How Excessive Regulation Helped Ignite COVID-19's Rampant Spread
When historians of the future look back at the 2020 pandemic, the heroic work of Helen Y. Chu, a flu researcher at the University of Washington, will be worthy of recognition.
Chu's team bravely defied the order and conducted the testing anyway.
In late January, Chu was testing nasal swabs for the Seattle Flu Study to monitor influenza spread when she learned of the first case of COVID-19 in Washington state. She deemed it a pressing public health matter to document if and how the illness was spreading locally, so that early containment efforts could succeed. So she sought regulatory approval to adapt the Flu Study to test for the coronavirus, but the federal government denied the request because the original project was funded to study only influenza.
Aware of the urgency, Chu's team bravely defied the order and conducted the testing anyway. Soon they identified a local case in a teenager without any travel history, followed by others. Still, the government tried to shutter their efforts until the outbreak grew dangerous enough to command attention.
Needless testing delays, prompted by excessive regulatory interference, eliminated any chances of curbing the pandemic at its initial stages. Even after Chu went out on a limb to sound alarms, a heavy-handed bureaucracy crushed the nation's ability to roll out early and widespread testing across the country. The Centers for Disease Control and Prevention infamously blundered its own test, while also impeding state and private labs from coming on board, fueling a massive shortage.
The long holdup created "a backlog of testing that needed to be done," says Amesh Adalja, an infectious disease specialist who is a senior scholar at the Johns Hopkins University Center for Health Security.
In a public health crisis, "the ideal situation" would allow the government's test to be "supplanted by private laboratories" without such "a lag in that transition," Adalja says. Only after the eventual release of CDC's test could private industry "begin in earnest" to develop its own versions under the Food and Drug Administration's emergency use authorization.
In a statement, CDC acknowledged that "this process has not gone as smoothly as we would have liked, but there is currently no backlog for testing at CDC."
Now, universities and corporations are in a race against time, playing catch up as the virus continues its relentless spread, also afflicting many health care workers on the front lines.
"Home-testing accessibility is key to preventing further spread of the COVID-19 pandemic."
Hospitals are attempting to add the novel coronavirus to the testing panel of their existent diagnostic machines, which would reduce the results processing time from 48 hours to as little as four hours. Meanwhile, at least four companies announced plans to deliver at-home collection tests to help meet the demand – before a startling injunction by the FDA halted their plans.
Everlywell, an Austin, Texas-based digital health company, had been set to launch online sales of at-home collection kits directly to consumers last week. Scaling up in a matter of days to an initial supply of 30,000 tests, Everlywell collaborated with multiple laboratories where consumers could ship their nasal swab samples overnight, projecting capacity to screen a quarter-million individuals on a weekly basis, says Frank Ong, chief medical and scientific officer.
Secure digital results would have been available online within 48 hours of a sample's arrival at the lab, as well as a telehealth consultation with an independent, board-certified doctor if someone tested positive, for an inclusive $135 cost. The test has a less than 3 percent false-negative rate, Ong says, and in the event of an inadequate self-swab, the lab would not report a conclusive finding. "Home-testing accessibility," he says, "is key to preventing further spread of the COVID-19 pandemic."
But on March 20, the FDA announced restrictions on home collection tests due to concerns about accuracy. The agency did note "the public health value in expanding the availability of COVID-19 testing through safe and accurate tests that may include home collection," while adding that "we are actively working with test developers in this space."
After the restrictions were announced, Everlywell decided to allocate its initial supply of COVID-19 collection kits to hospitals, clinics, nursing homes, and other qualifying health care companies that can commit to no-cost screening of frontline workers and high-risk symptomatic patients. For now, no consumers can order a home-collection test.
"Losing two months is close to disastrous, and that's what we did."
Currently, the U.S. has ramped up to testing an estimated 100,000 people a day, according to Stat News. But 150,000 or more Americans should be tested every day, says Ashish Jha, professor and director of the Harvard Global Health Institute. Due to the dearth of tests, many sick people who suspect they are infected still cannot get confirmation unless they need to be hospitalized.
To give a concrete sense of how far behind we are in testing, consider Palm Beach County, Fla. The state's only drive-thru test center just opened there, requiring an appointment. The center aims to test 750 people per day, but more than 330,000 people have already called to try to book a slot.
"This is such a rapidly moving infection that losing a few days is bad, and losing a couple of weeks is terrible," says Jha, a practicing general internist. "Losing two months is close to disastrous, and that's what we did."
At this point, it will take a long time to fully ramp up. "We are blindfolded," he adds, "and I'd like to take the blindfolds off so we can fight this battle with our eyes wide open."
Better late than never: Yesterday, FDA Commissioner Stephen Hahn said in a statement that the agency has worked with more than 230 test developers and has approved 20 tests since January. An especially notable one was authorized last Friday – 67 days since the country's first known case in Washington state. It's a rapid point-of-care test from medical-device firm Abbott that provides positive results in five minutes and negative results in 13 minutes. Abbott will send 50,000 tests a day to urgent care settings. The first tests are expected to ship tomorrow.
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.