Beyond Henrietta Lacks: How the Law Has Denied Every American Ownership Rights to Their Own Cells
The common perception is that Henrietta Lacks was a victim of poverty and racism when in 1951 doctors took samples of her cervical cancer without her knowledge or permission and turned them into the world's first immortalized cell line, which they called HeLa. The cell line became a workhorse of biomedical research and facilitated the creation of medical treatments and cures worth untold billions of dollars. Neither Lacks nor her family ever received a penny of those riches.
But racism and poverty is not to blame for Lacks' exploitation—the reality is even worse. In fact all patients, then and now, regardless of social or economic status, have absolutely no right to cells that are taken from their bodies. Some have called this biological slavery.
How We Got Here
The case that established this legal precedent is Moore v. Regents of the University of California.
John Moore was diagnosed with hairy-cell leukemia in 1976 and his spleen was removed as part of standard treatment at the UCLA Medical Center. On initial examination his physician, David W. Golde, had discovered some unusual qualities to Moore's cells and made plans prior to the surgery to have the tissue saved for research rather than discarded as waste. That research began almost immediately.
"On both sides of the case, legal experts and cultural observers cautioned that ownership of a human body was the first step on the slippery slope to 'bioslavery.'"
Even after Moore moved to Seattle, Golde kept bringing him back to Los Angeles to collect additional samples of blood and tissue, saying it was part of his treatment. When Moore asked if the work could be done in Seattle, he was told no. Golde's charade even went so far as claiming to find a low-income subsidy to pay for Moore's flights and put him up in a ritzy hotel to get him to return to Los Angeles, while paying for those out of his own pocket.
Moore became suspicious when he was asked to sign new consent forms giving up all rights to his biological samples and he hired an attorney to look into the matter. It turned out that Golde had been lying to his patient all along; he had been collecting samples unnecessary to Moore's treatment and had turned them into a cell line that he and UCLA had patented and already collected millions of dollars in compensation. The market for the cell lines was estimated at $3 billion by 1990.
Moore felt he had been taken advantage of and filed suit to claim a share of the money that had been made off of his body. "On both sides of the case, legal experts and cultural observers cautioned that ownership of a human body was the first step on the slippery slope to 'bioslavery,'" wrote Priscilla Wald, a professor at Duke University whose career has focused on issues of medicine and culture. "Moore could be viewed as asking to commodify his own body part or be seen as the victim of the theft of his most private and inalienable information."
The case bounced around different levels of the court system with conflicting verdicts for nearly six years until the California Supreme Court ruled on July 9, 1990 that Moore had no legal rights to cells and tissue once they were removed from his body.
The court made a utilitarian argument that the cells had no value until scientists manipulated them in the lab. And it would be too burdensome for researchers to track individual donations and subsequent cell lines to assure that they had been ethically gathered and used. It would impinge on the free sharing of materials between scientists, slow research, and harm the public good that arose from such research.
"In effect, what Moore is asking us to do is impose a tort duty on scientists to investigate the consensual pedigree of each human cell sample used in research," the majority wrote. In other words, researchers don't need to ask any questions about the materials they are using.
One member of the court did not see it that way. In his dissent, Stanley Mosk raised the specter of slavery that "arises wherever scientists or industrialists claim, as defendants have here, the right to appropriate and exploit a patient's tissue for their sole economic benefit—the right, in other words, to freely mine or harvest valuable physical properties of the patient's body. … This is particularly true when, as here, the parties are not in equal bargaining positions."
Mosk also cited the appeals court decision that the majority overturned: "If this science has become for profit, then we fail to see any justification for excluding the patient from participation in those profits."
But the majority bought the arguments that Golde, UCLA, and the nascent biotechnology industry in California had made in amici briefs filed throughout the legal proceedings. The road was now cleared for them to develop products worth billions without having to worry about or share with the persons who provided the raw materials upon which their research was based.
Critical Views
Biomedical research requires a continuous and ever-growing supply of human materials for the foundation of its ongoing work. If an increasing number of patients come to feel as John Moore did, that the system is ripping them off, then they become much less likely to consent to use of their materials in future research.
Some legal and ethical scholars say that donors should be able to limit the types of research allowed for their tissues and researchers should be monitored to assure compliance with those agreements. For example, today it is commonplace for companies to certify that their clothing is not made by child labor, their coffee is grown under fair trade conditions, that food labeled kosher is properly handled. Should we ask any less of our pharmaceuticals than that the donors whose cells made such products possible have been treated honestly and fairly, and share in the financial bounty that comes from such drugs?
Protection of individual rights is a hallmark of the American legal system, says Lisa Ikemoto, a law professor at the University of California Davis. "Putting the needs of a generalized public over the interests of a few often rests on devaluation of the humanity of the few," she writes in a reimagined version of the Moore decision that upholds Moore's property claims to his excised cells. The commentary is in a chapter of a forthcoming book in the Feminist Judgment series, where authors may only use legal precedent in effect at the time of the original decision.
"Why is the law willing to confer property rights upon some while denying the same rights to others?" asks Radhika Rao, a professor at the University of California, Hastings College of the Law. "The researchers who invest intellectual capital and the companies and universities that invest financial capital are permitted to reap profits from human research, so why not those who provide the human capital in the form of their own bodies?" It might be seen as a kind of sweat equity where cash strapped patients make a valuable in kind contribution to the enterprise.
The Moore court also made a big deal about inhibiting the free exchange of samples between scientists. That has become much less the situation over the more than three decades since the decision was handed down. Ironically, this decision, as well as other laws and regulations, have since strengthened the power of patents in biomedicine and by doing so have increased secrecy and limited sharing.
"Although the research community theoretically endorses the sharing of research, in reality sharing is commonly compromised by the aggressive pursuit and defense of patents and by the use of licensing fees that hinder collaboration and development," Robert D. Truog, Harvard Medical School ethicist and colleagues wrote in 2012 in the journal Science. "We believe that measures are required to ensure that patients not bear all of the altruistic burden of promoting medical research."
Additionally, the increased complexity of research and the need for exacting standardization of materials has given rise to an industry that supplies certified chemical reagents, cell lines, and whole animals bred to have specific genetic traits to meet research needs. This has been more efficient for research and has helped to ensure that results from one lab can be reproduced in another.
The Court's rationale of fostering collaboration and free exchange of materials between researchers also has been undercut by the changing structure of that research. Big pharma has shrunk the size of its own research labs and over the last decade has worked out cooperative agreements with major research universities where the companies contribute to the research budget and in return have first dibs on any findings (and sometimes a share of patent rights) that come out of those university labs. It has had a chilling effect on the exchange of materials between universities.
Perhaps tracking cell line donors and use restrictions on those donations might have been burdensome to researchers when Moore was being litigated. Some labs probably still kept their cell line records on 3x5 index cards, computers were primarily expensive room-size behemoths with limited capacity, the internet barely existed, and there was no cloud storage.
But that was the dawn of a new technological age and standards have changed. Now cell lines are kept in state-of-the-art sub zero storage units, tagged with the source, type of tissue, date gathered and often other information. Adding a few more data fields and contacting the donor if and when appropriate does not seem likely to disrupt the research process, as the court asserted.
Forging the Future
"U.S. universities are awarded almost 3,000 patents each year. They earn more than $2 billion each year from patent royalties. Sharing a modest portion of these profits is a novel method for creating a greater sense of fairness in research relationships that we think is worth exploring," wrote Mark Yarborough, a bioethicist at the University of California Davis Medical School, and colleagues. That was penned nearly a decade ago and those numbers have only grown.
The Michigan BioTrust for Health might serve as a useful model in tackling some of these issues. Dried blood spots have been collected from all newborns for half a century to be tested for certain genetic diseases, but controversy arose when the huge archive of dried spots was used for other research projects. As a result, the state created a nonprofit organization to in essence become a biobank and manage access to these spots only for specific purposes, and also to share any revenue that might arise from that research.
"If there can be no property in a whole living person, does it stand to reason that there can be no property in any part of a living person? If there were, can it be said that this could equate to some sort of 'biological slavery'?" Irish ethicist Asim A. Sheikh wrote several years ago. "Any amount of effort spent pondering the issue of 'ownership' in human biological materials with existing law leaves more questions than answers."
Perhaps the biggest question will arise when -- not if but when -- it becomes possible to clone a human being. Would a human clone be a legal person or the property of those who created it? Current legal precedent points to it being the latter.
Today, October 4, is the 70th anniversary of Henrietta Lacks' death from cancer. Over those decades her immortalized cells have helped make possible miraculous advances in medicine and have had a role in generating billions of dollars in profits. Surviving family members have spoken many times about seeking a share of those profits in the name of social justice; they intend to file lawsuits today. Such cases will succeed or fail on their own merits. But regardless of their specific outcomes, one can hope that they spark a larger public discussion of the role of patients in the biomedical research enterprise and lead to establishing a legal and financial claim for their contributions toward the next generation of biomedical research.
The Case for an Outright Ban on Facial Recognition Technology
[Editor's Note: This essay is in response to our current Big Question, which we posed to experts with different perspectives: "Do you think the use of facial recognition technology by the police or government should be banned? If so, why? If not, what limits, if any, should be placed on its use?"]
In a surprise appearance at the tail end of Amazon's much-hyped annual product event last month, CEO Jeff Bezos casually told reporters that his company is writing its own facial recognition legislation.
The use of computer algorithms to analyze massive databases of footage and photographs could render human privacy extinct.
It seems that when you're the wealthiest human alive, there's nothing strange about your company––the largest in the world profiting from the spread of face surveillance technology––writing the rules that govern it.
But if lawmakers and advocates fall into Silicon Valley's trap of "regulating" facial recognition and other forms of invasive biometric surveillance, that's exactly what will happen.
Industry-friendly regulations won't fix the dangers inherent in widespread use of face scanning software, whether it's deployed by governments or for commercial purposes. The use of this technology in public places and for surveillance purposes should be banned outright, and its use by private companies and individuals should be severely restricted. As artificial intelligence expert Luke Stark wrote, it's dangerous enough that it should be outlawed for "almost all practical purposes."
Like biological or nuclear weapons, facial recognition poses such a profound threat to the future of humanity and our basic rights that any potential benefits are far outweighed by the inevitable harms.
We live in cities and towns with an exponentially growing number of always-on cameras, installed in everything from cars to children's toys to Amazon's police-friendly doorbells. The use of computer algorithms to analyze massive databases of footage and photographs could render human privacy extinct. It's a world where nearly everything we do, everywhere we go, everyone we associate with, and everything we buy — or look at and even think of buying — is recorded and can be tracked and analyzed at a mass scale for unimaginably awful purposes.
Biometric tracking enables the automated and pervasive monitoring of an entire population. There's ample evidence that this type of dragnet mass data collection and analysis is not useful for public safety, but it's perfect for oppression and social control.
Law enforcement defenders of facial recognition often state that the technology simply lets them do what they would be doing anyway: compare footage or photos against mug shots, drivers licenses, or other databases, but faster. And they're not wrong. But the speed and automation enabled by artificial intelligence-powered surveillance fundamentally changes the impact of that surveillance on our society. Being able to do something exponentially faster, and using significantly less human and financial resources, alters the nature of that thing. The Fourth Amendment becomes meaningless in a world where private companies record everything we do and provide governments with easy tools to request and analyze footage from a growing, privately owned, panopticon.
Tech giants like Microsoft and Amazon insist that facial recognition will be a lucrative boon for humanity, as long as there are proper safeguards in place. This disingenuous call for regulation is straight out of the same lobbying playbook that telecom companies have used to attack net neutrality and Silicon Valley has used to scuttle meaningful data privacy legislation. Companies are calling for regulation because they want their corporate lawyers and lobbyists to help write the rules of the road, to ensure those rules are friendly to their business models. They're trying to skip the debate about what role, if any, technology this uniquely dangerous should play in a free and open society. They want to rush ahead to the discussion about how we roll it out.
We need spaces that are free from government and societal intrusion in order to advance as a civilization.
Facial recognition is spreading very quickly. But backlash is growing too. Several cities have already banned government entities, including police and schools, from using biometric surveillance. Others have local ordinances in the works, and there's state legislation brewing in Michigan, Massachusetts, Utah, and California. Meanwhile, there is growing bipartisan agreement in U.S. Congress to rein in government use of facial recognition. We've also seen significant backlash to facial recognition growing in the U.K., within the European Parliament, and in Sweden, which recently banned its use in schools following a fine under the General Data Protection Regulation (GDPR).
At least two frontrunners in the 2020 presidential campaign have backed a ban on law enforcement use of facial recognition. Many of the largest music festivals in the world responded to Fight for the Future's campaign and committed to not use facial recognition technology on music fans.
There has been widespread reporting on the fact that existing facial recognition algorithms exhibit systemic racial and gender bias, and are more likely to misidentify people with darker skin, or who are not perceived by a computer to be a white man. Critics are right to highlight this algorithmic bias. Facial recognition is being used by law enforcement in cities like Detroit right now, and the racial bias baked into that software is doing harm. It's exacerbating existing forms of racial profiling and discrimination in everything from public housing to the criminal justice system.
But the companies that make facial recognition assure us this bias is a bug, not a feature, and that they can fix it. And they might be right. Face scanning algorithms for many purposes will improve over time. But facial recognition becoming more accurate doesn't make it less of a threat to human rights. This technology is dangerous when it's broken, but at a mass scale, it's even more dangerous when it works. And it will still disproportionately harm our society's most vulnerable members.
Persistent monitoring and policing of our behavior breeds conformity, benefits tyrants, and enriches elites.
We need spaces that are free from government and societal intrusion in order to advance as a civilization. If technology makes it so that laws can be enforced 100 percent of the time, there is no room to test whether those laws are just. If the U.S. government had ubiquitous facial recognition surveillance 50 years ago when homosexuality was still criminalized, would the LGBTQ rights movement ever have formed? In a world where private spaces don't exist, would people have felt safe enough to leave the closet and gather, build community, and form a movement? Freedom from surveillance is necessary for deviation from social norms as well as to dissent from authority, without which societal progress halts.
Persistent monitoring and policing of our behavior breeds conformity, benefits tyrants, and enriches elites. Drawing a line in the sand around tech-enhanced surveillance is the fundamental fight of this generation. Lining up to get our faces scanned to participate in society doesn't just threaten our privacy, it threatens our humanity, and our ability to be ourselves.
[Editor's Note: Read the opposite perspective here.]
Scientists Are Building an “AccuWeather” for Germs to Predict Your Risk of Getting the Flu
Applied mathematician Sara del Valle works at the U.S.'s foremost nuclear weapons lab: Los Alamos. Once colloquially called Atomic City, it's a hidden place 45 minutes into the mountains northwest of Santa Fe. Here, engineers developed the first atomic bomb.
Like AccuWeather, an app for disease prediction could help people alter their behavior to live better lives.
Today, Los Alamos still a small science town, though no longer a secret, nor in the business of building new bombs. Instead, it's tasked with, among other things, keeping the stockpile of nuclear weapons safe and stable: not exploding when they're not supposed to (yes, please) and exploding if someone presses that red button (please, no).
Del Valle, though, doesn't work on any of that. Los Alamos is also interested in other kinds of booms—like the explosion of a contagious disease that could take down a city. Predicting (and, ideally, preventing) such epidemics is del Valle's passion. She hopes to develop an app that's like AccuWeather for germs: It would tell you your chance of getting the flu, or dengue or Zika, in your city on a given day. And like AccuWeather, it could help people alter their behavior to live better lives, whether that means staying home on a snowy morning or washing their hands on a sickness-heavy commute.
Sara del Valle of Los Alamos is working to predict and prevent epidemics using data and machine learning.
Since the beginning of del Valle's career, she's been driven by one thing: using data and predictions to help people behave practically around pathogens. As a kid, she'd always been good at math, but when she found out she could use it to capture the tentacular spread of disease, and not just manipulate abstractions, she was hooked.
When she made her way to Los Alamos, she started looking at what people were doing during outbreaks. Using social media like Twitter, Google search data, and Wikipedia, the team started to sift for trends. Were people talking about hygiene, like hand-washing? Or about being sick? Were they Googling information about mosquitoes? Searching Wikipedia for symptoms? And how did those things correlate with the spread of disease?
It was a new, faster way to think about how pathogens propagate in the real world. Usually, there's a 10- to 14-day lag in the U.S. between when doctors tap numbers into spreadsheets and when that information becomes public. By then, the world has moved on, and so has the disease—to other villages, other victims.
"We found there was a correlation between actual flu incidents in a community and the number of searches online and the number of tweets online," says del Valle. That was when she first let herself dream about a real-time forecast, not a 10-days-later backcast. Del Valle's group—computer scientists, mathematicians, statisticians, economists, public health professionals, epidemiologists, satellite analysis experts—has continued to work on the problem ever since their first Twitter parsing, in 2011.
They've had their share of outbreaks to track. Looking back at the 2009 swine flu pandemic, they saw people buying face masks and paying attention to the cleanliness of their hands. "People were talking about whether or not they needed to cancel their vacation," she says, and also whether pork products—which have nothing to do with swine flu—were safe to buy.
At the latest meeting with all the prediction groups, del Valle's flu models took first and second place.
They watched internet conversations during the measles outbreak in California. "There's a lot of online discussion about anti-vax sentiment, and people trying to convince people to vaccinate children and vice versa," she says.
Today, they work on predicting the spread of Zika, Chikungunya, and dengue fever, as well as the plain old flu. And according to the CDC, that latter effort is going well.
Since 2015, the CDC has run the Epidemic Prediction Initiative, a competition in which teams like de Valle's submit weekly predictions of how raging the flu will be in particular locations, along with other ailments occasionally. Michael Johannson is co-founder and leader of the program, which began with the Dengue Forecasting Project. Its goal, he says, was to predict when dengue cases would blow up, when previously an area just had a low-level baseline of sick people. "You'll get this massive epidemic where all of a sudden, instead of 3,000 to 4,000 cases, you have 20,000 cases," he says. "They kind of come out of nowhere."
But the "kind of" is key: The outbreaks surely come out of somewhere and, if scientists applied research and data the right way, they could forecast the upswing and perhaps dodge a bomb before it hit big-time. Questions about how big, when, and where are also key to the flu.
A big part of these projects is the CDC giving the right researchers access to the right information, and the structure to both forecast useful public-health outcomes and to compare how well the models are doing. The extra information has been great for the Los Alamos effort. "We don't have to call departments and beg for data," says del Valle.
When data isn't available, "proxies"—things like symptom searches, tweets about empty offices, satellite images showing a green, wet, mosquito-friendly landscape—are helpful: You don't have to rely on anyone's health department.
At the latest meeting with all the prediction groups, del Valle's flu models took first and second place. But del Valle wants more than weekly numbers on a government website; she wants that weather-app-inspired fortune-teller, incorporating the many diseases you could get today, standing right where you are. "That's our dream," she says.
This plot shows the the correlations between the online data stream, from Wikipedia, and various infectious diseases in different countries. The results of del Valle's predictive models are shown in brown, while the actual number of cases or illness rates are shown in blue.
(Courtesy del Valle)
The goal isn't to turn you into a germophobic agoraphobe. It's to make you more aware when you do go out. "If you know it's going to rain today, you're more likely to bring an umbrella," del Valle says. "When you go on vacation, you always look at the weather and make sure you bring the appropriate clothing. If you do the same thing for diseases, you think, 'There's Zika spreading in Sao Paulo, so maybe I should bring even more mosquito repellent and bring more long sleeves and pants.'"
They're not there yet (don't hold your breath, but do stop touching your mouth). She estimates it's at least a decade away, but advances in machine learning could accelerate that hypothetical timeline. "We're doing baby steps," says del Valle, starting with the flu in the U.S., dengue in Brazil, and other efforts in Colombia, Ecuador, and Canada. "Going from there to forecasting all diseases around the globe is a long way," she says.
But even AccuWeather started small: One man began predicting weather for a utility company, then helping ski resorts optimize their snowmaking. His influence snowballed, and now private forecasting apps, including AccuWeather's, populate phones across the planet. The company's progression hasn't been without controversy—privacy incursions, inaccuracy of long-term forecasts, fights with the government—but it has continued, for better and for worse.
Disease apps, perhaps spun out of a small, unlikely team at a nuclear-weapons lab, could grow and breed in a similar way. And both the controversies and public-health benefits that may someday spin out of them lie in the future, impossible to predict with certainty.