a negative result.

Using their model, the researchers identified the key parameters that limit sensitivity. These included the concentrations of antibodies, target molecules and nanoparticles, as well as how strongly they bind to one another. By optimizing these factors - such as reducing excess antibodies and minimizing interference from non-target molecules - they dramatically improved test performance.

The result was a new fentanyl test strip capable of detecting much lower concentrations than existing commercial options. The new strip exhibited roughly a 100-fold increase in sensitivity.

"This kind of universality is powerful," Lo said. "A single, unified framework can provide clear, actionable guidance for sensitivity optimization across many cLFAs, helping accelerate development and improve performance throughout the field."

In addition to fentanyl detection, the researchers say the model provides a strategy for improving a wide range of rapid diagnostic tests. It could potentially accelerate the development of more reliable, point-of-care tests for applications ranging from drug detection to infectious disease screening.

The team hopes to extend the approach to other types of lateral flow assays, including those used in HIV, STD, RSV, flu and COVID-19 tests.

"This could strengthen the reliability of existing point-of-care tests and expand what can be detected outside centralized laboratories, potentially enabling rapid screening for clinically important targets that currently rely on lab-based methods, including certain sexually transmitted infections and other low-abundance disease biomarkers," Lo said.

Full study: "Analytical physics framework for competitive binding and transport lateral flow assays: Application to fentanyl detection"

The authors report that this research is not supported by any external sources of funding and have no conflicts to disclose.

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