We are excited to announce yet another group of speakers who will share their thought-provoking ideas, groundbreaking discoveries and extraordinary passions with us this March 2-4 in Boston, MA. You can learn more about our TEDMED 2020 speakers and their work here.
At TEDMED 2020, be inspired by community led cervical cancer prevention efforts in Rwanda. In the face of drug resistant infections and global epidemics, learn about a novel innovation that’s changing how we fight viruses. Celebrate how a musical visionary is helping us deepen our understanding of the profound impact music can have on all of us.
Scientific inquiry and investigative reporting will come together to help us better understand the global health risks presented by the generic drug boom. We will examine the potential consequences of the rise of accessibility to genetic data and how neuroscience can inform the law and decisions made around human behavior. And, explore how physicians are addressing climate change, one of the social determinants of health and how all of us, as consumers, have a role to play in influencing decisions involving the environment and our health.
We hope to see you in Boston, MA this March 2-4 for these and many other exciting speakers and topics. If you have not registered yet, now is your chance to secure your spot at TEDMED 2020.
Palliative care expert and TEDMED 2018 speaker, Steve Pantilat, is a leader in transforming the healthcare system and creating innovative programs to improve the care and quality of life of people living with serious illness and their families. Watch his Talk, “Why palliative care is essential in the face of serious illness” and read his blog post below to learn more about palliative care.
As people everywhere are living longer, they are likely to spend some portion of their lives, years or even decades, with a serious illness. Receiving a diagnosis of heart failure, dementia, cancer, Parkinson’s disease, emphysema or any of the other countless chronic and life-threatening illnesses is shocking. It can send you into a tailspin with the fear that your life is over. And yet, even in the face of serious illness it is possible to experience great joy, deep love, profound gratitude and strong hope. Finding the best care you can for your serious illness is an important first step. At the same time and right alongside that care, you should get palliative care. Unfortunately, myths about palliative care keep people from asking for it and getting it. Don’t let that happen to you or to someone you love. Here are the truths behind the myths. Bottom line: palliative care can help you live better, happier, and quite possibly longer.
Myth: People with serious illness have to choose between living well and living long.
Truth: Palliative care helps you live better and just as long.
Although many people think that there has to be a trade off between length of life and quality of life and that a path that includes or focuses on palliative care will result in shorter lifespan, rigorous studies show that palliative care can help people with serious illness live longer. In fact there is no study that shows that palliative care is associated with shorter lifespan. The truth is that studies demonstrate that palliative care helps people achieve a better quality of life, eases pain and depression, and reduces the chance that loved ones will experience depression or complicated grief after the person dies.
Myth: Palliative care is just end-of-life care, so if you are not dying now, it’s not for you.
Truth: It’s always the right time for palliative care.
Many people ask when is the right time for palliative care. The answer is that it’s always the right time for palliative care for someone with a serious illness. Of course, if we always wait for the “right time” for palliative care, then palliative care will come near the end of life and be seen as a marker of things going poorly. Don’t be fooled by this self-fulfilling prophecy. Ask for, demand, palliative care whenever you are diagnosed with a serious illness. Palliative care is also of great help to patients and their loved ones near the end of life. A palliative care team, or hospice, at the end of life can help you be comfortable, dignified, and peaceful at the end. And for times when the end of life is more chaotic than peaceful, as sometimes happens, having an experienced team to help out is even more important.
Myth: Palliative care can show you the right way to die.
Truth: There is no best or right way to approach serious illness and end of life.
There is no one right way to approach the end of life, just as there is no one right way to approach life. Decisions about the kind of care you want when faced with serious illness are very personal and based on many issues including your culture, religion, personal experiences and outlook on life. For all the talk about a good death, we can’t really make death good—it’s just sad and filled with grief and loss. Nothing good about that. But we can do our best to make the end of life peaceful, comfortable and dignified. Thinking about it in advance and facing it head on can make it more likely to be peaceful than chaotic. More important, we should focus on living, and making our lives, even with serious illness as fulfilling, meaningful, and good as possible. Palliative care can help.
My grandmother used to sign my birthday cards with the wish that I should live to one hundred and twenty. Moses lived that long and she wished that for me, too. As she got older, my grandmother changed it just a bit. In Hebrew, she changed just one letter and turned the wish upside down. Instead of writing, “live to one hundred and twenty” she wrote, “live to one hundred like twenty.” Live long and live well. My grandmother knew that a good life was as important as a long one. She would have told you to get palliative care, and she would have been right.
At TEDMED 2018 David Asch shared how he advances individual and population health by improving how physicians and patients make decisions in health care and in everyday life, including the use of medical treatments and personal health behaviors. Watch his Talk “Why it’s so hard make healthy decisions” and read his blog post below to understand more about the role irrationality and predictability play in decision making and why behavioral economics is such a powerful tool in health.
Health programs are more likely to be successful if they reflect how real people make real decisions.
If everyone did what was in his or her own best interest, no one would smoke, everyone would wear seatbelts, and most people would skip dessert. The simple observation that plenty of people do things that they know in their hearts isn’t good for them is partly a story about the limits of human willpower. It’s also a story about the trap of assuming that people are rational. We fall into that trap when we believe that helping people understand how to improve their health is enough to help them actually improve their health. Often it isn’t. We often do things that compete with our own best interest not because we don’t know what to do, but because even though we know what to do, we don’t do it.
Do any of these examples sound like you?
Sally is at an event where chocolate cake is served for dessert. Sally knows that the cake will throw her off her diet, but it is right in front of her, and it looks so luscious and, well, the diet can take a break until tomorrow…
Joe knows that regularly taking his high blood pressure medication is one of the best ways to avoid the kind of devastating stroke that dramatically changed his father’s life. But as he heads to bed for the evening and realizes he didn’t take his medication, he decides not to turn around and head back to the medicine cabinet…
Sally and Joe have present bias—meaning that they pay more attention to the outcomes that are right in front of them (like that chocolate cake) than the even-more-important outcomes that are in the future (like losing weight). They aren’t alone. I have present bias, and so do we all.
Reggie buys a lottery ticket on his way to work every day, and he always plays the same number. He dreams about what he’d do if he won, and although the odds are small, people win all the time. And he never misses a day because what if his number came up on just the day he missed buying a ticket!
Like Reggie, each of us sometimes overestimates small chances—focusing on the outcome rather than its likelihood. And each of us sometimes has regret aversion: we hate that feeling of missing out, that life would have been better if only we had done things differently. If only we had bought that stock when it was low. We all feel this way sometimes, just like we all overestimate small chances, and all focus too much on the present and not enough on the future.
Sally, Joe, and Reggie are not behaving in ways that best help them achieve their goals. But they are making the mistakes we all make.
So why do we continue to design tepid health programs based on a belief that people will do as they should? We do so because our first assumption is that people will behave with their own best interests in mind—that they will behave rationally. But often, we are irrational.
Behavioral economics is based on this recognition. We don’t always do what is in our own best interest. Our decisions are subject to emotion, to framing, to social context. But the key contribution of behavioral economics is recognizing we are irrational in highly predictable ways. It is the predictability of our psychological foibles that allows us to design strategies to overcome them. Forewarned is forearmed.
That’s why behavioral economics is such a powerful tool in health. For example, we can use behavioral economics to help people take their medications as prescribed. Perhaps we offer rewards to help them to do so—making the benefits of taking medicine seem relevant today, unlike the potential avoidance of a stroke years down the line. We can set up rewards in lottery formats because the difficulty interpreting small probabilities makes lottery incentives even more potent. We can make patients eligible for rewards only if they took their medicine the day before, harnessing the human tendency to avoid regret.
These approaches work because they see past how we would like people to make decisions and toward how they actually do so. They work because they hitch our health care wagon to the behaviors and mental approaches we already follow. They make the right choice the easy choice because they harness our own, predictable, irrationality instead of trying to compete with it.
We are thrilled to share another round of impressive speakers for TEDMED 2020 this coming March 2-4. These revolutionary thinkers are shaking up the status quo, from transforming how we care for our society’s most vulnerable populations to shifting our perceptions on aging and death, to using AI and crowdsourcing to revolutionize patient diagnosis. We’ll be fascinated by the possibilities of the bio-imaging revolution and discuss the art and the science behind a new platform focused on driving innovation that works toward preventing the next pandemic. The range of topics and ideas shared will inspire us all. You can learn more about the speakers and their groundbreaking work here.
Look out for another speaker announcement coming soon! Don’t miss your chance to register for TEDMED 2020 at our special Early Bird rate. Hope to see you there.
TEDMED: In your 2018 TEDMED Talk, you impart the importance of trying to stop pandemics before they start. You posit one way to begin to do this is to find patterns and test out new solutions for “everyday killer viruses” that can jump from animals to people, like rabies, but are not necessarily pandemics. What led you to choose to study rabies over another virus?
Daniel Streicker: In short, I followed the data and it led to rabies. Just consider the numbers— whereas many viruses jump into people or domestic animals only every few years or every few decades, rabies is transmitted from wild animals into new species every single day, probably hundreds of times over and governments around the world routinely carry out diagnostics on these cases. That means we get a high-resolution glimpse into the host jumping process: which hosts are involved, where it happens and when. The other thing that struck me about rabies was that we already knew so much about its basic biology. The decades of work done before me meant that I didn’t need to waste much time working out the fundamentals and could jump straight into what for me were the most exciting questions about anticipating and blocking transmission between species.
TM: Your research took you to the Peruvian Amazon to study rabies in vampire bats. You mention mudslides, power outages and stomach bugs among the challenges you encountered. What was the most difficult part of working in the field?
DS: I never worried too much about the uncontrollable things like getting sick or natural disasters. It was the things I thought I could control, but couldn’t and the things that seemed straightforward, but weren’t, that pushed me to the limit. In the first two years of the project in Peru, I tried to pack much more in than was humanly possible. Every time a key person arrived late, or our transportation didn’t show up, or bats were mysteriously difficult to catch, the realization that the day was lost stressed me out to no end. My solution was to work harder on less and less sleep. Looking back, I’m surprised the field team didn’t mutiny. After about 6 months, I remember walking down a street in Lima feeling like a sleep-deprived zombie, and suddenly realizing that no matter how much planning and wishful thinking I did, things would almost always go wrong in ways that I couldn’t predict. The only solution was to give myself a few extra weeks on both ends of every trip and go with the flow. That seems blindingly obvious now, but it took a lot of pain and frustration for me to get there.
TM: What impact has your research had on the communities you worked in that were facing a high prevalence of rabies transmittal?
DS: My longer term vision of preventing human and animal rabies by vaccinating bats is still a ways off, but I believe the road to getting there does provide tangible benefits. We have already made some progress with models that forecast rabies risk so this can potentially enable anticipatory vaccination before outbreaks begin, which would save lives. Beyond that, the nature of the work means we get exceptional access to remote communities in the Andes and Amazon that are typically underserved with respect to health access and education. This provides constant opportunities to talk to communities about the research we are doing and what actions they can take now to protect themselves and their animals (for example, using bed nets to prevent human bites or vaccinating livestock). I’d also like to think seeing us capture, handle and collect samples from mysterious animals like bats inspires some natural curiosity in younger generations and might even let them see science as a career possibility.
TM: You shared that you and your team have used genomics to forecast outbreaks and are working on an edible self-spreading vaccine that can “get rid of viruses at their source before they have a chance to jump to people”. What other creative or innovative tactics have you and your team employed in your efforts?
DS: One of my favorite things about science is that you occasionally get the chance to chase unconventional ideas. One of those was a recent project where a few colleagues and I became convinced that it might be possible to use machine learning to mine the genome sequences of viruses to predict what host they came from. This was a major challenge since when new viruses emerge, it’s almost always from a non-human animal, but it can take years or even decades of experiments and surveillance to find the culprit and while all that research is happening, the disease is free to emerge again. Although there’s still a lot of work to do in this area, we ended up developing algorithms published in Science that when provided, just a single viral genome can instantaneously predict which kinds of animals the virus came from. That effectively narrows the short list of animals for researchers to consider and in some cases could even guide how outbreaks are managed in real time to limit onward transmission.
TM: What do you see for the future of virus control/eradication?
DS: I think right now is an incredibly exciting time for disease control. We have technologies at our fingertips that just a few years ago were almost unimaginable. Transmissible vaccines are the example I discussed in my Talk, but other approaches like engineering pathogen resistance into hosts or using natural enemies or symbionts to control human pathogens like malaria or dengue within the mosquito vectors that transmit them are also taking off and show great promise. More and more the scientific question is not whether these tools work in the lab (we know they do), but how to apply them in the real world. That creates an interesting interdisciplinary challenge that will need to involve collaborations among the laboratory scientists developing the technologies, the field biologists who understand the natural systems, the epidemiologists who can project the outcomes on disease transmission, and the social scientists who can evaluate the economic costs and acceptability to the public. That last challenge is crucial since interventions in natural systems, particularly those involving genetic engineering of hosts or vaccines, are bound to be controversial. My view is that it’s vital to recognize in these situations that inaction costs lives. Rational, evidence-based assessment of the risks and benefits of these technologies will be increasingly important so we can actually realize the potential that new technologies have to transform human and animal health.
We are excited to begin sharing the speakers who will take the stage this coming March 2-4 in Boston, MA at TEDMED 2020. The first group of speakers we’re sharing is revolutionizing the way we think about health and enabling new ways to achieve a healthier humanity. You can learn more about the speakers and their fascinating work here.
We’ll be sharing more in the next few weeks, including this year’s session themes, so be sure to keep an eye out. You won’t want to miss this year’s event—register today!
Massive Science is a digital science media publication that brings together scientists and the science-curious public. The team at Massive joined us at TEDMED 2018 and covered talks by various speakers including Daniel Streicker. Check out their coverage of Streicker’s 2018 TEDMED Talk below.
Many of the world’s deadliest viruses didn’t originate in humans. Rabies, HIV, and Ebola are just three of the countless illnesses that have jumped from animals to humans. Known as zoonotic diseases, this kind of cross-species transmission is actually not an exception, but a norm. So in order to protect people from dangerous new diseases, we must first understand where and how people might be exposed in the first place.
Tracking the transmission of viruses across species is a monumental task. To do so, scientists conduct field research in far-flung places, often on multiple species—all hopefully without contracting diseases themselves. Take, for example, the deadly rabies virus, which is found in many animal species, including bats. Daniel Streicker is a senior research fellow at the University of Glasgow who has been working with collaborators in Peru to track the spread of rabies. Streicker’s been traveling to different barns and caves across Peru and hoisting nets around the exits, capturing vampire bats in order to tag and sample them. For Streicker and his research team, understanding how rabies is transmitted by bats was the first step toward learning what viral and host characteristics impact disease transmission generally.
While we may be racing against fast-evolving viruses, there’s no doubt human ingenuity is playing defense.
Just as Streicker started this project in Peru, the region began battling a rabies outbreak. Vampire bats typically live south of the United States border with Mexico (at least for now), and are particularly problematic because of their feeding habits: Since they bite other animals to feed, they’re “the perfect vector for this disease,” says Striecker.
While strategies to contain rabies transmission from dogs and bats are well established in North America, Latin America still suffers from widespread outbreaks. The numbers of cases have decreased, but many thousands of animals in Latin America still die of rabies every year. Especially in rural areas, which have limited public health infrastructure, the prevalence of the virus makes it dangerous for humans and animals alike. For farmers in particular, rabid bats are a constant fear. If a rabies outbreak from bats reaches their lands, livestock infections pose not only a health risk, but a problem for their pocketbook. “It doesn’t kill off thousands of livestock at once,” Streicker says, but cumulatively outbreaks are still a substantial public threat.
The researchers have learned that male bats are largely to blame for the virus’ spread, and that bat culling, a strategy used to reduce rabies transmission, may in fact, hurt the effort to stop rabies virus.
Streicker and his colleagues have been collecting DNA and RNA sequences from vampire bats, as well as other environmental DNA. By tracing and comparing the variations in these sequences, Streicker and his collaborators have learned more about how the rabies virus has moved around Peru. Their phylogenetic analysis works like this: Imagine 100 people start in the center of town for a bar crawl. Groups of people head in the directions of their favorite stops. At the end of the night, by comparing who went to which bar, you have an idea of who drank together. The variation within the sequences Streicker collects from DNA and RNA samples provides the same information about the rabies virus and bat populations. We now know, for example, how far the virus can travel in a year, and what areas may be most at risk. The researchers have learned that male bats are largely to blame for the virus’ spread, and that bat culling, a strategy used to reduce rabies transmission, may in fact, hurt the effort to stop rabies virus, since possibly infected bats typically disperse to new areas after populations are culled
To minimize public health risks, Streicker emphasizes the need to “control rabies in the bats themselves.” Luckily, a United States Geologic Survey researcher, Tonie Rocke has been studying bats in captivity to develop an innovative vaccine. Unlike normal vaccines, which would be unfeasible to deliver to wild populations, Rocke’s invention can be transmitted directly from bat to bat through skin contact. Combined with Streicker’s research, the scientists are hoping to target at-risk populations, like bats who live near a known outbreak. While these strategies may reduce outbreaks within five years, Streicker’s ultimate goal is a long-term solution. “It would be nice to have something to target elimination, more than just localized prevention.”
The insights these scientists are gleaning about rabies transmission may also be useful in understanding other diseases. Streicker, for example, recently published a bold theory about Ebola virus. He was curious if the Ebola virus was now evolving quickly as it spread among primates, reasoning that as the virus replicated within different hosts, it would essentially self-optimize in each. Could researchers use this virus evolution as clues to which animal host new outbreaks sprang from? If so, researchers could learn critical information during early stages of epidemics, helping prevent people’s exposure.
In the paper, published in Science, Streicker and his collaborators gathered hundreds of viral sequences, and then used machine learning algorithms to predict what animal host the viruses came from. These machine learning models were able to make predictions with 72 percent accuracy. Next, Streicker and his team hope to improve the model by testing its results in the field, but it’s already a notable step towards being able to predict and respond to Ebola outbreaks. During pandemics, the ability to run genetic sequences from samples through such a model could quickly narrow down potential hosts. Such a tool would benefit many neglected diseases, including Lassa virus, and other devastating illnesses.
Improving our epidemiological toolkits is important because the future of pandemics doesn’t look great. Responding to disease outbreaks requires a complex combination of local, national, and global efforts. Being able to warn a neighboring community of a potential rabies outbreak, intelligently inoculate at-risk bat populations, or predict the host animal of a deadly new virus would give public health officials a critical headstart in combating outbreaks.
As researchers sample and sequence diverse viruses across the globe, their insights can have a direct impact on response plans for pandemics. This is precisely the goal of the Global Virome Project (GVP). Although the international effort is in early stages, an initial project called PREDICT is collecting samples from over 30 countries. The collection of these samples provides efforts like Streicker’s more data to help predict virus behavior. “Everywhere we work, the teams are a resource for public health networks, strengthening capacity for secure and safe field surveillance, as well as laboratory training.” explains Dr. Jonna Mazet, global lead of PREDICT and member of the GVP steering committee.
While we may be racing against fast-evolving viruses, there’s no doubt human ingenuity is playing defense.
About the author: Joshua Peters is a PhD student in Biological Engineering at MIT. Around two billion people in the world are infected with a microscopic bug called Mycobacterium Tuberculosis. Despite this, only a fraction develop tuberculosis. And a fraction of those infected – almost 5,000 a day – die. He puts on Stranger Things-esque protection equipment and probes these bacteria to ask, what allows them bacteria to win this tug-of-war? To understand this variation, he looks at how both human and bacteria cells change on a genetic level in response to each other, as a member of the Blainey Lab, located in the Broad Institute, and Bryson Lab, located in the Ragon Institute and MIT.
TEDMED: You mentioned in your Talk that as you became more involved in medical robotics, you realized there are many non-traditional approaches to robotics. The exosuit, a soft wearable robot being a great example of a non-traditional robot. Are there any other innovative designs in the field of medical robotics that stand out to you, or that you have worked on recently?
Kathleen O’Donnell: There are tons of interesting robotics approaches out there! I recently read an article in Nature about a system that consists of individual robotic elements that come together and behave cooperatively to achieve locomotion and other complex tasks, similar to the way that the cells of living organisms work together to achieve complex functional behaviors. This example really helps to highlight the massive diversity in robotic approaches today.
TM: New technologies often require a lot of time and money to create. Are these things the biggest barriers to creating new innovations in medical robotics?
KO: One reason that it takes so much time and money to create new innovations in medical robotics is that designs need to be iteratively tested in representative use scenarios to properly develop and validate the designs. Then you still have to begin your summative clinical and engineering testing to ensure that everything is performing safely, effectively, and in compliance with relevant regulatory agencies (such as the FDA). One thing that has really helped to accelerate the development of the exosuit is that from the very early stages, we always were able to involve stroke patients and physical therapists in the device testing, through an IRB-approved protocol. This “early and often” approach to testing with actual users of the device (both the therapists and the patients) helped to ensure that each iteration of development was helping to move us closer to our end goals and allowed us to course-correct before we got too far off track.
TM: The exosuit was adapted to address mobility issues stemming from neurological disease. Do you think soft wearable robots like the exosuit will be used in a more widespread way in the future?
KO: Absolutely! The Exosuit for Stroke Rehabilitation that I discussed during my Talk recently achieved several major milestones, including completion of a clinical trial and achievement of FDA clearance and CE marking, meaning that the exosuit is now commercially available for clinics in the US and Europe to purchase for use in their stroke rehabilitation programs, making this the first (of many) widespread clinical applications for soft exosuits. Furthermore, the technology which comprises the core functionality of the soft exosuit is essentially a platform technology that can be adapted to a wide variety of applications. By leveraging the knowledge gained from developing the exosuit for stroke rehabilitation, we can more quickly develop systems to support additional joints, such as the hip or the knee, as well as additional patient populations, such as MS, Parkinson Disease, or TBI, for example. It’s really exciting to see how the first exosuits have lead to such a robust pipeline of innovation.
TM: In your Talk, you placed a great emphasis on the fact that the focus is always the people the technology is helping, do you think your experience as a patient plays a part in this mindset?
KO: I think my experience as a patient has certainly helped me to empathize with the patients we work with, and to understand why walking ability is such a powerful component of patients’ quality of life. However, even without this experience, I think it would be impossible to work as closely as we do with patients and therapists and not develop a deep sense of empathy and understanding for the challenges they encounter on a daily basis. The teams I have worked on have always placed an emphasis on going the extra mile to “get out of the lab” and better understand the people who are using these robots and understand what they are trying to achieve, and it is this mindset which continues to be instrumental to informing the design of exosuits throughout their evolution.
TEDMED: In your 2018 TEDMED Talk and exhibit, your work depicted a digitized future. What have you learned through the process of creating this work?
Marilène Oliver: I would say that they also depict a digitised present: the majority of my daily life is spent creating and moving packets of data around and the fact that I can now be represented as a high-resolution scan dataset pretty much sums how I understand and know myself! Understanding and questioning how we are digitised – both our physical bodies and our digitized activities – is fascinating for me, as it offers powerful metaphors to think about what and who we are becoming in the digital age. Equally, finding the right processes and materials to creatively re-export and materialise that scan data has been very important. There is no question that transparent materials were best for making my early stacked sculptures, then I needed to work with neon materials so that certain features could be highlighted and tagged. Now I am working with virtual reality: material concerns could disappear completely. Reflecting on the choices that I make in order to create artworks made from scan data teaches me a lot about my relationship to digitisation.
TM: Your work has strong scientific elements in it. Have you always had an interest in science?
MO: My interest in science has grown as my work has developed. I soon realized when I started working with scan data that many of the possibilities of the technology were not available to me (both practically and poetically) as long as I didn’t understand the science behind it. I started by reading as much as I could and trying to teach myself but when I needed more structure and reliable content I applied to do a long distance MSc in Imaging at the University of Edinburgh. This has helped me greatly, not only to understand the actual science of imaging better, but also to understand the rigid structure and pressures of scientific research compared to artistic research, but there is so much I still don’t know and it feels impossible to keep up! I strongly believe in interdisciplinary research and now at the University of Alberta I have been able to bring together a fabulous team of radiologists, computer scientists, digital humanists and nurses. We are currently developing projects that will allow us to create virtual and augmented reality artworks which is very exciting.
TM: In your Talk you discuss the challenges using MRI data posed, such as it being slow to acquire and could not be reformatted, which led you to use CT scans for your muse Melanix. What other challenges did you encounter when creating your work using digitized bodies?
MO: As I explained briefly in my talk, one of the most challenging times for me was moving to Angola and waking up to the fact that Melanix was not only a medical dataset that I needed to think about as a creative resource and material, but also a symbol of first world privilege. Until moving to Angola, I had taken scan data more or less for granted, but working with Melanix in Angola where the majority of the population had little or no access to public healthcare, let alone the possibility to be scanned, caused me to radically rethink my practice and my relationship to data acquired to cure rich white people when there were still countries with endemic malaria and people still die of tetanus poisoning every day. Making art with medical data in Angola demanded I realize my position as a privileged white woman of colonial heritage, which ashamedly I hadn’t considered until that time. This technology and these concerns are far from global and digital privilege is a huge issue that threatens to exacerbate the disgusting inequalities in the world.
The ethics of data anonymization is also something I find problematic. I understand it in medical research, but when it is being used to create artworks, I question whether this is always the ‘right’ solution. I have made scores of artworks using the Melanix dataset yet I have no idea who the original subject of the scan is. I would hope the work I have made would please the original subject if she were to know about it, but as we learn more and more how the digital data we generate is used and abused by government and corporations and other individuals, I think there has to be better discussions and global agreements about the ethics of data ownership.
TM: What are you currently working on? What is your inspiration for this work?
MO: Since my talk, I have made two virtual reality artworks and sculptural installations using a new high-resolution MRI dataset acquired with researchers at the University of Alberta. Deep Connection is the first work we made using virtual reality and was inspired from experiences using the Body VR app which allows 3D medical scan datasets to be loaded into virtual reality space as a semi-transparent block of data.
When the viewer enters the Deep Connection, they see a scanned body lying prone in mid-air. The user can walk around the body and inspect it, lie underneath it and walk through it. The user can put their head inside the body: dive inside and see its inner workings, its lungs, spine, brain. Using a virtual hand, they can then take hold of the figure’s outstretched hand, trigger a 4D dataset and see figure’s heart beat and lungs breathe. When the user lets go the hand, the heart stops beating and the lungs stop breathing. Deep Connection has an interactive soundscape made by Gary James Joynes made from recordings of the MRI scanner. When the user holds the figure’s hand a human voice sings a beautiful mourning song. The VR experience is part of a sculptural installation created using the same MRI data. The installation is comprised of a row of 3 sculptures of bodies into which the VR hardware is embedded/housed. The sensors are embedded in the chest of the outer two figures, and the inner figure holds the headset, controller and guards the workstation.
Tim Lu uses his extensive background in computer programming, electrical engineering and micrcobiology to engineer cells to act as living therapeutics. At TEDMED 2018, Tim Lu shared how his work in bioengineered medicine is enabling dynamic responses to disease in previously unseen ways. Watch his Talk, “Biological engineering—the nexus between computer programming and medicine” and read his post below to learnmore about his pioneering work.
Ever since the human genome was decoded, we’ve gained considerable insights into the origins of disease. The biological programs encoded by the DNA inside our cells are highly interconnected, allowing them to orchestrate the complex activities of life. When these fine-tuned interconnections within cells and between cells go awry, disease results.
With an increasing understanding of these dysfunctional biological programs and their role in human illness, scientists are trying to develop new ways to cure disease, not simply keep it at bay. However, our current armamentarium of medicines is dominated by small-molecule drugs and biologics, such as antibodies and enzymes. Although these medicines have resulted in tremendous advancements in human health, they are fundamentally limited in their activity and are nowhere as sophisticated as the disease networks they are trying to address.
For example, these drugs distribute systemically throughout the body and are not easily activated (if more activity is needed) or suppressed (if side effects are encountered). In addition, these medicines often only target a single mechanism of action, which may be insufficient to cure diseases. The basic problem is that we are using static, simple, non-living medicines to treat indications that are inherently dynamic, multi-factorial and living.
Fortunately, while we’ve been decoding our DNA and the biological programs we’re born with, we’ve also been learning how to design DNA to create new programs in living cells. The engineering discipline of synthetic biology has the potential to create powerful new medicines that can match the complexity of disease with even more sophisticated therapeutic programs. These medicines are called (1) cell therapies, where living cells are reprogrammed with artificial DNA programs and delivered into patients, and (2) gene therapies, where the artificial DNA programs are administered directly into patients, typically using a virus or a chemical carrier.
We’re already seeing these living cell and gene therapies have an impact on certain diseases, such as acute lymphoblastic leukemia (ALL). For example, a new class of medicines called CAR-T cells are made by extracting T cells from ALL patients, engineering them to kill any cells expressing a protein called CD19, and then reinfusing the living drug into the body, wherein the CAR-T cells eliminate CD19-positive leukemia cells, as well as normal B cells. These CD19-targeting CAR-T cells have achieved tremendous success in the clinic, with more than 80 percent complete response rates in some studies.
However, we’re only scratching the surface of what is possible with current cell and gene therapies. For example, CAR-T cells don’t work particularly well against solid tumors, such as ovarian, lung and liver cancers, or difficult-to-treat liquid tumors, such as acute myeloid leukemia (AML). Solid tumors have evolved multiple ways to block T cells from being active within the tumors, so that CAR-T cells can’t exert maximal killing activity against cancer cells.
More sophisticated genetic programming through synthetic biology can help overcome this challenge. For example, CAR-T cells can be engineered not only to kill cancer cells, but also to secrete multiple additional drugs that counteract solid tumor defenses in a multi-factorial fashion. Combination therapy encoded within a living cell therapy can address the complexity of cancer disease networks and significantly improve treatment effectiveness.
Moreover, diseases, such as AML, are highly heterogeneous, so that it’s difficult to find a single antigen target that can discriminate between cancer and healthy cells. Antibodies and CAR-T cells that only go after a single target can generate significant side effects by also killing healthy cells. This isn’t a major problem with CD19-targeting therapies in ALL, because people can survive ablation of all their healthy B cells (which make antibodies) by being supplemented with antibody infusions. However, when the healthy tissues that are inadvertently killed are irreplaceable — such as stem cells, cardiac tissue or lung cells — these side effects can cause substantial toxicity.
Fortunately, we no longer have to be satisfied with drugs that only rely on a single protein to distinguish between diseased and healthy cells. Leveraging synthetic biology, we can design cell therapies to sense multiple disease biomarkers and to respond only when a specific combination of biomarkers is encountered. For example, CAR-T cells can be outfitted with a “NOT gate” program to kill tumors when they express biomarker A but NOT biomarker B, and to prevent killing of healthy tissues that express both biomarker A and B. By doing so, we can significantly increase the safety margin of these drugs and enable enhanced potency against cancer cells.
These biological programs are just a few examples of how programming sophisticated living drugs can improve therapeutic outcomes. The emerging synthetic biology toolbox also enables living medicines that can be turned on or off by administering orally dosed FDA-approved small molecule drugs. Such medicines can be narrowly targeted against specific cell types or tissues, and that can even adapt their activity to dynamic and evolving diseases. A new era of programmable drugs is coming, and has the promise to deliver cures that match the complexity of human diseases.