An At-Home Contagiousness Test for COVID-19 Already Exists. Why Can’t We Use It?
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
You're lying in bed late at night, the foggy swirl of the pandemic's 8th month just beginning to fall behind you, when you detect a slight tickle at the back of your throat.
"If half of people choose to use these tests every other day, then we can stop transmission faster than a vaccine can."
Suddenly fully awake, a jolt of panicked electricity races through your body. Has COVID-19 come for you? In the U.S., answering this simple question is incredibly difficult.
Now, you might have to wait for hours in line in your car to get a test for $100, only to find out your result 10-14 days later -- much too late to matter in stopping an outbreak. Due to such obstacles, a recent report in JAMA Internal Medicine estimated that 9 out of 10 infections in the U.S. are being missed.
But what if you could use a paper strip in the privacy of your own home, like a pregnancy test, and find out if you are contagious in real time?
e25 Bio, a small company in Cambridge, Mass., has already created such a test and it has been sitting on a lab bench, inaccessible, since April. It is an antigen test, which looks for proteins on the outside of a virus, and can deliver results in about 15 minutes. Also like an over-the-counter pregnancy test, e25 envisions its paper strips as a public health screening tool, rather than a definitive diagnostic test. People who see a positive result would be encouraged to then seek out a physician-administered, gold-standard diagnostic test: the more sensitive PCR.
Typically, hospitals and other health facilities rely on PCR tests to diagnose viruses. This test can detect small traces of genetic material that a virus leaves behind in the human body, which tells a clinician that the patient is either actively infected with or recently cleared that virus. PCR is quite sensitive, meaning that it is able to detect the presence of a virus' genetic material very accurately.
But although PCR is the gold-standard for diagnostics, it's also the most labor-intensive way to test for a virus and takes a relatively long time to produce results. That's not a good match for stopping super-spreader events during an unchecked pandemic. PCR is also not great at identifying the infected people when they are most at risk of potentially transmitting the virus to others.
That's because the viral threshold at which PCR can detect a positive result is so low, that it's actually too sensitive for the purposes of telling whether someone is contagious.
"The majority of time someone is PCR positive, those [genetic] remnants do not indicate transmissible virus," epidemiologist Michael Mina recently Tweeted. "They indicate remnants of a recently cleared infection."
To stop the chain of transmission for COVID-19, he says, "We need a more accurate test than PCR, that turns positive when someone is able to transmit."
In other words, we need a test that is better at detecting whether a person is contagious, as opposed to whether a small amount of virus can be detected in their nose or saliva. This kind of test is especially critical given the research showing that asymptomatic and pre-symptomatic people have high viral loads and are spreading the virus undetected.
The critical question for contagiousness testing, then, is how big a dose of SARS-CoV-2, the virus that causes COVID, does it take to infect most people? Researchers are still actively trying to answer this. As Angela Rasmussen, a coronavirus expert at Columbia University, told STAT: "We don't know the amount that is required to cause an infection, but it seems that it's probably not a really, really small amount, like measles."
Amesh Adalja, an infectious disease physician and a senior scholar at the Johns Hopkins University Center for Health Security, told LeapsMag: "It's still unclear what viral load is associated with contagiousness but it is biologically plausible that higher viral loads, in general, are associated with more efficient transmission especially in symptomatic individuals. In those without symptoms, however, the same relationship may not hold and this may be one of the reasons young children, despite their high viral loads, are not driving outbreaks."
"Antigen tests work best when there's high viral loads. They're catching people who are super spreaders."
Mina and colleagues estimate that widespread use of weekly cheap, rapid tests that are 100 times less sensitive than PCR tests would prevent outbreaks -- as long as the people who are positive self-isolate.
So why can't we buy e25Bio's test at a drugstore right now? Ironically, it's barred for the very reason that it's useful in the first place: Because it is not sensitive enough to satisfy the U.S. Food and Drug Administration, according to the company.
"We're ready to go," says Carlos-Henri Ferré, senior associate of operations and communications at e25. "We've applied to FDA, and now it's in their hands."
The problem, he said, is that the FDA is evaluating applications for antigen tests based on criteria for assessing diagnostics, like PCR, even when the tests serve a different purpose -- as a screening tool.
"Antigen tests work best when there's high viral loads," Ferré says. "They're catching people who are super spreaders, that are capable of continuing the spread of disease … FDA criteria is for diagnostics and not this."
FDA released guidance on July 29th -- 140 days into the pandemic -- recommending that at-home tests should perform with at least 80 percent sensitivity if ordered by prescription, and at least 90 percent sensitivity if purchased over the counter. "The danger of a false negative result is that it can contribute to the spread of COVID-19," according to an FDA spokesperson. "However, oversight of a health care professional who reviews the results, in combination with the patient's symptoms and uses their clinical judgment to recommend additional testing, if needed, among other things, can help mitigate some risks."
Crucially, the 90 percent sensitivity recommendation is judged upon comparison to PCR tests, meaning that if a PCR test is able to detect virus in 100 samples, the at-home antigen test would need to detect virus in at least 90 of those samples. Since antigen tests only detect high viral loads, frustrated critics like Mina say that such guidance is "unreasonable."
"The FDA at this moment is not understanding the true potential for wide-scale frequent testing. In some ways this is not their fault," Mina told LeapsMag. "The FDA does not have any remit to evaluate tests that fall outside of medical diagnostic testing. The proposal I have put forth is not about diagnostic testing (leave that for symptomatic cases reporting to their physician and getting PCR tests)....Daily rapid tests are not about diagnosing people and they are not about public health surveillance and they are not about passports to go to school, out to dinner or into the office. They are about reducing population-level transmission given a similar approach as vaccines."
A reasonable standard, he added, would be to follow the World Health Organization's Target Product Profiles, which are documents to help developers build desirable and minimally acceptable testing products. "A decent limit," Mina says, "is a 70% or 80% sensitivity (if they truly require sensitivity as a metric) to detect virus at Ct values less than 25. This coincides with detection of the most transmissible people, which is important."
(A Ct value is a type of measurement that corresponds inversely to the amount of viral load in a given sample. Researchers have found that Ct values of 13-17 indicate high viral load, whereas Ct values greater than 34 indicate a lack of infectious virus.)
"We believe this should be an at-home test, but [if FDA approval comes through] the first rollout is to do this in laboratories, hospitals, and clinics."
"We believe that population screening devices have an immediate place and use in helping beat the virus," says Ferré. "You can have a significant impact even with a test at 60% sensitivity if you are testing frequently."
When presented with criticism of its recommendations, the FDA indicated that it will not automatically deny any at-home test that fails to meet the 90 percent sensitivity guidance.
"FDA is always open to alternative proposals from developers, including strategies for serial testing with less sensitive tests," a spokesperson wrote in a statement. "For example, it is possible that overall sensitivity of the strategy could be considered cumulatively rather than based on one-time testing….In the case of a manufacturer with an at-home test that can only detect people with COVID-19 when they have a high viral load, we encourage them to talk with us so we can better understand their test, how they propose to use it, and the validation data they have collected to support that use."
However, the FDA's actions so far conflict with its stated openness. e25 ended up adding a step to the protocol in order to better meet FDA standards for sensitivity, but that extra step—sending samples to a laboratory for results—will undercut the test's ability to work as an at-home screening tool.
"We believe this should be an at-home test, but [if FDA approval comes through] the first rollout is to do this in laboratories, hospitals, and clinics," Ferré says.
According to the FDA, no test developers have approached them with a request for an emergency use authorization that proposes an alternate testing paradigm, such as serial testing, to mitigate test sensitivity below 80 percent.
From a scientific perspective, antigen tests like e25Bio's are not the only horse in the race for a simple rapid test with potential for at-home use. CRISPR technology has long been touted as fertile ground for diagnostics, and in an eerily prescient interview with LeapsMag in November, CRISPR pioneer Feng Zhang spoke of its potential application as an at-home diagnostic for an infectious disease specifically.
"I think in the long run it will be great to see this for, say, at-home disease testing, for influenza and other sorts of important public health [concerns]," he said in the fall. "To be able to get a readout at home, people can potentially quarantine themselves rather than traveling to a hospital and then carrying the risk of spreading that disease to other people as they get to the clinic."
Zhang's company Sherlock Biosciences is now working on scaled-up manufacturing of a test to detect SARS CoV-2. Mammoth Biosciences, which secured funding from the National Institutes of Health's Rapid Acceleration of Diagnostics program, is also working on a CRISPR diagnostic for SARS CoV-2. Both would check the box for rapid testing, but so far not for at-home testing, as they would also require laboratory infrastructure to provide results.
If any at-home tests can clear the regulatory hurdles, they would also need to be manufactured on a large scale and be cheap enough to entice people to actually use them. In the world of at-home diagnostics, pregnancy tests have become the sole mainstream victor because they're simple to use, small to carry, easy to interpret, and costs about seven or eight dollars at any ubiquitous store, like Target or Walmart. By comparison, the at-home COVID collection tests that don't even offer diagnostics—you send away your sample to an external lab—all cost over $100 to take just one time.
For the time being, the only available diagnostics for COVID require a lab or an expensive dedicated machine to process. This disconnect could prolong the world's worst health crisis in a century.
"Daily rapid tests have enormous potential to sever transmission chains and create herd effects similar to herd immunity," Mina says. "We all recognize that vaccines and infections can result in herd immunity when something around half of people are no longer susceptible.
"The same thing exists with these tests. These are the intervention to stop the virus. If half of people choose to use these tests every other day, then we can stop transmission faster than a vaccine can. The technology exists, the theory and mathematics back it up, the epidemiology is sound. There is no reason we are not approaching this as strongly as we would be approaching vaccines."
--Additional reporting by Julia Sklar
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
A new type of cancer therapy is shrinking deadly brain tumors with just one treatment
Few cancers are deadlier than glioblastomas—aggressive and lethal tumors that originate in the brain or spinal cord. Five years after diagnosis, less than five percent of glioblastoma patients are still alive—and more often, glioblastoma patients live just 14 months on average after receiving a diagnosis.
But an ongoing clinical trial at Mass General Cancer Center is giving new hope to glioblastoma patients and their families. The trial, called INCIPIENT, is meant to evaluate the effects of a special type of immune cell, called CAR-T cells, on patients with recurrent glioblastoma.
How CAR-T cell therapy works
CAR-T cell therapy is a type of cancer treatment called immunotherapy, where doctors modify a patient’s own immune system specifically to find and destroy cancer cells. In CAR-T cell therapy, doctors extract the patient’s T-cells, which are immune system cells that help fight off disease—particularly cancer. These T-cells are harvested from the patient and then genetically modified in a lab to produce proteins on their surface called chimeric antigen receptors (thus becoming CAR-T cells), which makes them able to bind to a specific protein on the patient’s cancer cells. Once modified, these CAR-T cells are grown in the lab for several weeks so that they can multiply into an army of millions. When enough cells have been grown, these super-charged T-cells are infused back into the patient where they can then seek out cancer cells, bind to them, and destroy them. CAR-T cell therapies have been approved by the US Food and Drug Administration (FDA) to treat certain types of lymphomas and leukemias, as well as multiple myeloma, but haven’t been approved to treat glioblastomas—yet.
CAR-T cell therapies don’t always work against solid tumors, such as glioblastomas. Because solid tumors contain different kinds of cancer cells, some cells can evade the immune system’s detection even after CAR-T cell therapy, according to a press release from Massachusetts General Hospital. For the INCIPIENT trial, researchers modified the CAR-T cells even further in hopes of making them more effective against solid tumors. These second-generation CAR-T cells (called CARv3-TEAM-E T cells) contain special antibodies that attack EFGR, a protein expressed in the majority of glioblastoma tumors. Unlike other CAR-T cell therapies, these particular CAR-T cells were designed to be directly injected into the patient’s brain.
The INCIPIENT trial results
The INCIPIENT trial involved three patients who were enrolled in the study between March and July 2023. All three patients—a 72-year-old man, a 74-year-old man, and a 57-year-old woman—were treated with chemo and radiation and enrolled in the trial with CAR-T cells after their glioblastoma tumors came back.
The results, which were published earlier this year in the New England Journal of Medicine (NEJM), were called “rapid” and “dramatic” by doctors involved in the trial. After just a single infusion of the CAR-T cells, each patient experienced a significant reduction in their tumor sizes. Just two days after receiving the infusion, the glioblastoma tumor of the 72-year-old man decreased by nearly twenty percent. Just two months later the tumor had shrunk by an astonishing 60 percent, and the change was maintained for more than six months. The most dramatic result was in the 57-year-old female patient, whose tumor shrank nearly completely after just one infusion of the CAR-T cells.
The results of the INCIPIENT trial were unexpected and astonishing—but unfortunately, they were also temporary. For all three patients, the tumors eventually began to grow back regardless of the CAR-T cell infusions. According to the press release from MGH, the medical team is now considering treating each patient with multiple infusions or prefacing each treatment with chemotherapy to prolong the response.
While there is still “more to do,” says co-author of the study neuro-oncologist Dr. Elizabeth Gerstner, the results are still promising. If nothing else, these second-generation CAR-T cell infusions may someday be able to give patients more time than traditional treatments would allow.
“These results are exciting but they are also just the beginning,” says Dr. Marcela Maus, a doctor and professor of medicine at Mass General who was involved in the clinical trial. “They tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease.”
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.