Breakthrough for Improved AI-Based At-Home Testing Technology of Hepatitis and COVID-19
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Breakthrough for Improved AI-Based At-Home Testing Technology of Hepatitis and COVID-19
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Breakthrough for Improved AI-Based At-Home Testing Technology of Hepatitis and COVID-19.
In addition to pregnancy and COVID-19, the world may one day soon rely on home tests for many diseases, thanks in part to improvements powered by artificial intelligence.
Scientists at the University of Florida (UF) have used artificial intelligence tools to simplify a test that is effective for both hepatitis C and SARS-CoV-2, the virus that causes COVID-19.
The simplified test takes a few minutes in a small test tube. With further refinement, it may soon be available in doctors’ offices, and even one day as a home test as simple as a pregnancy test.
“We’re trying to create a home-based test that is as reliable as a lab-based test,” said Piyush Jain, a UF professor of chemical engineering who led the latest research. “We’re trying to make the test simple and eliminate the need for expensive equipment, And provide results in as little as 10 to 20 minutes.”
To achieve these goals, Jain’s group is innovating on a system known as a one-tube reaction, because the entire test takes place in one small test tube. The tests are based on a technique known as RT-LAMP, which amplifies a small portion of the virus’ genome and produces a visible signal when it is detected. Reading these tests can be as simple as looking for blue, or using a small device that detects changes in a test tube.
The U.S. Food and Drug Administration has approved some at-home one-tube tests for COVID-19 as part of an emergency use authorization, but their relatively high rate of false positives means they’re not as reliable as they could be .
“We are combining it with another technology called CRISPR to determine the difference between false positives and true positives,” Jain said.
Known in the biotech world for its ability to drive rapid genetic engineering improvements, CRISPR could one day cure inherited diseases by repairing the genome.
Jain’s group relies on the CRISPR system’s ability to target specific genetic sequences. The test will only show a positive result if the sequence, such as the hepatitis virus, is actually present.
The only problem? The RT-LAMP technique requires temperatures of 150 degrees Fahrenheit, while CRISPR works best at 100 degrees Fahrenheit.
This difference makes the test more complicated, requiring two separate responses — too complex for home use. Jain’s team has been trying to close this gap by developing a CRISPR system that can withstand higher temperatures.
Researchers recently identified a CRISPR enzyme from a thermophilic bacterial species that can grow at 140 degrees. In their latest work, Jain’s group turned to artificial intelligence tools to analyze the enzyme and discover how they could make it survive 150 degrees.
The AI program suggested dozens of changes to the enzyme, which Jain’s team tested in the lab. They eventually found four ways to alter the enzyme to make it work at 150 degrees.
“Doing this kind of analysis on an enzyme is very challenging for any human being. Instead of taking years, we can make these improvements in a few months,” Jain said. “Since everything is working at the same temperature, we are now able to combine everything in a true one-pot reaction, which we call SPLENDID.”
The team validated their simplified SPLENDID test on clinical samples from patients with hepatitis C or COVID-19. The test was 97 percent accurate for SARS-CoV-2 and 95 percent accurate for the version of the hepatitis C virus most prevalent in the world.
Although it doesn’t work very well against all the other less dominant versions of the hepatitis C virus, a direct modification of the test should rapidly improve its accuracy, Jain said. His team published their findings May 8 in the journal Cell Reports Medicine.
The work, funded by the National Institute of Allergy and Infectious Diseases at the National Institutes of Health, hopes to develop simple tests for viruses like hepatitis C so that they can be detected and treated early, when treatments are most effective.
Jain’s research group will now work to refine the test, improve its ability to distinguish strains of hepatitis C virus, and validate it in a hospital setting, with the hope that one day it will also be available as a home test.
Breakthrough for Improved AI-Based At-Home Testing Technology of Hepatitis and COVID-19
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