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#435436 Undeclared Wars in Cyberspace Are ...
The US is at war. That’s probably not exactly news, as the country has been engaged in one type of conflict or another for most of its history. The last time we officially declared war was after Japan bombed Pearl Harbor in December 1941.
Our biggest undeclared war today is not being fought by drones in the mountains of Afghanistan or even through the less-lethal barrage of threats over the nuclear programs in North Korea and Iran. In this particular war, it is the US that is under attack and on the defensive.
This is cyberwarfare.
The definition of what constitutes a cyber attack is a broad one, according to Greg White, executive director of the Center for Infrastructure Assurance and Security (CIAS) at The University of Texas at San Antonio (UTSA).
At the level of nation-state attacks, cyberwarfare could involve “attacking systems during peacetime—such as our power grid or election systems—or it could be during war time in which case the attacks may be designed to cause destruction, damage, deception, or death,” he told Singularity Hub.
For the US, the Pearl Harbor of cyberwarfare occurred during 2016 with the Russian interference in the presidential election. However, according to White, an Air Force veteran who has been involved in computer and network security since 1986, the history of cyber war can be traced back much further, to at least the first Gulf War of the early 1990s.
“We started experimenting with cyber attacks during the first Gulf War, so this has been going on a long time,” he said. “Espionage was the prime reason before that. After the war, the possibility of expanding the types of targets utilized expanded somewhat. What is really interesting is the use of social media and things like websites for [psychological operation] purposes during a conflict.”
The 2008 conflict between Russia and the Republic of Georgia is often cited as a cyberwarfare case study due to the large scale and overt nature of the cyber attacks. Russian hackers managed to bring down more than 50 news, government, and financial websites through denial-of-service attacks. In addition, about 35 percent of Georgia’s internet networks suffered decreased functionality during the attacks, coinciding with the Russian invasion of South Ossetia.
The cyberwar also offers lessons for today on Russia’s approach to cyberspace as a tool for “holistic psychological manipulation and information warfare,” according to a 2018 report called Understanding Cyberwarfare from the Modern War Institute at West Point.
US Fights Back
News in recent years has highlighted how Russian hackers have attacked various US government entities and critical infrastructure such as energy and manufacturing. In particular, a shadowy group known as Unit 26165 within the country’s military intelligence directorate is believed to be behind the 2016 US election interference campaign.
However, the US hasn’t been standing idly by. Since at least 2012, the US has put reconnaissance probes into the control systems of the Russian electric grid, The New York Times reported. More recently, we learned that the US military has gone on the offensive, putting “crippling malware” inside the Russian power grid as the U.S. Cyber Command flexes its online muscles thanks to new authority granted to it last year.
“Access to the power grid that is obtained now could be used to shut something important down in the future when we are in a war,” White noted. “Espionage is part of the whole program. It is important to remember that cyber has just provided a new domain in which to conduct the types of activities we have been doing in the real world for years.”
The US is also beginning to pour more money into cybersecurity. The 2020 fiscal budget calls for spending $17.4 billion throughout the government on cyber-related activities, with the Department of Defense (DoD) alone earmarked for $9.6 billion.
Despite the growing emphasis on cybersecurity in the US and around the world, the demand for skilled security professionals is well outpacing the supply, with a projected shortfall of nearly three million open or unfilled positions according to the non-profit IT security organization (ISC)².
UTSA is rare among US educational institutions in that security courses and research are being conducted across three different colleges, according to White. About 10 percent of the school’s 30,000-plus students are enrolled in a cyber-related program, he added, and UTSA is one of only 21 schools that has received the Cyber Operations Center of Excellence designation from the National Security Agency.
“This track in the computer science program is specifically designed to prepare students for the type of jobs they might be involved in if they went to work for the DoD,” White said.
However, White is extremely doubtful there will ever be enough cyber security professionals to meet demand. “I’ve been preaching that we’ve got to worry about cybersecurity in the workforce, not just the cybersecurity workforce, not just cybersecurity professionals. Everybody has a responsibility for cybersecurity.”
Artificial Intelligence in Cybersecurity
Indeed, humans are often seen as the weak link in cybersecurity. That point was driven home at a cybersecurity roundtable discussion during this year’s Brainstorm Tech conference in Aspen, Colorado.
Participant Dorian Daley, general counsel at Oracle, said insider threats are at the top of the list when it comes to cybersecurity. “Sadly, I think some of the biggest challenges are people, and I mean that in a number of ways. A lot of the breaches really come from insiders. So the more that you can automate things and you can eliminate human malicious conduct, the better.”
White noted that automation is already the norm in cybersecurity. “Humans can’t react as fast as systems can launch attacks, so we need to rely on automated defenses as well,” he said. “This doesn’t mean that humans are not in the loop, but much of what is done these days is ‘scripted’.”
The use of artificial intelligence, machine learning, and other advanced automation techniques have been part of the cybersecurity conversation for quite some time, according to White, such as pattern analysis to look for specific behaviors that might indicate an attack is underway.
“What we are seeing quite a bit of today falls under the heading of big data and data analytics,” he explained.
But there are signs that AI is going off-script when it comes to cyber attacks. In the hands of threat groups, AI applications could lead to an increase in the number of cyberattacks, wrote Michelle Cantos, a strategic intelligence analyst at cybersecurity firm FireEye.
“Current AI technology used by businesses to analyze consumer behavior and find new customer bases can be appropriated to help attackers find better targets,” she said. “Adversaries can use AI to analyze datasets and generate recommendations for high-value targets they think the adversary should hit.”
In fact, security researchers have already demonstrated how a machine learning system could be used for malicious purposes. The Social Network Automated Phishing with Reconnaissance system, or SNAP_R, generated more than four times as many spear-phishing tweets on Twitter than a human—and was just as successful at targeting victims in order to steal sensitive information.
Cyber war is upon us. And like the current war on terrorism, there are many battlefields from which the enemy can attack and then disappear. While total victory is highly unlikely in the traditional sense, innovations through AI and other technologies can help keep the lights on against the next cyber attack.
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Posted in Human Robots
#435161 Less Like Us: An Alternate Theory of ...
The question of whether an artificial general intelligence will be developed in the future—and, if so, when it might arrive—is controversial. One (very uncertain) estimate suggests 2070 might be the earliest we could expect to see such technology.
Some futurists point to Moore’s Law and the increasing capacity of machine learning algorithms to suggest that a more general breakthrough is just around the corner. Others suggest that extrapolating exponential improvements in hardware is unwise, and that creating narrow algorithms that can beat humans at specialized tasks brings us no closer to a “general intelligence.”
But evolution has produced minds like the human mind at least once. Surely we could create artificial intelligence simply by copying nature, either by guided evolution of simple algorithms or wholesale emulation of the human brain.
Both of these ideas are far easier to conceive of than they are to achieve. The 302 neurons of the nematode worm’s brain are still an extremely difficult engineering challenge, let alone the 86 billion in a human brain.
Leaving aside these caveats, though, many people are worried about artificial general intelligence. Nick Bostrom’s influential book on superintelligence imagines it will be an agent—an intelligence with a specific goal. Once such an agent reaches a human level of intelligence, it will improve itself—increasingly rapidly as it gets smarter—in pursuit of whatever goal it has, and this “recursive self-improvement” will lead it to become superintelligent.
This “intelligence explosion” could catch humans off guard. If the initial goal is poorly specified or malicious, or if improper safety features are in place, or if the AI decides it would prefer to do something else instead, humans may be unable to control our own creation. Bostrom gives examples of how a seemingly innocuous goal, such as “Make everyone happy,” could be misinterpreted; perhaps the AI decides to drug humanity into a happy stupor, or convert most of the world into computing infrastructure to pursue its goal.
Drexler and Comprehensive AI Services
These are increasingly familiar concerns for an AI that behaves like an agent, seeking to achieve its goal. There are dissenters to this picture of how artificial general intelligence might arise. One notable alternative point of view comes from Eric Drexler, famous for his work on molecular nanotechnology and Engines of Creation, the book that popularized it.
With respect to AI, Drexler believes our view of an artificial intelligence as a single “agent” that acts to maximize a specific goal is too narrow, almost anthropomorphizing AI, or modeling it as a more realistic route towards general intelligence. Instead, he proposes “Comprehensive AI Services” (CAIS) as an alternative route to artificial general intelligence.
What does this mean? Drexler’s argument is that we should look more closely at how machine learning and AI algorithms are actually being developed in the real world. The optimization effort is going into producing algorithms that can provide services and perform tasks like translation, music recommendations, classification, medical diagnoses, and so forth.
AI-driven improvements in technology, argues Drexler, will lead to a proliferation of different algorithms: technology and software improvement, which can automate increasingly more complicated tasks. Recursive improvement in this regime is already occurring—take the newer versions of AlphaGo, which can learn to improve themselves by playing against previous versions.
Many Smart Arms, No Smart Brain
Instead of relying on some unforeseen breakthrough, the CAIS model of AI just assumes that specialized, narrow AI will continue to improve at performing each of its tasks, and the range of tasks that machine learning algorithms will be able to perform will become wider. Ultimately, once a sufficient number of tasks have been automated, the services that an AI will provide will be so comprehensive that they will resemble a general intelligence.
One could then imagine a “general” intelligence as simply an algorithm that is extremely good at matching the task you ask it to perform to the specialized service algorithm that can perform that task. Rather than acting like a single brain that strives to achieve a particular goal, the central AI would be more like a search engine, looking through the tasks it can perform to find the closest match and calling upon a series of subroutines to achieve the goal.
For Drexler, this is inherently a safety feature. Rather than Bostrom’s single, impenetrable, conscious and superintelligent brain (which we must try to psychoanalyze in advance without really knowing what it will look like), we have a network of capabilities. If you don’t want your system to perform certain tasks, you can simply cut it off from access to those services. There is no superintelligent consciousness to outwit or “trap”: more like an extremely high-level programming language that can respond to complicated commands by calling upon one of the myriad specialized algorithms that have been developed by different groups.
This skirts the complex problem of consciousness and all of the sticky moral quandaries that arise in making minds that might be like ours. After all, if you could simulate a human mind, you could simulate it experiencing unimaginable pain. Black Mirror-esque dystopias where emulated minds have no rights and are regularly “erased” or forced to labor in dull and repetitive tasks, hove into view.
Drexler argues that, in this world, there is no need to ever build a conscious algorithm. Yet it seems likely that, at some point, humans will attempt to simulate our own brains, if only in the vain attempt to pursue immortality. This model cannot hold forever. Yet its proponents argue that any world in which we could develop general AI would probably also have developed superintelligent capabilities in a huge range of different tasks, such as computer programming, natural language understanding, and so on. In other words, CAIS arrives first.
The Future In Our Hands?
Drexler argues that his model already incorporates many of the ideas from general AI development. In the marketplace, algorithms compete all the time to perform these services: they undergo the same evolutionary pressures that lead to “higher intelligence,” but the behavior that’s considered superior is chosen by humans, and the nature of the “general intelligence” is far more shaped by human decision-making and human programmers. Development in AI services could still be rapid and disruptive.
But in Drexler’s case, the research and development capacity comes from humans and organizations driven by the desire to improve algorithms that are performing individualized and useful tasks, rather than from a conscious AI recursively reprogramming and improving itself.
In other words, this vision does not absolve us of the responsibility of making our AI safe; if anything, it gives us a greater degree of responsibility. As more and more complex “services” are automated, performing what used to be human jobs at superhuman speed, the economic disruption will be severe.
Equally, as machine learning is trusted to carry out more complex decisions, avoiding algorithmic bias becomes crucial. Shaping each of these individual decision-makers—and trying to predict the complex ways they might interact with each other—is no less daunting a task than specifying the goal for a hypothetical, superintelligent, God-like AI. Arguably, the consequences of the “misalignment” of these services algorithms are already multiplying around us.
The CAIS model bridges the gap between real-world AI, machine learning developments, and real-world safety considerations, as well as the speculative world of superintelligent agents and the safety considerations involved with controlling their behavior. We should keep our minds open as to what form AI and machine learning will take, and how it will influence our societies—and we must take care to ensure that the systems we create don’t end up forcing us all to live in a world of unintended consequences.
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Posted in Human Robots
#435046 The Challenge of Abundance: Boredom, ...
As technology continues to progress, the possibility of an abundant future seems more likely. Artificial intelligence is expected to drive down the cost of labor, infrastructure, and transport. Alternative energy systems are reducing the cost of a wide variety of goods. Poverty rates are falling around the world as more people are able to make a living, and resources that were once inaccessible to millions are becoming widely available.
But such a life presents fuel for the most common complaint against abundance: if robots take all the jobs, basic income provides us livable welfare for doing nothing, and healthcare is a guarantee free of charge, then what is the point of our lives? What would motivate us to work and excel if there are no real risks or rewards? If everything is simply given to us, how would we feel like we’ve ever earned anything?
Time has proven that humans inherently yearn to overcome challenges—in fact, this very desire likely exists as the root of most technological innovation. And the idea that struggling makes us stronger isn’t just anecdotal, it’s scientifically validated.
For instance, kids who use anti-bacterial soaps and sanitizers too often tend to develop weak immune systems, causing them to get sick more frequently and more severely. People who work out purposely suffer through torn muscles so that after a few days of healing their muscles are stronger. And when patients visit a psychologist to handle a fear that is derailing their lives, one of the most common treatments is exposure therapy: a slow increase of exposure to the suffering so that the patient gets stronger and braver each time, able to take on an incrementally more potent manifestation of their fears.
Different Kinds of Struggle
It’s not hard to understand why people might fear an abundant future as a terribly mundane one. But there is one crucial mistake made in this assumption, and it was well summarized by Indian mystic and author Sadhguru, who said during a recent talk at Google:
Stomach empty, only one problem. Stomach full—one hundred problems; because what we refer to as human really begins only after survival is taken care of.
This idea is backed up by Maslow’s hierarchy of needs, which was first presented in his 1943 paper “A Theory of Human Motivation.” Maslow shows the steps required to build to higher and higher levels of the human experience. Not surprisingly, the first two levels deal with physiological needs and the need for safety—in other words, with the body. You need to have food, water, and sleep, or you die. After that, you need to be protected from threats, from the elements, from dangerous people, and from disease and pain.
Maslow’s Hierarchy of Needs. Photo by Wikimedia User:Factoryjoe / CC BY-SA 3.0
The beauty of these first two levels is that they’re clear-cut problems with clear-cut solutions: if you’re hungry, then you eat; if you’re thirsty, then you drink; if you’re tired, then you sleep.
But what about the next tiers of the hierarchy? What of love and belonging, of self-esteem and self-actualization? If we’re lonely, can we just summon up an authentic friend or lover? If we feel neglected by society, can we demand it validate us? If we feel discouraged and disappointed in ourselves, can we simply dial up some confidence and self-esteem?
Of course not, and that’s because these psychological needs are nebulous; they don’t contain clear problems with clear solutions. They involve the external world and other people, and are complicated by the infinite flavors of nuance and compromise that are required to navigate human relationships and personal meaning.
These psychological difficulties are where we grow our personalities, outlooks, and beliefs. The truly defining characteristics of a person are dictated not by the physical situations they were forced into—like birth, socioeconomic class, or physical ailment—but instead by the things they choose. So a future of abundance helps to free us from the physical limitations so that we can truly commit to a life of purpose and meaning, rather than just feel like survival is our purpose.
The Greatest Challenge
And that’s the plot twist. This challenge to come to grips with our own individuality and freedom could actually be the greatest challenge our species has ever faced. Can you imagine waking up every day with infinite possibility? Every choice you make says no to the rest of reality, and so every decision carries with it truly life-defining purpose and meaning. That sounds overwhelming. And that’s probably because in our current socio-economic systems, it is.
Studies have shown that people in wealthier nations tend to experience more anxiety and depression. Ron Kessler, professor of health care policy at Harvard and World Health Organization (WHO) researcher, summarized his findings of global mental health by saying, “When you’re literally trying to survive, who has time for depression? Americans, on the other hand, many of whom lead relatively comfortable lives, blow other nations away in the depression factor, leading some to suggest that depression is a ‘luxury disorder.’”
This might explain why America scores in the top rankings for the most depressed and anxious country on the planet. We surpassed our survival needs, and instead became depressed because our jobs and relationships don’t fulfill our expectations for the next three levels of Maslow’s hierarchy (belonging, esteem, and self-actualization).
But a future of abundance would mean we’d have to deal with these levels. This is the challenge for the future; this is what keeps things from being mundane.
As a society, we would be forced to come to grips with our emotional intelligence, to reckon with philosophy rather than simply contemplate it. Nearly every person you meet will be passionately on their own customized life journey, not following a routine simply because of financial limitations. Such a world seems far more vibrant and interesting than one where most wander sleep-deprived and numb while attempting to survive the rat race.
We can already see the forceful hand of this paradigm shift as self-driving cars become ubiquitous. For example, consider the famous psychological and philosophical “trolley problem.” In this thought experiment, a person sees a trolley car heading towards five people on the train tracks; they see a lever that will allow them to switch the trolley car to a track that instead only has one person on it. Do you switch the lever and have a hand in killing one person, or do you let fate continue and kill five people instead?
For the longest time, this was just an interesting quandary to consider. But now, massive corporations have to have an answer, so they can program their self-driving cars with the ability to choose between hitting a kid who runs into the road or swerving into an oncoming car carrying a family of five. When companies need philosophers to make business decisions, it’s a good sign of what’s to come.
Luckily, it’s possible this forceful reckoning with philosophy and our own consciousness may be exactly what humanity needs. Perhaps our great failure as a species has been a result of advanced cognition still trapped in the first two levels of Maslow’s hierarchy due to a long history of scarcity.
As suggested in the opening scenes in 2001: A Space Odyssey, our ape-like proclivity for violence has long stayed the same while the technology we fight with and live amongst has progressed. So while well-off Americans may have comfortable lives, they still know they live in a system where there is no safety net, where a single tragic failure could still mean hunger and homelessness. And because of this, that evolutionarily hard-wired neurotic part of our brain that fears for our survival has never been able to fully relax, and so that anxiety and depression that come with too much freedom but not enough security stays ever present.
Not only might this shift in consciousness help liberate humanity, but it may be vital if we’re to survive our future creations as well. Whatever values we hold dear as a species are the ones we will imbue into the sentient robots we create. If machine learning is going to take its guidance from humanity, we need to level up humanity’s emotional maturity.
While the physical struggles of the future may indeed fall to the wayside amongst abundance, it’s unlikely to become a mundane world; instead, it will become a vibrant culture where each individual is striving against the most important struggle that affects all of us: the challenge to find inner peace, to find fulfillment, to build meaningful relationships, and ultimately, the challenge to find ourselves.
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Posted in Human Robots
#434792 Extending Human Longevity With ...
Lizards can regrow entire limbs. Flatworms, starfish, and sea cucumbers regrow entire bodies. Sharks constantly replace lost teeth, often growing over 20,000 teeth throughout their lifetimes. How can we translate these near-superpowers to humans?
The answer: through the cutting-edge innovations of regenerative medicine.
While big data and artificial intelligence transform how we practice medicine and invent new treatments, regenerative medicine is about replenishing, replacing, and rejuvenating our physical bodies.
In Part 5 of this blog series on Longevity and Vitality, I detail three of the regenerative technologies working together to fully augment our vital human organs.
Replenish: Stem cells, the regenerative engine of the body
Replace: Organ regeneration and bioprinting
Rejuvenate: Young blood and parabiosis
Let’s dive in.
Replenish: Stem Cells – The Regenerative Engine of the Body
Stem cells are undifferentiated cells that can transform into specialized cells such as heart, neurons, liver, lung, skin and so on, and can also divide to produce more stem cells.
In a child or young adult, these stem cells are in large supply, acting as a built-in repair system. They are often summoned to the site of damage or inflammation to repair and restore normal function.
But as we age, our supply of stem cells begins to diminish as much as 100- to 10,000-fold in different tissues and organs. In addition, stem cells undergo genetic mutations, which reduce their quality and effectiveness at renovating and repairing your body.
Imagine your stem cells as a team of repairmen in your newly constructed mansion. When the mansion is new and the repairmen are young, they can fix everything perfectly. But as the repairmen age and reduce in number, your mansion eventually goes into disrepair and finally crumbles.
What if you could restore and rejuvenate your stem cell population?
One option to accomplish this restoration and rejuvenation is to extract and concentrate your own autologous adult stem cells from places like your adipose (or fat) tissue or bone marrow.
These stem cells, however, are fewer in number and have undergone mutations (depending on your age) from their original ‘software code.’ Many scientists and physicians now prefer an alternative source, obtaining stem cells from the placenta or umbilical cord, the leftovers of birth.
These stem cells, available in large supply and expressing the undamaged software of a newborn, can be injected into joints or administered intravenously to rejuvenate and revitalize.
Think of these stem cells as chemical factories generating vital growth factors that can help to reduce inflammation, fight autoimmune disease, increase muscle mass, repair joints, and even revitalize skin and grow hair.
Over the last decade, the number of publications per year on stem cell-related research has increased 40x, and the stem cell market is expected to increase to $297 billion by 2022.
Rising research and development initiatives to develop therapeutic options for chronic diseases and growing demand for regenerative treatment options are the most significant drivers of this budding industry.
Biologists led by Kohji Nishida at Osaka University in Japan have discovered a new way to nurture and grow the tissues that make up the human eyeball. The scientists are able to grow retinas, corneas, the eye’s lens, and more, using only a small sample of adult skin.
In a Stanford study, seven of 18 stroke victims who agreed to stem cell treatments showed remarkable motor function improvements. This treatment could work for other neurodegenerative conditions such as Alzheimer’s, Parkinson’s, and ALS.
Doctors from the USC Neurorestoration Center and Keck Medicine of USC injected stem cells into the damaged cervical spine of a recently paralyzed 21-year-old man. Three months later, he showed dramatic improvement in sensation and movement of both arms.
In 2019, doctors in the U.K. cured a patient with HIV for the second time ever thanks to the efficacy of stem cells. After giving the cancer patient (who also had HIV) an allogeneic haematopoietic (e.g. blood) stem cell treatment for his Hodgkin’s lymphoma, the patient went into long-term HIV remission—18 months and counting at the time of the study’s publication.
Replace: Organ Regeneration and 3D Printing
Every 10 minutes, someone is added to the US organ transplant waiting list, totaling over 113,000 people waiting for replacement organs as of January 2019.
Countless more people in need of ‘spare parts’ never make it onto the waiting list. And on average, 20 people die each day while waiting for a transplant.
As a result, 35 percent of all US deaths (~900,000 people) could be prevented or delayed with access to organ replacements.
The excessive demand for donated organs will only intensify as technologies like self-driving cars make the world safer, given that many organ donors result from auto and motorcycle accidents. Safer vehicles mean less accidents and donations.
Clearly, replacement and regenerative medicine represent a massive opportunity.
Organ Entrepreneurs
Enter United Therapeutics CEO, Dr. Martine Rothblatt. A one-time aerospace entrepreneur (she was the founder of Sirius Satellite Radio), Rothblatt changed careers in the 1990s after her daughter developed a rare lung disease.
Her moonshot today is to create an industry of replacement organs. With an initial focus on diseases of the lung, Rothblatt set out to create replacement lungs. To accomplish this goal, her company United Therapeutics has pursued a number of technologies in parallel.
3D Printing Lungs
In 2017, United teamed up with one of the world’s largest 3D printing companies, 3D Systems, to build a collagen bioprinter and is paying another company, 3Scan, to slice up lungs and create detailed maps of their interior.
This 3D Systems bioprinter now operates according to a method called stereolithography. A UV laser flickers through a shallow pool of collagen doped with photosensitive molecules. Wherever the laser lingers, the collagen cures and becomes solid.
Gradually, the object being printed is lowered and new layers are added. The printer can currently lay down collagen at a resolution of around 20 micrometers, but will need to achieve resolution of a micrometer in size to make the lung functional.
Once a collagen lung scaffold has been printed, the next step is to infuse it with human cells, a process called recellularization.
The goal here is to use stem cells that grow on scaffolding and differentiate, ultimately providing the proper functionality. Early evidence indicates this approach can work.
In 2018, Harvard University experimental surgeon Harald Ott reported that he pumped billions of human cells (from umbilical cords and diced lungs) into a pig lung stripped of its own cells. When Ott’s team reconnected it to a pig’s circulation, the resulting organ showed rudimentary function.
Humanizing Pig Lungs
Another of Rothblatt’s organ manufacturing strategies is called xenotransplantation, the idea of transplanting an animal’s organs into humans who need a replacement.
Given the fact that adult pig organs are similar in size and shape to those of humans, United Therapeutics has focused on genetically engineering pigs to allow humans to use their organs. “It’s actually not rocket science,” said Rothblatt in her 2015 TED talk. “It’s editing one gene after another.”
To accomplish this goal, United Therapeutics made a series of investments in companies such as Revivicor Inc. and Synthetic Genomics Inc., and signed large funding agreements with the University of Maryland, University of Alabama, and New York Presbyterian/Columbia University Medical Center to create xenotransplantation programs for new hearts, kidneys, and lungs, respectively. Rothblatt hopes to see human translation in three to four years.
In preparation for that day, United Therapeutics owns a 132-acre property in Research Triangle Park and built a 275,000-square-foot medical laboratory that will ultimately have the capability to annually produce up to 1,000 sets of healthy pig lungs—known as xenolungs—from genetically engineered pigs.
Lung Ex Vivo Perfusion Systems
Beyond 3D printing and genetically engineering pig lungs, Rothblatt has already begun implementing a third near-term approach to improve the supply of lungs across the US.
Only about 30 percent of potential donor lungs meet transplant criteria in the first place; of those, only about 85 percent of those are usable once they arrive at the surgery center. As a result, nearly 75 percent of possible lungs never make it to the recipient in need.
What if these lungs could be rejuvenated? This concept informs Dr. Rothblatt’s next approach.
In 2016, United Therapeutics invested $41.8 million in TransMedics Inc., an Andover, Massachusetts company that develops ex vivo perfusion systems for donor lungs, hearts, and kidneys.
The XVIVO Perfusion System takes marginal-quality lungs that initially failed to meet transplantation standard-of-care criteria and perfuses and ventilates them at normothermic conditions, providing an opportunity for surgeons to reassess transplant suitability.
Rejuvenate Young Blood and Parabiosis
In HBO’s parody of the Bay Area tech community, Silicon Valley, one of the episodes (Season 4, Episode 5) is named “The Blood Boy.”
In this installment, tech billionaire Gavin Belson (Matt Ross) is meeting with Richard Hendricks (Thomas Middleditch) and his team, speaking about the future of the decentralized internet. A young, muscled twenty-something disrupts the meeting when he rolls in a transfusion stand and silently hooks an intravenous connection between himself and Belson.
Belson then introduces the newcomer as his “transfusion associate” and begins to explain the science of parabiosis: “Regular transfusions of the blood of a younger physically fit donor can significantly retard the aging process.”
While the sitcom is fiction, that science has merit, and the scenario portrayed in the episode is already happening today.
On the first point, research at Stanford and Harvard has demonstrated that older animals, when transfused with the blood of young animals, experience regeneration across many tissues and organs.
The opposite is also true: young animals, when transfused with the blood of older animals, experience accelerated aging. But capitalizing on this virtual fountain of youth has been tricky.
Ambrosia
One company, a San Francisco-based startup called Ambrosia, recently commenced one of the trials on parabiosis. Their protocol is simple: Healthy participants aged 35 and older get a transfusion of blood plasma from donors under 25, and researchers monitor their blood over the next two years for molecular indicators of health and aging.
Ambrosia’s founder Jesse Karmazin became interested in launching a company around parabiosis after seeing impressive data from animals and studies conducted abroad in humans: In one trial after another, subjects experience a reversal of aging symptoms across every major organ system. “The effects seem to be almost permanent,” he said. “It’s almost like there’s a resetting of gene expression.”
Infusing your own cord blood stem cells as you age may have tremendous longevity benefits. Following an FDA press release in February 2019, Ambrosia halted its consumer-facing treatment after several months of operation.
Understandably, the FDA raised concerns about the practice of parabiosis because to date, there is a marked lack of clinical data to support the treatment’s effectiveness.
Elevian
On the other end of the reputability spectrum is a startup called Elevian, spun out of Harvard University. Elevian is approaching longevity with a careful, scientifically validated strategy. (Full Disclosure: I am both an advisor to and investor in Elevian.)
CEO Mark Allen, MD, is joined by a dozen MDs and Ph.Ds out of Harvard. Elevian’s scientific founders started the company after identifying specific circulating factors that may be responsible for the “young blood” effect.
One example: A naturally occurring molecule known as “growth differentiation factor 11,” or GDF11, when injected into aged mice, reproduces many of the regenerative effects of young blood, regenerating heart, brain, muscles, lungs, and kidneys.
More specifically, GDF11 supplementation reduces age-related cardiac hypertrophy, accelerates skeletal muscle repair, improves exercise capacity, improves brain function and cerebral blood flow, and improves metabolism.
Elevian is developing a number of therapeutics that regulate GDF11 and other circulating factors. The goal is to restore our body’s natural regenerative capacity, which Elevian believes can address some of the root causes of age-associated disease with the promise of reversing or preventing many aging-related diseases and extending the healthy lifespan.
Conclusion
In 1992, futurist Leland Kaiser coined the term “regenerative medicine”:
“A new branch of medicine will develop that attempts to change the course of chronic disease and in many instances will regenerate tired and failing organ systems.”
Since then, the powerful regenerative medicine industry has grown exponentially, and this rapid growth is anticipated to continue.
A dramatic extension of the human healthspan is just over the horizon. Soon, we’ll all have the regenerative superpowers previously relegated to a handful of animals and comic books.
What new opportunities open up when anybody, anywhere, and at anytime can regenerate, replenish, and replace entire organs and metabolic systems on command?
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