Your Genetic Data Is The New Oil. These Startups Will Pay to Rent It.
Perhaps you're one of the 12 million people who has spit into a tube in recent years to learn the secrets in your genetic code, like your ancestry, your health risks, or your carrier status for certain diseases. If you haven't participated in direct-to-consumer genetic testing, you may know someone who has.
It's for people who want more control over their genetic data--plus a share of the proceeds when and if that data is used.
Mountains of genomic data have been piling up steeply over the last several years, but according to some experts, not enough research and drug discovery is being done with the data collected, and customers rarely have a say in how their data is used. Now, a slew of ambitious startup companies are bringing together the best of blockchain technology and human genomics to help solve these problems.
But First, Why Is Your Genome So Valuable?
Access to genetic information is an obvious boon to scientific and medical progress. In the right hands, it has the potential to save lives and reduce suffering — by facilitating the development of better, safer, more targeted treatments and by shedding light on the role of genetics in countless diseases and medical conditions.
Research requiring access to direct-to-consumer (DTC) genomic data is already well underway. For example, 23andMe, the popular California-based DTC genetic testing company, has published 107 research articles so far, as of this May, using data from their five million-plus customers around the world. Their website states that, on average, of the 80 percent of their customers who have opted to share their genomic data for research purposes, each "individual contributes to 200 different research studies."
And this July, a new collaboration was announced between 23andMe and GlaxoSmithKline, the London-based pharmaceutical company. GlaxoSmithKline will be using data from 23andMe customers to develop new medical treatments, while 23andMe will receive $300 million from the four-year deal. Both companies are poised to profit significantly from their union.
Should 23andMe's customers share in the gains? Peter Pitts, president of the Center for Medicine in the Public Interest, believes they should. "Are they going to offer rebates to people who opt in, so their customers aren't paying for the privilege of 23andMe working with a for-profit company in a for-profit research project?" Pitts told NBC. So far, 23andMe has not announced any plans to share profits with their customers.
But outside of such major partnerships, many researchers are frustrated by the missed opportunities to dig deeper into the correlations between genetics and disease. That's because people's de-identified genomic information is "essentially lying fallow," siloed behind significant security blockades in the interest of preserving their anonymity. So how can both researchers and consumers come out ahead?
Putting Consumers Back in Control
For people who want more control over their genetic data -- plus a share of the proceeds when and if that data is used -- a few companies have paired consumer genomics with blockchain technology to form a new field called "blockchain genomics." Blockchain is a data storage technology that relies on a network of computers, or peer-to-peer setup, making it incredibly difficult to hack. "It's a closed loop of transactions that gets protected and encrypted, and it cannot be changed," says Tanya Woods, a blockchain thought leader and founder of Kind Village, a social impact technology platform.
The vision is to incentivize consumers to share their genomic data and empower researchers to make new breakthroughs.
"So if I agree to give you something and you agree to accept it, we make that exchange, and then that basic framework is captured in a block. … Anything that can be exchanged can be ledgered on blockchain. Anything. It could be real estate, it could be the transfer of artwork, it could be the purchase of a song or any digital content, it could be recognition of a certification," and so on.
The blockchain genomics companies' vision is to incentivize consumers to share their genomic data and empower researchers to make new breakthroughs, all while keeping the data secure and the identities of consumers anonymous.
Consumers, or "partners" as these companies call them, will have a direct say regarding which individuals or organizations can "rent" their data, and will be able to negotiate the amount they receive in exchange. But instead of fiat currency (aka "regular money") as payment, partners will either be remunerated in cryptocurrency unique to the specific company or they will be provided with individual shares of ownership in the database for contributing DNA data and other medical information.
Luna DNA, one of the blockchain genomics companies, "will allow any credible researcher or non-profit to access the databases for a nominal fee," says its president and co-founder, Dawn Barry. Luna DNA's infrastructure was designed to embrace certain conceptions of privacy and privacy law "in which individuals are in total control of their data, including the ability to have their data be 'forgotten' at any time," she said. This is nearly impossible to implement in pre-existing systems that were not designed with full control by the individual in mind.
One of the legal instruments to which Barry referred was the European Union's General Data Protection Regulation, which "states that the data collected on an individual is owned and should be controlled by that individual," she explained. Another is the California Privacy Act that echoes similar principles. "There is a global trend towards more control by the individual that has very deep implications to companies and sites that collect and aggregate data."
David Koepsell, CEO and co-founder of EncrypGen, told Forbes that "Most people are not aware that your DNA contains information about your life expectancy, your proclivity to depression or schizophrenia, your complete ethnic ancestry, your expected intelligence, maybe even your political inclinations" — information that could be misused by insurance companies and employers. And though DTC customers have been assured that their data will stay anonymous, some data can be linked back to consumers' identities. Blockchain may be the answer to these concerns.
Both blockchain technology and the DTC genetic testing arena have a glaring diversity problem.
"The security that's provided by blockchain is tremendous," Woods says. "It's a significant improvement … and as we move toward more digitized economies around the world, these kinds of solutions that are providing security, validity, trust — they're very important."
In the case of blockchain genomics companies like EncrypGen, Luna DNA, Longenesis, and Zenome, each partner who joins would bring a digital copy of their genetic readout from DTC testing companies (like 23andMe or AncestryDNA). The blockchain technology would then be used to record how and for what purposes researchers interact with it. (To learn more about blockchain, check out this helpful visual guide by Reuters.)
Obstacles in the Path to Success
The cryptocurrency approach as a method of payment could be an unattractive lure to consumers if only a limited number of people make transactions in a given currency's network. And the decade-old technology underlying it -- blockchain -- is not yet widely supported, or even well-understood, by the public at large.
"People conflate blockchain with cryptocurrency and bitcoin and all of the concerns and uncertainty thereof," Barry told us. "One can think of cryptocurrency as a single expression of the vast possibilities of the blockchain technology. Blockchain is straightforward in concept and arcane in its implementation."
But blockchain, with its Gini coefficient of 0.98, is one of the most unequal "playing fields" around. The Gini coefficient is a measure of economic inequality, where 0 represents perfect equality and 1 represents perfect inequality. Around 90 percent of bitcoin users, for example, are male, white or Asian, between the ages of 18 and 34, straight, and from middle and upper class families.
The DTC genetic testing arena, too, has a glaring diversity problem. Most DTC genetic test consumers, just like most genetic study participants, are of European descent. In the case of genetic studies, this disparity is largely explained by the fact that most research is done in Europe and North America. In addition to being over 85 percent white, individuals who purchase DTC genetic testing kits are highly educated (about half have more than a college degree), well off (43 percent have a household income of $100,000 or more per year), and are politically liberal (almost 65 percent). Only 14.5 percent of DTC genetic test consumers are non-white, and a mere 5 percent are Hispanic.
Since risk of genetic diseases often varies greatly between ethnic groups, results from DTC tests can be less accurate and less specific for those of non-European ancestry — simply due to a lack of diverse data. The bigger the genetic database, wrote Sarah Zhang for The Atlantic, the more insights 23andMe and other DTC companies "can glean from DNA. That, in turn, means the more [they] can tell customers about their ancestry and health…" Though efforts at recruiting non-white participants have been ongoing, and some successes have been made at improving ancestry tools for people of color, the benefits of genomic gathering in North America are still largely reaped by Caucasians.
So far, it's not yet clear who or how many people will choose to partake in the offerings of blockchain genomics companies.
So one chief hurdle for the blockchain genomics companies is getting the technology into the hands of those who are under-represented in both blockchain and genetic testing research. Women, in particular, may be difficult to bring on board the blockchain genomics bandwagon — though not from lack of interest. Although women make up a significant portion of DTC genetic testing customers (between 50 and 60 percent), their presence is lacking in blockchain and the biotech industry in general.
At the North American Bitcoin Conference in Miami earlier this year, only three women were on stage, compared to 84 men. And the after-party was held in a strip club.
"I was at that conference," Woods told us. "I don't know what happened at the strip club, I didn't observe it. That's not to say it didn't happen … but I enjoyed being at the conference and I enjoyed learning from people who are experimenting in the space and developing in it. Generally, would I have loved to see more women visible? Of course. In tech generally I want to see more women visible, but there's a whole ecosystem shifting that has to happen to make that possible."
Luna's goal is to achieve equal access to a technology (blockchain genomics) that could potentially improve health and quality of life for all involved. But in the merging of two fields that have been unequal since their inception, achieving equal access is one tall order indeed. So far, it's not yet clear who or how many people will choose to participate. LunaDNA's platform has not yet launched; EncrypGen released their beta version just last month.
Sharon Terry, president and CEO of Genetic Alliance — a nonprofit organization that advocates for access to quality genetic services — recently shared a message that reflects the zeitgeist for all those entering the blockchain genomics space: "Be authentic. Tell the truth, even about motives and profits. Be transparent. Engage us. Don't leave us out. Make this real collaboration. Be bold. Take risks. People are dying. It's time to march forward and make a difference."
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.