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."
Awash in a fluid finely calibrated to keep it alive, a human eye rests inside a transparent cubic device. This ECaBox, or Eyes in a Care Box, is a one-of-a-kind system built by scientists at Barcelona’s Centre for Genomic Regulation (CRG). Their goal is to preserve human eyes for transplantation and related research.
In recent years, scientists have learned to transplant delicate organs such as the liver, lungs or pancreas, but eyes are another story. Even when preserved at the average transplant temperature of 4 Centigrade, they last for 48 hours max. That's one explanation for why transplanting the whole eye isn’t possible—only the cornea, the dome-shaped, outer layer of the eye, can withstand the procedure. The retina, the layer at the back of the eyeball that turns light into electrical signals, which the brain converts into images, is extremely difficult to transplant because it's packed with nerve tissue and blood vessels.
These challenges also make it tough to research transplantation. “This greatly limits their use for experiments, particularly when it comes to the effectiveness of new drugs and treatments,” said Maria Pia Cosma, a biologist at Barcelona’s Centre for Genomic Regulation (CRG), whose team is working on the ECaBox.
Eye transplants are desperately needed, but they're nowhere in sight. About 12.7 million people worldwide need a corneal transplant, which means that only one in 70 people who require them, get them. The gaps are international. Eye banks in the United Kingdom are around 20 percent below the level needed to supply hospitals, while Indian eye banks, which need at least 250,000 corneas per year, collect only around 45 to 50 thousand donor corneas (and of those 60 to 70 percent are successfully transplanted).
As for retinas, it's impossible currently to put one into the eye of another person. Artificial devices can be implanted to restore the sight of patients suffering from severe retinal diseases, but the number of people around the world with such “bionic eyes” is less than 600, while in America alone 11 million people have some type of retinal disease leading to severe vision loss. Add to this an increasingly aging population, commonly facing various vision impairments, and you have a recipe for heavy burdens on individuals, the economy and society. In the U.S. alone, the total annual economic impact of vision problems was $51.4 billion in 2017.
Even if you try growing tissues in the petri dish route into organoids mimicking the function of the human eye, you will not get the physiological complexity of the structure and metabolism of the real thing, according to Cosma. She is a member of a scientific consortium that includes researchers from major institutions from Spain, the U.K., Portugal, Italy and Israel. The consortium has received about $3.8 million from the European Union to pursue innovative eye research. Her team’s goal is to give hope to at least 2.2 billion people across the world afflicted with a vision impairment and 33 million who go through life with avoidable blindness.
Their method? Resuscitating cadaveric eyes for at least a month.
If we succeed, it will be the first intact human model of the eye capable of exploring and analyzing regenerative processes ex vivo. -- Maria Pia Cosma.
“We proposed to resuscitate eyes, that is to restore the global physiology and function of human explanted tissues,” Cosma said, referring to living tissues extracted from the eye and placed in a medium for culture. Their ECaBox is an ex vivo biological system, in which eyes taken from dead donors are placed in an artificial environment, designed to preserve the eye’s temperature and pH levels, deter blood clots, and remove the metabolic waste and toxins that would otherwise spell their demise.
Scientists work on resuscitating eyes in the lab of Maria Pia Cosma.
Courtesy of Maria Pia Cosma.
“One of the great challenges is the passage of the blood in the capillary branches of the eye, what we call long-term perfusion,” Cosma said. Capillaries are an intricate network of very thin blood vessels that transport blood, nutrients and oxygen to cells in the body’s organs and systems. To maintain the garland-shaped structure of this network, sufficient amounts of oxygen and nutrients must be provided through the eye circulation and microcirculation. “Our ambition is to combine perfusion of the vessels with artificial blood," along with using a synthetic form of vitreous, or the gel-like fluid that lets in light and supports the the eye's round shape, Cosma said.
The scientists use this novel setup with the eye submersed in its medium to keep the organ viable, so they can test retinal function. “If we succeed, we will ensure full functionality of a human organ ex vivo. It will be the first intact human model of the eye capable of exploring and analyzing regenerative processes ex vivo,” Cosma added.
A rapidly developing field of regenerative medicine aims to stimulate the body's natural healing processes and restore or replace damaged tissues and organs. But for people with retinal diseases, regenerative medicine progress has been painfully slow. “Experiments on rodents show progress, but the risks for humans are unacceptable,” Cosma said.
The ECaBox could boost progress with regenerative medicine for people with retinal diseases, which has been painfully slow because human experiments involving their eyes are too risky. “We will test emerging treatments while reducing animal research, and greatly accelerate the discovery and preclinical research phase of new possible treatments for vision loss at significantly reduced costs,” Cosma explained. Much less time and money would be wasted during the drug discovery process. Their work may even make it possible to transplant the entire eyeball for those who need it.
“It is a very exciting project,” said Sanjay Sharma, a professor of ophthalmology and epidemiology at Queen's University, in Kingston, Canada. “The ability to explore and monitor regenerative interventions will increasingly be of importance as we develop therapies that can regenerate ocular tissues, including the retina.”
Seemingly, there's no sacred religious text or a holy book prohibiting the practice of eye donation.
But is the world ready for eye transplants? “People are a bit weird or very emotional about donating their eyes as compared to other organs,” Cosma said. And much can be said about the problem of eye donor shortage. Concerns include disfigurement and healthcare professionals’ fear that the conversation about eye donation will upset the departed person’s relatives because of cultural or religious considerations. As just one example, Sharma noted the paucity of eye donations in his home country, Canada.
Yet, experts like Sharma stress the importance of these donations for both the recipients and their family members. “It allows them some psychological benefit in a very difficult time,” he said. So why are global eye banks suffering? Is it because the eyes are the windows to the soul?
Seemingly, there's no sacred religious text or a holy book prohibiting the practice of eye donation. In fact, most major religions of the world permit and support organ transplantation and donation, and by extension eye donation, because they unequivocally see it as an “act of neighborly love and charity.” In Hinduism, the concept of eye donation aligns with the Hindu principle of daan or selfless giving, where individuals donate their organs or body after death to benefit others and contribute to society. In Islam, eye donation is a form of sadaqah jariyah, a perpetual charity, as it can continue to benefit others even after the donor's death.
Meanwhile, Buddhist masters teach that donating an organ gives another person the chance to live longer and practice dharma, the universal law and order, more meaningfully; they also dismiss misunderstandings of the type “if you donate an eye, you’ll be born without an eye in the next birth.” And Christian teachings emphasize the values of love, compassion, and selflessness, all compatible with organ donation, eye donation notwithstanding; besides, those that will have a house in heaven, will get a whole new body without imperfections and limitations.
The explanation for people’s resistance may lie in what Deepak Sarma, a professor of Indian religions and philosophy at Case Western Reserve University in Cleveland, calls “street interpretation” of religious or spiritual dogmas. Consider the mechanism of karma, which is about the causal relation between previous and current actions. “Maybe some Hindus believe there is karma in the eyes and, if the eye gets transplanted into another person, they will have to have that karmic card from now on,” Sarma said. “Even if there is peculiar karma due to an untimely death–which might be interpreted by some as bad karma–then you have the karma of the recipient, which is tremendously good karma, because they have access to these body parts, a tremendous gift,” Sarma said. The overall accumulation is that of good karma: “It’s a beautiful kind of balance,” Sarma said.
For the Jews, Christians, and Muslims who believe in the physical resurrection of the body that will be made new in an afterlife, the already existing body is sacred since it will be the basis of a new refashioned body in an afterlife.---Omar Sultan Haque.
With that said, Sarma believes it is a fallacy to personify or anthropomorphize the eye, which doesn’t have a soul, and stresses that the karma attaches itself to the soul and not the body parts. But for scholars like Omar Sultan Haque—a psychiatrist and social scientist at Harvard Medical School, investigating questions across global health, anthropology, social psychology, and bioethics—the hierarchy of sacredness of body parts is entrenched in human psychology. You cannot equate the pinky toe with the face, he explained.
“The eyes are the window to the soul,” Haque said. “People have a hierarchy of body parts that are considered more sacred or essential to the self or soul, such as the eyes, face, and brain.” In his view, the techno-utopian transhumanist communities (especially those in Silicon Valley) have reduced the totality of a person to a mere material object, a “wet robot” that knows no sacredness or hierarchy of human body parts. “But for the Jews, Christians, and Muslims who believe in the physical resurrection of the body that will be made new in an afterlife, the [already existing] body is sacred since it will be the basis of a new refashioned body in an afterlife,” Haque said. “You cannot treat the body like any old material artifact, or old chair or ragged cloth, just because materialistic, secular ideologies want so,” he continued.
For Cosma and her peers, however, the very definition of what is alive or not is a bit semantic. “As soon as we die, the electrophysiological activity in the eye stops,” she said. “The goal of the project is to restore this activity as soon as possible before the highly complex tissue of the eye starts degrading.” Cosma’s group doesn’t yet know when they will be able to keep the eyes alive and well in the ECaBox, but the consensus is that the sooner the better. Hopefully, the taboos and fears around the eye donations will dissipate around the same time.
As Our AI Systems Get Better, So Must We
As the power and capability of our AI systems increase by the day, the essential question we now face is what constitutes peak human. If we stay where we are while the AI systems we are unleashing continually get better, they will meet and then exceed our capabilities in an ever-growing number of domains. But while some technology visionaries like Elon Musk call for us to slow down the development of AI systems to buy time, this approach alone will simply not work in our hyper-competitive world, particularly when the potential benefits of AI are so great and our frameworks for global governance are so weak. In order to build the future we want, we must also become ever better humans.
The list of activities we once saw as uniquely human where AIs have now surpassed us is long and growing. First, AI systems could beat our best chess players, then our best Go players, then our best champions of multi-player poker. They can see patterns far better than we can, generate medical and other hypotheses most human specialists miss, predict and map out new cellular structures, and even generate beautiful, and, yes, creative, art.
A recent paper by Microsoft researchers analyzing the significant leap in capabilities in OpenAI’s latest AI bot, ChatGPT-4, asserted that the algorithm can “solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting.” Calling this functionality “strikingly close to human-level performance,” the authors conclude it “could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system.”
The concept of AGI has been around for decades. In its common use, the term suggests a time when individual machines can do many different things at a human level, not just one thing like playing Go or analyzing radiological images. Debating when AGI might arrive, a favorite pastime of computer scientists for years, now has become outdated.
We already have AI algorithms and chatbots that can do lots of different things. Based on the generalist definition, in other words, AGI is essentially already here.
Unfettered by the evolved capacity and storage constraints of our brains, AI algorithms can access nearly all of the digitized cultural inheritance of humanity since the dawn of recorded history and have increasing access to growing pools of digitized biological data from across the spectrum of life.
Once we recognize that both AI systems and humans have unique superpowers, the essential question becomes what each of us can do better than the other and what humans and AIs can best do in active collaboration. The future of our species will depend upon our ability to safely, dynamically, and continually figure that out.
With these ever-larger datasets, rapidly increasing computing and memory power, and new and better algorithms, our AI systems will keep getting better faster than most of us can today imagine. These capabilities have the potential to help us radically improve our healthcare, agriculture, and manufacturing, make our economies more productive and our development more sustainable, and do many important things better.
Soon, they will learn how to write their own code. Like human children, in other words, AI systems will grow up. But even that doesn’t mean our human goose is cooked.
Just like dolphins and dogs, these alternate forms of intelligence will be uniquely theirs, not a lesser or greater version of ours. There are lots of things AI systems can't do and will never be able to do because our AI algorithms, for better and for worse, will never be human. Our embodied human intelligence is its own thing.
Our human intelligence is uniquely ours based on the capacities we have developed in our 3.8-billion-year journey from single cell organisms to us. Our brains and bodies represent continuous adaptations on earlier models, which is why our skeletal systems look like those of lizards and our brains like most other mammals with some extra cerebral cortex mixed in. Human intelligence isn’t just some type of disembodied function but the inextricable manifestation of our evolved physical reality. It includes our sensory analytical skills and all of our animal instincts, intuitions, drives, and perceptions. Disembodied machine intelligence is something different than what we have evolved and possess.
Because of this, some linguists including Noam Chomsky have recently argued that AI systems will never be intelligent as long as they are just manipulating symbols and mathematical tokens without any inherent understanding. Nothing could be further from the truth. Anyone interacting with even first-generation AI chatbots quickly realizes that while these systems are far from perfect or omniscient and can sometimes be stupendously oblivious, they are surprisingly smart and versatile and will get more so… forever. We have little idea even how our own minds work, so judging AI systems based on their output is relatively close to how we evaluate ourselves.
Anyone not awed by the potential of these AI systems is missing the point. AI’s newfound capacities demand that we work urgently to establish norms, standards, and regulations at all levels from local to global to manage the very real risks. Pausing our development of AI systems now doesn’t make sense, however, even if it were possible, because we have no sufficient ways of uniformly enacting such a pause, no plan for how we would use the time, and no common framework for addressing global collective challenges like this.
But if all we feel is a passive awe for these new capabilities, we will also be missing the point.
Human evolution, biology, and cultural history are not just some kind of accidental legacy, disability, or parlor trick, but our inherent superpower. Our ancestors outcompeted rivals for billions of years to make us so well suited to the world we inhabit and helped build. Our social organization at scale has made it possible for us to forge civilizations of immense complexity, engineer biology and novel intelligence, and extend our reach to the stars. Our messy, embodied, intuitive, social human intelligence is roughly mimicable by AI systems but, by definition, never fully replicable by them.
Once we recognize that both AI systems and humans have unique superpowers, the essential question becomes what each of us can do better than the other and what humans and AIs can best do in active collaboration. We still don't know. The future of our species will depend upon our ability to safely, dynamically, and continually figure that out.
As we do, we'll learn that many of our ideas and actions are made up of parts, some of which will prove essentially human and some of which can be better achieved by AI systems. Those in every walk of work and life who most successfully identify the optimal contributions of humans, AIs, and the two together, and who build systems and workflows empowering humans to do human things, machines to do machine things, and humans and machines to work together in ways maximizing the respective strengths of each, will be the champions of the 21st century across all fields.
The dawn of the age of machine intelligence is upon us. It’s a quantum leap equivalent to the domestication of plants and animals, industrialization, electrification, and computing. Each of these revolutions forced us to rethink what it means to be human, how we live, and how we organize ourselves. The AI revolution will happen more suddenly than these earlier transformations but will follow the same general trajectory. Now is the time to aggressively prepare for what is fast heading our way, including by active public engagement, governance, and regulation.
AI systems will not replace us, but, like these earlier technology-driven revolutions, they will force us to become different humans as we co-evolve with our technology. We will never reach peak human in our ongoing evolutionary journey, but we’ve got to manage this transition wisely to build the type of future we’d like to inhabit.
Alongside our ascending AIs, we humans still have a lot of climbing to do.