Regenerative medicine has come a long way, baby
The field of regenerative medicine had a shaky start. In 2002, when news spread about the first cloned animal, Dolly the sheep, a raucous debate ensued. Scary headlines and organized opposition groups put pressure on government leaders, who responded by tightening restrictions on this type of research.
Fast forward to today, and regenerative medicine, which focuses on making unhealthy tissues and organs healthy again, is rewriting the code to healing many disorders, though it’s still young enough to be considered nascent. What started as one of the most controversial areas in medicine is now promising to transform it.
Progress in the lab has addressed previous concerns. Back in the early 2000s, some of the most fervent controversy centered around somatic cell nuclear transfer (SCNT), the process used by scientists to produce Dolly. There was fear that this technique could be used in humans, with possibly adverse effects, considering the many medical problems of the animals who had been cloned.
But today, scientists have discovered better approaches with fewer risks. Pioneers in the field are embracing new possibilities for cellular reprogramming, 3D organ printing, AI collaboration, and even growing organs in space. It could bring a new era of personalized medicine for longer, healthier lives - while potentially sparking new controversies.
Engineering tissues from amniotic fluids
Work in regenerative medicine seeks to reverse damage to organs and tissues by culling, modifying and replacing cells in the human body. Scientists in this field reach deep into the mechanisms of diseases and the breakdowns of cells, the little workhorses that perform all life-giving processes. If cells can’t do their jobs, they take whole organs and systems down with them. Regenerative medicine seeks to harness the power of healthy cells derived from stem cells to do the work that can literally restore patients to a state of health—by giving them healthy, functioning tissues and organs.
Modern-day regenerative medicine takes its origin from the 1998 isolation of human embryonic stem cells, first achieved by John Gearhart at Johns Hopkins University. Gearhart isolated the pluripotent cells that can differentiate into virtually every kind of cell in the human body. There was a raging controversy about the use of these cells in research because at that time they came exclusively from early-stage embryos or fetal tissue.
Back then, the highly controversial SCNT cells were the only way to produce genetically matched stem cells to treat patients. Since then, the picture has changed radically because other sources of highly versatile stem cells have been developed. Today, scientists can derive stem cells from amniotic fluid or reprogram patients’ skin cells back to an immature state, so they can differentiate into whatever types of cells the patient needs.
In the context of medical history, the field of regenerative medicine is progressing at a dizzying speed. But for those living with aggressive or chronic illnesses, it can seem that the wheels of medical progress grind slowly.
The ethical debate has been dialed back and, in the last few decades, the field has produced important innovations, spurring the development of whole new FDA processes and categories, says Anthony Atala, a bioengineer and director of the Wake Forest Institute for Regenerative Medicine. Atala and a large team of researchers have pioneered many of the first applications of 3D printed tissues and organs using cells developed from patients or those obtained from amniotic fluid or placentas.
His lab, considered to be the largest devoted to translational regenerative medicine, is currently working with 40 different engineered human tissues. Sixteen of them have been transplanted into patients. That includes skin, bladders, urethras, muscles, kidneys and vaginal organs, to name just a few.
These achievements are made possible by converging disciplines and technologies, such as cell therapies, bioengineering, gene editing, nanotechnology and 3D printing, to create living tissues and organs for human transplants. Atala is currently overseeing clinical trials to test the safety of tissues and organs engineered in the Wake Forest lab, a significant step toward FDA approval.
In the context of medical history, the field of regenerative medicine is progressing at a dizzying speed. But for those living with aggressive or chronic illnesses, it can seem that the wheels of medical progress grind slowly.
“It’s never fast enough,” Atala says. “We want to get new treatments into the clinic faster, but the reality is that you have to dot all your i’s and cross all your t’s—and rightly so, for the sake of patient safety. People want predictions, but you can never predict how much work it will take to go from conceptualization to utilization.”
As a surgeon, he also treats patients and is able to follow transplant recipients. “At the end of the day, the goal is to get these technologies into patients, and working with the patients is a very rewarding experience,” he says. Will the 3D printed organs ever outrun the shortage of donated organs? “That’s the hope,” Atala says, “but this technology won’t eliminate the need for them in our lifetime.”
New methods are out of this world
Jeanne Loring, another pioneer in the field and director of the Center for Regenerative Medicine at Scripps Research Institute in San Diego, says that investment in regenerative medicine is not only paying off, but is leading to truly personalized medicine, one of the holy grails of modern science.
This is because a patient’s own skin cells can be reprogrammed to become replacements for various malfunctioning cells causing incurable diseases, such as diabetes, heart disease, macular degeneration and Parkinson’s. If the cells are obtained from a source other than the patient, they can be rejected by the immune system. This means that patients need lifelong immunosuppression, which isn’t ideal. “With Covid,” says Loring, “I became acutely aware of the dangers of immunosuppression.” Using the patient’s own cells eliminates that problem.
Microgravity conditions make it easier for the cells to form three-dimensional structures, which could more easily lead to the growing of whole organs. In fact, Loring's own cells have been sent to the ISS for study.
Loring has a special interest in neurons, or brain cells that can be developed by manipulating cells found in the skin. She is looking to eventually treat Parkinson’s disease using them. The manipulated cells produce dopamine, the critical hormone or neurotransmitter lacking in the brains of patients. A company she founded plans to start a Phase I clinical trial using cell therapies for Parkinson’s soon, she says.
This is the culmination of many years of basic research on her part, some of it on her own cells. In 2007, Loring had her own cells reprogrammed, so there’s a cell line that carries her DNA. “They’re just like embryonic stem cells, but personal,” she said.
Loring has another special interest—sending immature cells into space to be studied at the International Space Station. There, microgravity conditions make it easier for the cells to form three-dimensional structures, which could more easily lead to the growing of whole organs. In fact, her own cells have been sent to the ISS for study. “My colleagues and I have completed four missions at the space station,” she says. “The last cells came down last August. They were my own cells reprogrammed into pluripotent cells in 2009. No one else can say that,” she adds.
Future controversies and tipping points
Although the original SCNT debate has calmed down, more controversies may arise, Loring thinks.
One of them could concern growing synthetic embryos. The embryos are ultimately derived from embryonic stem cells, and it’s not clear to what stage these embryos can or will be grown in an artificial uterus—another recent invention. The science, so far done only in animals, is still new and has not been widely publicized but, eventually, “People will notice the production of synthetic embryos and growing them in an artificial uterus,” Loring says. It’s likely to incite many of the same reactions as the use of embryonic stem cells.
Bernard Siegel, the founder and director of the Regenerative Medicine Foundation and executive director of the newly formed Healthspan Action Coalition (HSAC), believes that stem cell science is rapidly approaching tipping point and changing all of medical science. (For disclosure, I do consulting work for HSAC). Siegel says that regenerative medicine has become a new pillar of medicine that has recently been fast-tracked by new technology.
Artificial intelligence is speeding up discoveries and the convergence of key disciplines, as demonstrated in Atala’s lab, which is creating complex new medical products that replace the body’s natural parts. Just as importantly, those parts are genetically matched and pose no risk of rejection.
These new technologies must be regulated, which can be a challenge, Siegel notes. “Cell therapies represent a challenge to the existing regulatory structure, including payment, reimbursement and infrastructure issues that 20 years ago, didn’t exist.” Now the FDA and other agencies are faced with this revolution, and they’re just beginning to adapt.
Siegel cited the 2021 FDA Modernization Act as a major step. The Act allows drug developers to use alternatives to animal testing in investigating the safety and efficacy of new compounds, loosening the agency’s requirement for extensive animal testing before a new drug can move into clinical trials. The Act is a recognition of the profound effect that cultured human cells are having on research. Being able to test drugs using actual human cells promises to be far safer and more accurate in predicting how they will act in the human body, and could accelerate drug development.
Siegel, a longtime veteran and founding father of several health advocacy organizations, believes this work helped bring cell therapies to people sooner rather than later. His new focus, through the HSAC, is to leverage regenerative medicine into extending not just the lifespan but the worldwide human healthspan, the period of life lived with health and vigor. “When you look at the HSAC as a tree,” asks Siegel, “what are the roots of that tree? Stem cell science and the huge ecosystem it has created.” The study of human aging is another root to the tree that has potential to lengthen healthspans.
The revolutionary science underlying the extension of the healthspan needs to be available to the whole world, Siegel says. “We need to take all these roots and come up with a way to improve the life of all mankind,” he says. “Everyone should be able to take advantage of this promising new world.”
Ethan Lindenberger, the Ohio teenager who sought out vaccinations after he was denied them as a child, recently testified before Congress about why his parents became anti-vaxxers. The trouble, he believes, stems from the pervasiveness of misinformation online.
There is evidence that 'educating' people with facts about the benefits of vaccination may not be effective.
"For my mother, her love and affection and care as a parent was used to push an agenda to create a false distress," he told the Senate Committee. His mother read posts on social media saying vaccines are dangerous, and that was enough to persuade her against them.
His story is an example of how widespread and harmful the current discourse on vaccinations is—and more importantly—how traditional strategies to convince people about the merits of vaccination have largely failed.
As responsible members of society, all of us have implicitly signed on to what ethicists call the "Social Contract" -- we agree to abide by certain moral and political rules of behavior. This is what our societal values, norms, and often governments are based upon. However, with the unprecedented rise of social media, alternative facts, and fake news, it is evident that our understanding—and application—of the social contract must also evolve.
Nowhere is this breakdown of societal norms more visible than in the failure to contain the spread of vaccine-preventable diseases like measles. What started off as unexplained episodes in New York City last October, mostly in communities that are under-vaccinated, has exploded into a national epidemic: 880 cases of measles across 24 states in 2019, according to the CDC (as of May 17, 2019). In fact, the Unites States is only eight months away from losing its "measles free" status, joining Venezuela as the second country out of North and South America with that status.
The U.S. is not the only country facing this growing problem. Such constant and perilous reemergence of measles and other vaccine-preventable diseases in various parts of the world raises doubts about the efficacy of current vaccination policies. In addition to the loss of valuable life, these outbreaks lead to loss of millions of dollars in unnecessary expenditure of scarce healthcare resources. While we may be living through an age of information, we are also navigating an era whose hallmark is a massive onslaught on truth.
There is ample evidence on how these outbreaks start: low-vaccination rates. At the same time, there is evidence that 'educating' people with facts about the benefits of vaccination may not be effective. Indeed, human reasoning has a limit, and facts alone rarely change a person's opinion. In a fascinating report by researchers from the University of Pennsylvania, a small experiment revealed how "behavioral nudges" could inform policy decisions around vaccination.
In the reported experiment, the vaccination rate for employees of a company increased by 1.5 percent when they were prompted to name the date when they planned to get their flu shot. In the same experiment, when employees were prompted to name both a date and a time for their planned flu shot, vaccination rate increased by 4 percent.
A randomized trial revealed the subtle power of "announcements" – direct, brief, assertive statements by physicians that assumed parents were ready to vaccinate their children.
This experiment is a part of an emerging field of behavioral economics—a scientific undertaking that uses insights from psychology to understand human decision-making. The field was born from a humbling realization that humans probably do not possess an unlimited capacity for processing information. Work in this field could inform how we can formulate vaccination policy that is effective, conserves healthcare resources, and is applicable to current societal norms.
Take, for instance, the case of Human Papilloma Virus (HPV) that can cause several types of cancers in both men and women. Research into the quality of physician communication has repeatedly revealed how lukewarm recommendations for HPV vaccination by primary care physicians likely contributes to under-immunization of eligible adolescents and can cause confusion for parents.
A randomized trial revealed the subtle power of "announcements" – direct, brief, assertive statements by physicians that assumed parents were ready to vaccinate their children. These announcements increased vaccination rates by 5.4 percent. Lengthy, open-ended dialogues demonstrated no benefit in vaccination rates. It seems that uncertainty from the physician translates to unwillingness from a parent.
Choice architecture is another compelling concept. The premise is simple: We hardly make any of our decisions in vacuum; the environment in which these decisions are made has an influence. If health systems were designed with these insights in mind, people would be more likely to make better choices—without being forced.
This theory, proposed by Richard Thaler, who won the 2017 Nobel Prize in Economics, was put to the test by physicians at the University of Pennsylvania. In their study, flu vaccination rates at primary care practices increased by 9.5 percent all because the staff implemented "active choice intervention" in their electronic health records—a prompt that nudged doctors and nurses to ask patients if they'd gotten the vaccine yet. This study illustrated how an intervention as simple as a reminder can save lives.
To be sure, some bioethicists do worry about implementing these policies. Are behavioral nudges akin to increased scrutiny or a burden for the disadvantaged? For example, would incentives to quit smoking unfairly target the poor, who are more likely to receive criticism for bad choices?
The measles outbreak is a sober reminder of how devastating it can be when the social contract breaks down.
While this is a valid concern, behavioral economics offers one of the only ethical solutions to increasing vaccination rates by addressing the most critical—and often legal—challenge to universal vaccinations: mandates. Choice architecture and other interventions encourage and inform a choice, allowing an individual to retain his or her right to refuse unwanted treatment. This distinction is especially important, as evidence suggests that people who refuse vaccinations often do so as a result of cognitive biases – systematic errors in thinking resulting from emotional attachment or a lack of information.
For instance, people are prone to "confirmation bias," or a tendency to selectively believe in information that confirms their preexisting theories, rather than the available evidence. At the same time, people do not like mandates. In such situations, choice architecture provides a useful option: people are nudged to make the right choice via the design of health delivery systems, without needing policies that rely on force.
The measles outbreak is a sober reminder of how devastating it can be when the social contract breaks down and people fall prey to misinformation. But all is not lost. As we fight a larger societal battle against alternative facts, we now have another option in the trenches to subtly encourage people to make better choices.
Using insights from research in decision-making, we can all contribute meaningfully in controversial conversations with family, friends, neighbors, colleagues, and our representatives — and push for policies that protect those we care about. A little more than a hundred years ago, thousands of lives were routinely lost to preventive illnesses. We've come too far to let ignorance destroy us now.
New Tech Can Predict Breast Cancer Years in Advance
Every two minutes, a woman is diagnosed with breast cancer. The question is, can those at high risk be identified early enough to survive?
New AI software has predicted risk equally well in both white and black women for the first time.
The current standard practice in medicine is not exactly precise. It relies on age, family history of cancer, and breast density, among other factors, to determine risk. But these factors do not always tell the whole story, leaving many women to slip through the cracks. In addition, a racial gap persists in breast cancer treatment and survival. African-American women are 42 percent more likely to die from the disease despite relatively equal rates of diagnosis.
But now those grim statistics could be changing. A team of researchers from MIT's Computer Science and Artificial Intelligence Laboratory have developed a deep learning model that can more accurately predict a patient's breast cancer risk compared to established clinical guidelines – and it has predicted risk equally well in both white and black women for the first time.
The Lowdown
Study results published in Radiology described how the AI software read mammogram images from more than 60,000 patients at Massachusetts General Hospital to identify subtle differences in breast tissue that pointed to potential risk factors, even in their earliest stages. The team accessed the patients' actual diagnoses and determined that the AI model was able to correctly place 31 percent of all cancer patients in the highest-risk category of developing breast cancer within five years of the examination, compared to just 18 percent for existing models.
"Each image has hundreds of thousands of pixels identifying something that may not necessarily be detected by the human eye," said MIT professor Regina Barzilay, one of the study's lead authors. "We all have limited visual capacities so it seems some machines trained on hundreds of thousands of images with a known outcome can capture correlations the human eye might not notice."
Barzilay, a breast cancer survivor herself, had abnormal tissue patterns on mammograms in 2012 and 2013, but wasn't diagnosed until after a 2014 image reading, illustrating the limitations of human processing alone.
MIT professor Regina Barzilay, a lead author on the new study and a breast cancer survivor herself.
(Courtesy MIT)
Next up: The MIT team is looking at training the model to detect other cancers and health risks. Barzilay recalls how a cardiologist told her during a conference that women with heart diseases had a different pattern of calcification on their mammograms, demonstrating how already existing images can be used to extract other pieces of information about a person's health status.
Integration of the AI model in standard care could help doctors better tailor screening and prevention programs based on actual instead of perceived risk. Patients who might register as higher risk by current guidelines could be identified as lower risk, helping resolve conflicting opinions about how early and how often women should receive mammograms.
Open Questions: While the results were promising, it's unknown how well the model will work on a larger scale, as the study looked at data from just one institution and used mammograms supplied by just one hospital. Some risk factor information was also unavailable for certain patients during the study, leaving researchers unable to fully compare the AI model's performance to that of the traditional standard.
One incentive to wider implementation and study, however, is the bonus that no new hardware is required to use the AI model. With other institutions now showing interest, this software could lead to earlier routine detection and treatment of breast cancer — resulting in more lives saved.