Medical Breakthroughs Set to be Fast-Tracked by Innovative New Health Agency
In 2007, Matthew Might's son, Bertrand, was born with a life-threatening disease that was so rare, doctors couldn't diagnose it. Might, a computer scientist and biologist, eventually realized, "Oh my gosh, he's the only patient in the world with this disease right now." To find effective treatments, new methodologies would need to be developed. But there was no process or playbook for doing that.
Might took it upon himself, along with a team of specialists, to try to find a cure. "What Bertrand really taught me was the visceral sense of urgency when there's suffering, and how to act on that," he said.
He calls it "the agency of urgency"—and patients with more common diseases, such as cancer and Alzheimer's, often feel that same need to take matters into their own hands, as they find their hopes for new treatments running up against bureaucratic systems designed to advance in small, steady steps, not leaps and bounds. "We all hope for a cure," said Florence "Pippy" Rogers, a 65-year-old volunteer with Georgia's chapter of the Alzheimer's Association. She lost her mother to the disease and, these days, worries about herself and her four siblings. "We need to keep accelerating research."
We have a fresh example of what can be achieved by fast-tracking discoveries in healthcare: Covid-19 vaccines.
President Biden has pushed for cancer moonshots since the disease took the life of his son, Beau, in 2015. His administration has now requested $6.5 billion to start a new agency in 2022, called the Advanced Research Projects Agency for Health, or ARPA-H, within the National Institutes of Health. It's based on DARPA, the Department of Defense agency known for hatching world-changing technologies such as drones, GPS and ARPANET, which became the internet.
We have a fresh example of what can be achieved by fast-tracking discoveries in healthcare: Covid-19 vaccines. "Operation Warp Speed was using ARPA-like principles," said Might. "It showed that in a moment of crisis, institutions like NIH can think in an ARPA-like way. So now the question is, why don't we do that all the time?"
But applying the DARPA model to health involves several challenging decisions. I asked experts what could be the hardest question facing advocates of ARPA-H: which health problems it should seek to address. "All the wonderful choices lead to the problem of which ones to choose and prioritize," said Sudip Parikh, CEO of the American Association for the Advancement of Science and executive publisher of the Science family of journals. "There is no objectively right answer."
The Agency of Urgency
ARPA-H will borrow at least three critical ingredients from DARPA: goal-oriented project managers, many from industry; aggressive public-private partnerships; and collaboration among fields that don't always interact. The DARPA concept has been applied to other purposes, including energy and homeland security, with promising results. "We're learning that 'ARPA-ism' is a franchisable model," said Might, a former principal investigator on DARPA projects.
The federal government already pours billions of dollars into advancing research on life-threatening diseases, with much of it channeled through the National Institutes of Health. But the purpose of ARPA-H "isn't just the usual suspects that NIH would fund," said David Walt, a Harvard biochemist, an innovator in gene sequencing and former chair of DARPA's Defense Science Research Council. Whereas some NIH-funded studies aim to gradually improve our understanding of diseases, ARPA-H projects will give full focus to real-world applications; they'll use essential findings from NIH research as starting points, drawing from them to rapidly engineer new technologies that could save lives.
And, ultimately, billions in healthcare costs, if ARPA-H lives up to its predecessor's track record; DARPA's breakthroughs have been economic game-changers, while its fail-fast approach—quickly pulling the plug on projects that aren't panning out—helps to avoid sunken costs. ARPA-H could fuel activities similar to the human genome project, which used existing research to map the base pairs that make up DNA, opening new doors for the biotech industry, sparking economic growth and creating hundreds of thousands of new jobs.
Despite a nearly $4 trillion health economy, "we aren't innovating when it comes to technological capabilities for health," said Liz Feld, president of the Suzanne Wright Foundation for pancreatic cancer.
Individual Diseases Ripe for Innovation
Although the need for innovation is clear, which diseases ARPA-H should tackle is less apparent. One important consideration when choosing health priorities could be "how many people suffer from a disease," said Nancy Kass, a professor of bioethics and public health at Johns Hopkins.
That perspective could justify cancer as a top objective. Cancer and heart disease have long been the two major killers in the U.S. Leonidas Platanias, professor of oncology at Northwestern and director of its cancer center, noted that we've already made significant progress on heart disease. "Anti-cholesterol drugs really have a wide impact," he said. "I don't want to compare one disease to another, but I think cancer may be the most challenging. We need even bigger breakthroughs." He wondered whether ARPA-H should be linked to the part of NIH dedicated to cancer, the National Cancer Institute, "to take maximum advantage of what happens" there.
Previous cancer moonshots have laid a foundation for success. And this sort of disease-by-disease approach makes sense in a way. "We know that concentrating on some diseases has led to treatments," said Parikh. "Think of spinal muscular atrophy or cystic fibrosis. Now, imagine if immune therapies were discovered ten years earlier."
But many advocates think ARPA-H should choose projects that don't revolve around any one disease. "It absolutely has to be disease agnostic," said Feld, president of the pancreatic cancer foundation. "We cannot reach ARPA-H's potential if it's subject to the advocacy of individual patient groups who think their disease is worse than the guy's disease next to them. That's not the way the DARPA model works." Platanias agreed that ARPA-H should "pick the highest concepts and developments that have the best chance" of success.
Finding Connections Between Diseases
Kass, the Hopkins bioethicist, believes that ARPA-H should walk a balance, with some projects focusing on specific diseases and others aspiring to solutions with broader applications, spanning multiple diseases. Being impartial, some have noted, might involve looking at the total "life years" saved by a health innovation; the more diseases addressed by a given breakthrough, the more years of healthy living it may confer. The social and economic value should increase as well.
For multiple payoffs, ARPA-H could concentrate on rare diseases, which can yield important insights for many other diseases, said Might. Every case of cancer and Alzheimer's is, in a way, its own rare disease. Cancer is a genetic disease, like his son Bertrand's rare disorder, and mutations vary widely across cancer patients. "It's safe to say that no two people have ever actually had the same cancer," said Might. In theory, solutions for rare diseases could help us understand how to individualize treatments for more common diseases.
Many experts I talked with support another priority for ARPA-H with implications for multiple diseases: therapies that slow down the aging process. "Aging is the greatest risk factor for every major disease that NIH is studying," said Matt Kaeberlein, a bio-gerontologist at the University of Washington. Yet, "half of one percent of the NIH budget goes to researching the biology of aging. An ARPA-H sized budget would push the field forward at a pace that's hard to imagine."
Might agreed. "It could take ARPA-H to get past the weird stigmas around aging-related research. It could have a tremendous impact on the field."
For example, ARPA-H could try to use mRNA technology to express proteins that affect biological aging, said Kaeberlein. It's an engineering project well-suited to the DARPA model. So is harnessing machine learning to identify biomarkers that assess how fast people are aging. Biological aging clocks, if validated, could quickly reveal whether proposed therapies for aging are working or not. "I think there's huge value in that," said Kaeberlein.
By delivering breakthroughs in computation, ARPA-H could improve diagnostics for many different diseases. That could include improving biowearables for continuously monitoring blood pressure—a hypothetical mentioned in the White House's concept paper on ARPA-H—and advanced imaging technologies. "The high cost of medical imaging is a leading reason why our healthcare costs are the highest in the world," said Feld. "There's no detection test for ALS. No brain detection for Alzheimer's. Innovations in detection technology would save on cost and human suffering."
Some biotech companies may be skeptical about the financial rewards of accelerating such technologies. But ARPA-H could fund public-private partnerships to "de-risk" biotech's involvement—an incentive that harkens back to the advance purchase contracts that companies got during Covid. (Some groups have suggested that ARPA-H could provide advance purchase agreements.)
Parikh is less bullish on creating diagnostics through ARPA-H. Like DARPA, Biden's health agency will enjoy some independence from federal oversight; it may even be located hundreds of miles from DC. That freedom affords some breathing room for innovation, but it could also make it tougher to ensure that algorithms fully consider diverse populations. "That part I really would like the government more involved in," Parikh said.
Might thinks ARPA-H should also explore innovations in clinical trials, which many patients and medical communities view as grindingly slow and requiring too many participants. "We can approve drugs for very tiny patient populations, even at the level of the individual," he said, while emphasizing the need for safety. But Platanias thinks the FDA has become much more flexible in recent years. In the cancer field, at least, "You now see faster approvals for more drugs. Having [more] shortcuts on clinical trial approvals is not necessarily a good idea."
With so many options on the table, ARPA-H needs to show the public a clear framework for measuring the value of potential projects. Kass warned that well-resourced advocates could skew the agency's priorities. They've affected health outcomes before, she noted; fundraising may partly explain larger increases in life expectancy for cystic fibrosis than sickle cell anemia. Engaging diverse communities is a must for ARPA-H. So are partnerships to get the agency's outputs to people who need them. "Research is half the equation," said Kass. "If we don't ensure implementation and access, who cares." The White House concept paper on ARPA-H made a similar point.
As Congress works on authorizing ARPA-H this year, Might is doing what he can to ensure better access to innovation on a patient-by-patient basis. Last year, his son, Bertrand, passed away suddenly from his disorder. He was 12. But Might's sense of urgency has persisted, as he directs the Precision Medicine Institute at the University of Alabama-Birmingham. That urgency "can be carried into an agency like ARPA-H," he said. "It guides what I do as I apply for funding, because I'm trying to build the infrastructure that other parents need. So they don't have to build it from scratch like I did."
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.