Can Radical Transparency Overcome Resistance to COVID-19 Vaccines?
When historians look back on the COVID-19 pandemic, they may mark November 9, 2020 as the day the tide began to turn. That's when the New York-based pharmaceutical giant Pfizer announced that clinical trials showed its experimental vaccine, developed with the German firm BioNTech, to be 90 percent effective in preventing the disease.
A week later, Massachusetts biotech startup Moderna declared its vaccine to be 95 percent effective. By early December, Great Britain had begun mass inoculations, followed—once the Food and Drug Administration gave the thumbs-up—by the United States. In this scenario, the worst global health crisis in a century was on the cusp of resolution.
Yet future chroniclers may instead peg November 9 as the day false hope dawned. That could happen if serious safety issues, undetected so far, arise after millions of doses are administered. Experts consider it unlikely, however, that such problems alone (as opposed to the panic they might spark) would affect enough people to thwart a victory over the coronavirus. A more immediate obstacle is vaccine hesitancy—the prospect that much of the populace will refuse to roll up their sleeves.
To achieve "herd immunity" for COVID-19 (the point at which a vaccine reduces transmission rates enough to protect those who can't or won't take it, or for whom it doesn't work), epidemiologists estimate that up to 85 percent of the population will have to be vaccinated. Alarmingly, polls suggest that 40 to 50 percent of Americans intend to decline, judging the risks to be more worrisome than those posed by the coronavirus itself.
COVID vaccine skeptics occupy various positions on a spectrum of doubt. Some are committed anti-vaxxers, or devotees of conspiracy theories that view the pandemic as a hoax. Others belong to minority groups that have historically been used as guinea pigs in unethical medical research (for horrific examples, Google "Tuskegee syphilis experiment" or "Henrietta Lacks"). Still others simply mistrust Big Pharma and/or Big Government. A common fear is that the scramble to find a vaccine—intensified by partisan and profit motives—has led to corner-cutting in the testing and approval process. "They really rushed," an Iowa trucker told The Washington Post. "I'll probably wait a couple of months after they start to see how everyone else is handling it."
The COVID crisis has spurred calls for secretive Data Safety and Monitoring Boards to come out of the shadows.
The consensus among scientists, by contrast, is that the process has been rigorous enough, given the exigency of the situation, that the public can feel reasonably confident in any vaccine that has earned the imprimatur of the FDA. For those of us who share that assessment, finding ways to reassure the hesitant-but-persuadable is an urgent matter.
Vax-positive public health messaging is one obvious tactic, but a growing number of experts say it's not enough. They prescribe a regimen of radical transparency throughout the system that regulates research—in particular, regarding the secretive panels that oversee vaccine trials.
The Crucial Role of the Little-Known Panels
Like other large clinical trials involving potentially high-demand or controversial products, studies of COVID-19 vaccines in most countries are supervised by groups of independent observers. Known in the United States as data safety and monitoring boards (DSMBs), and elsewhere as data monitoring committees, these panels consist of scientists, clinicians, statisticians, and other authorities with no ties to the sponsor of the study.
The six trials funded by the federal program known as Operation Warp Speed (including those of newly approved Moderna and frontrunner AstraZeneca) share a DSMB, whose members are selected by the National Institutes of Health; other companies (including Pfizer) appoint their own. The panel's job is to monitor the safety and efficacy of a treatment while the trial is ongoing, and to ensure that data is being collected and analyzed correctly.
Vaccine studies are "double-blinded," which means neither the participants nor the doctors running the trial know who's getting the real thing and who's getting a placebo. But the DSMB can access that information if a study volunteer has what might be a serious side effect—and if the participant was in the vaccine group, the board can ask that the trial be paused for further investigation.
The DSMB also checks for efficacy at pre-determined intervals. If it finds that the vaccine group and the placebo group are getting sick at similar rates, the panel can recommend stopping the trial due to "futility." And if the results look overwhelmingly positive, the DSMB can recommend that the study sponsor apply for FDA approval before the scheduled end of the trial, in order to hurry the product to market.
With this kind of inside dope and high-level influence, DSMBs could easily become targets for outside pressure. That's why, since the 1980s, their membership has typically been kept secret.
During the early days of the AIDS crisis, researchers working on HIV drugs feared for the safety of the experts on their boards. "They didn't want them to be besieged and harassed by members of the community," explains Susan Ellenberg, a professor of biostatistics, medical ethics and health policy at the University of Pennsylvania, and co-author of Data Monitoring Committees in Clinical Trials, the DSMB bible. "You can understand why people would very much want to know how things were looking in a given trial. They wanted to save their own lives; they wanted to save their friends' lives." Ellenberg, who was founding director of the biostatistics branch of the AIDS division at the National Institute of Allergy and Infectious Diseases (NIAID), helped shape a range of policies designed to ensure that DSMBs made decisions based on data and nothing else.
Confidentiality also shields DSMB members from badgering by patient advocacy groups, who might urge that a drug be presented for approval before trial results are conclusive, or by profit-hungry investors. "It prevents people from trying to pry out information to get an edge in the stock market," says Art Caplan, a bioethicist at New York University.
Yet the COVID crisis has spurred calls for DSMBs to come out of the shadows. One triggering event came in March 2020, when the FDA approved hydroxychloroquine for COVID-19—a therapy that President Donald J. Trump touted, despite scant evidence for its efficacy. (Approval was rescinded in June.) If the agency could bow to political pressure on these medications, critics warned, it might do so with vaccines as well. In the end, that didn't happen; the Pfizer approval was issued well after Election Day, despite Trump's goading, and most experts agree that it was based on solid science. Still, public suspicion lingers.
Another shock came in September, after British-based AstraZeneca announced it was pausing its vaccine trial globally due to a "suspected adverse rection" in a volunteer. The company shared no details with the press. Instead, AstraZeneca's CEO divulged them in a private call with J.P. Morgan investors the next day, confirming that the volunteer was suffering from transverse myelitis, a rare and serious spinal inflammation—and that the study had also been halted in July, when another volunteer displayed neurological symptoms. STAT News broke the story after talking to tipsters.
Although both illnesses were found to be unrelated to the vaccine, and the trial was restarted, the incident had a paradoxical effect: while it confirmed for experts that the oversight system was working, AstraZeneca's initial lack of candor added to many laypeople's sense that it wasn't. "If you were seeking to undermine trust, that's kind of how you would go about doing it," says Charles Weijer, a bioethicist at Western University in Ontario, who has helped develop clinical trial guidelines for the World Health Organization.
Both Caplan and Weijer have served on many DSMBs; they believe the boards are generally trustworthy, and that those overseeing COVID vaccine trials are performing their jobs well. But the secrecy surrounding these groups, they and others argue, has become counterproductive. Shining a light on the statistical sausage-makers would help dispel doubts about the finished product.
"I'm not suggesting that any of these companies are doing things unethically," Weijer explains. "But the circumstances of a global pandemic are sufficiently challenging that perhaps they ought to be doing some things differently. I believe it would be trust-producing for data monitoring committees to be more forthcoming than usual."
Building Trust: More Transparency
Just how forthcoming is a matter of debate. Caplan suggests that each COVID vaccine DSMB reveal the name of its chair; that would enable the scientific community, as well as the media and the general public, to get a sense of the integrity and qualifications of the board as a whole while preserving the anonymity of the other members.
Indeed, when Operation Warp Speed's DSMB chair, Richard Whitley, was outed through a website slip-up, many observers applauded his selection for the role; a professor of pediatrics, microbiology, medicine and neurosurgery at the University of Alabama at Birmingham, he is "an exceptionally experienced and qualified individual," Weijer says. (Reporters with ProPublica later identified two other members: Susan Ellenberg and immunologist William Makgoba, known for his work on the South African AIDS Vaccine Initiative.)
Caplan would also like to see more details of the protocols DSMBs are using to make decisions, such as the statistical threshold for efficacy that would lead them to seek approval from the FDA. And he wishes the NIH would spell out specific responsibilities for these monitoring boards. "They don't really have clear, government-mandated charters," he notes. For example, there's no requirement that DSMBs include an ethicist or patient advocate—both of which Caplan considers essential for vaccine trials. "Rough guidelines," he says, "would be useful."
Weijer, for his part, thinks DSMBs should disclose all their members. "When you only disclose the chair, you leave questions unanswered," he says. "What expertise do [the others] bring to the table? Are they similarly free of relevant conflicts of interest? And it doesn't answer the question that will be foremost on many people's minds: are these people in the pocket of pharma?"
Weijer and Caplan both want to see greater transparency around the trial results themselves. Because the FDA approved the Pfizer and Moderna vaccines with emergency use authorizations rather than full licensure, which requires more extensive safety testing, these products reached the market without the usual paper trail of peer-reviewed publications. The same will likely be true of any future COVID vaccines that the agency greenlights. To add another level of scrutiny, both ethicists suggest, each company should publicly release its data at the end of a trial. "That offers the potential for academic groups to go in and do an analysis," Weijer explains, "to verify the claims about the safety and efficacy of the vaccine." The point, he says, is not only to ensure that the approval was justified, but to provide evidence to counter skeptics' qualms.
Caplan may differ on some of the details, but he endorses the premise. "It's all a matter of trust," he says. "You're always watching that, because a vaccine is only as good as the number of people who take it."
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.