TED Radio Hour - Biotech is about to change your world

Episode Date: April 18, 2025

The latest innovations in biotech are upending our approach to disease, longevity and climate change. Are we ready? This hour, TED speakers share ideas at the forefront of this new wave. Guests include co-founder of the Human Cell Atlas Aviv Regev, physical chemist Brad Ringeisen and immunoengineer Aaron Morris.TED Radio Hour+ subscribers now get access to bonus episodes, with more ideas from TED speakers and a behind the scenes look with our producers. A Plus subscription also lets you listen to regular episodes (like this one!) without sponsors. Sign-up at: plus.npr.org/ted.See pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences.NPR Privacy Policy

This is the TED Radio Hour. Each week, groundbreaking TED Talks. Our job now is to dream big. Delivered at TED conferences. To bring about the future we want to see. Around the world. To understand who we are. From those talks, we bring you speakers and ideas that will surprise you.

You just don't know what you're going to find. Challenge you. We truly have to ask ourselves, like, why is it noteworthy? And even change you. I literally feel like I'm a different person. Yes. Do you feel that way? Ideas worth spreading.

From TED and NPR. I'm Manoosh Zamoroti. About 25 years ago, the first draft of the Human Genome Project was completed. We're here to celebrate the completion of the first survey. Then President Bill Clinton, surrounded by scientists and world leaders, Most wondrous map ever produced by humankind. Praised the breakthrough project from the podium at the White House. But today's historic achievement is only a starting point.

It took another 20 years to sequence the last 8%. But meanwhile, this genetic map of the human body has led to major breakthroughs in cancer treatments, prenatal testing, and our understanding of rare diseases. It's considered a massive scientific accomplishment. And today, researchers want to go even further. So in the Human Genome Project, we only had to handle that genome. But remember, one genome yields many, many, many different kinds of cells. This is computational biologist Aviv Regev.

And so instead of just having to map this one static genome that kind of stays the same throughout the lifespan, when you look at cells, they actually change. My cells today are not the same as the cells that I had 20 years ago or 10 years ago or the ones that I will have in 10 or 20 years from now. Aviv is the co-founder of a project to map all of the types of cells in the human body. The project is called the Human Cell Atlas. She and researchers all over the world are cataloging how our cells change. and interact. The goal is to use it to develop highly personalized medical treatments.

One of the critical things we need to navigate in the human bodies are diseases. For example, I need an address for a cell if I want to go and target it with a therapy. Biologists have tried to do this for a very long time, but there's about 37.2 trillion cells in an adult human body and they do different things and behave in different ways. And there's 20,000 genes in the genome. And these genes combine to act in different ways that are not predict. If I know what happens about gene A and I know what happens with gene B, it doesn't mean that I can predict what will happen when I put A and B together. So when you start calculating the number of ways our cells and genome could combine, the possibilities are astronomical. Some of the

the numbers are larger than the numbers of atoms in the universe. So it's big. But now, thanks to artificial intelligence, scientists can identify all those cells and do these complex calculations. That shift can only happen with the AI. Aviv expects to complete the first draft of the Atlas in the next year or so. And she says the old way of understanding cells in the human body compared to the human cell Atlas will be like, comparing a 15th century map of the world to Google Maps. In a Google map, you also have many, many layers. So you can look at a Google map right and choose the Earth view, and you see the real topography.

Here are the hills, and this is where the water is. But you can also look at a Google map for traffic patterns. And when you have a map like that, you can choose that different level in order to learn the things that you need to know in order to take the right action. These are the things that we need. we often like to call them atlases because they help us navigate. It's the things we need in order to navigate the human body. If I want to develop a medicine that we'd only go to the place where something is broken

and help that cell function, help that tissue, I need to know how to get there. If you have a map, you have the zip codes. And if you have the zip codes, you can get where you want to get. And if you can get where you want to get, you can deliver a very targeted, very specific therapy that spares the rest of the body and gets only where it needs to go in order to help us be better. Those are the kinds of things that you can do with the Google map, and it's very hard to do with a map from the 15th century. And now we have something that's constantly at higher and higher resolution, and so that is extremely rich information for us to navigate.

From mapping every cell in the human body to engineering climate resilient crops, some of the biggest innovations happening right now are in biotechnology. And that is what we're bringing you today. Ideas and projects at the forefront of this new wave and how these breakthroughs are upending our approach to disease, climate change, and our longevity. Back to computational biologist Aviv Regev. Aviv says developing new medications is one of the toughest things for scientists to do. But the human Cell Atlas makes it much easier. Here she is on the TED stage. Making new medicines is really, really hard. We need to generate the next medicine, and then we need to predict the right dose for the right patient. This is not just hard and takes a lot

of time. It does. It takes about 10 years or more to develop a new medicine. But the vast majority of the time, it fails. 90% of potential drugs fail. in either pre-clinical research or in clinical trial. You can focus on the fact that it's not happening, but I prefer to think that there's something we can do. What might that be? Well, one of the greatest innovations of our generation are the great advances that have happened in machine learning and AI.

They can transform the discovery of medicines. And so, in mid-2020, I moved to Genetic to solve this problem. And so every day, when I come to work, our patient's pictures look at me from our buildings. Like Renita here, who is a patient with her two positive breast cancer. And like Renita, there are millions and millions of patients who need better medicines. Now, we haven't been idle. For example, we have developed medicines across seven major disease areas, in oncology, in neurology, in rare blood disorders.

We run currently 732 clinical trials. Last year alone, 14 million, more than 14 million patients, were treated with our medicines. These are successes, but there are successes in a field where the odds against success are 9 to 1. We absolutely have to do better than that. Explain to me what we can do now and what you see happening in the next 5, 10, 20 years.

Yeah. So first of all, we use the human cells. Atlas every single day. We use it to research and discover medicines and to develop medicines. And this is because we ask these questions every day. Which cells in the body use this disease gene? Where could I go in order to target a disease cell, but not the healthy cells of the body? What are the unique characteristics of this patient? What happens to cells when we treat? with drugs. One of the unique things that we still have to figure out is not just where are the cells, but also the answer to what would happen if I treat this patient. What would happen if I had a

therapeutic that inhibits the activity of this gene or of that gene? And those are harder questions to answer. To answer them, Aviv and her colleagues consult the cell at least, kind of like you or I might consult chat GPT. For example, researchers have been looking at a medication for lung disease that targets particular cells. She can ask the Atlas if those same cells show up in other diseases too. We said, we already know that we have a medicine that targets a particular behavior in cells. In what other diseases might we see cells like these?

And the answer that we got back was inflammatory bowel disease, alternative colitis and Crohn's disease. This was not something we expected at all. It wasn't the direction in which we were originally going to develop this therapeutic. But now we actually have a phase two clinical trial in patients based on this finding. That's the kind of stuff that a human cell atlas allows you to do. You describe it as a lab in a loop, right, that you're constantly learning and applying your learnings and trying out different sort of medications.

Do you mind just walking us through how quickly that can move now that you have this information? Yeah. So in the lab in the loop, you do different kinds of interventions. You go and you poke and you prod cells in different ways. Then you feed that into an algorithm, actually into AI, and you let it build a more. model of what it thinks is going on. That model might not be necessarily correct, but it is going to make predictions for you. And based on those predictions, you're going to go back and do another experiment and go on and on and on like that. The one that will succeed are the ones that the

algorithm learns that worked well. The one that didn't succeed also teach the algorithm about what didn't work well. It gets better. It makes a new set of predictions. And you iterate and iterate, it is giving you a good enough answer that you can start making an actual medicine from. And that brings us to the final step, which is the patient, the ultimate step for us. But there is many patients in the world, and they're not all the same,

and we have to provide the right medicine to the right patient, and sometimes we have to personalize this medicine to the patient. A notable example of that is in cancer. Tumors are different. Every patient's tumor is different. They have a lot of mutations in them. Some of these mutations are entirely private to the patient. These mutations are very important.

They are identified by our immune systems, by our T cells in the immune system. They see them in the same way that they see viruses, and they kill the cancer cell. What if, just like a vaccine against a virus, we could devise a vaccine against cancer, that we target the immune cells against the cancer cells. But the mutations are private. We need to make the vaccine personalized. Here comes our lab in a loop.

We take the patient's tumor. We sequence this. We identify the mutation. And we use a transformer model trained on previous data in order to identify those mutations that would trigger the immune system. We collect a collection of these mutations and we make them into a personalized cancer vaccine

just for this patient. And as we treat the patient, we monitor their immune response. We use this information to improve the model for the benefit of all. I mean, we're talking about the advent, finally, of really personalized medicine. This is huge, right? Like cancer patients will be able to get a vaccine that nobody else will have.

It will be formulated just for them. Yeah, highly personalized medicine that the cancer patient can receive after their diagnosis and that will trigger the immune system to control the, the, you know, microscopic tumor that might have remained in the patient's body and that you cannot remove by surgery, resection, and so on. In a moment, Aviv shares how AI and the human cell Atlas could go so far as to predict if someone will develop a disease and treat it before it even starts. On the show today, the new wave of biotechnology.

I'm Manus Zameroody, and you're listening to the TED Radio Hour from NPR. NPR. We'll be right back. It's the TED Radio Hour from NPR. I'm Manoosh Zamorodi. On the show today, the new wave of biotechnology. And we were just talking to Aviv Regev, one of the founders of the Human Cell Atlas Project, a mapping of every type of human cell and how they interact with genes. Aviv is now working at Genentech, where she and other scientists are applying this new knowledge to create personalized medical treatments. Imagine a vaccine formulated just for you based on your genetic and cellular profile.

But her other goal is to predict and prevent disease from developing in the first place. Can I ask you about the future of preventative care? One of the things or one of the teams working on the Cell Atlas has produced a blueprint of how huge, human skeletons form in utero. And one of them found that certain genes were activated in early bone cells that might be linked to an increased risk of developing hip arthritis as an adult. So I guess I'm wondering, you know, in the future, when your baby is born, will a doctor be saying, okay, well, based on what we know about your newborn, they have these sorts of proclivities towards these diseases.

So make sure you get these vitamins and make sure you get this sort of vaccine at this point. You know, we won't even have to develop the diseases because we'll nip them in the bud because we know the blueprint. Yes, there are huge diagnostic and prognostic opportunities, not just when you already have disease, but also well ahead of them.

And there is a lot to say about that. The first actually starts with human genetics, which is the ability to look at your genome and assess some of your risk. We already know that we can assess the risk for some really serious conditions, which are really driven by a single gene. For example, if you have a certain mutation in your BRCA-1 gene, then your risk of breast cancer is substantially increased,

and it changes how your doctor will monitor you and how you will be cared for throughout your life. But now we can actually look across information from a lot of our genes combined together. This is actually something known as the polygenic risk score. And for certain diseases, you can start making these assessments for people who have especially substantially increased risk. And I think this would be fantastic because most of our focus has been on looking at disease after it already exists.

This gives so many opportunities for preventative care. I guess could you just paint a picture for us about how you think the field of medicine and biotechnology will be different for the patient in the long term, 20 years, 30 years, 40 years. What sort of mindset will we have as people when we think of how to treat illnesses that we're born with or develop over time? I think it's a great question. I'm not going to put a timeline on it, but I do think things will change substantially for patients. There are so many patients who are treated on medicines, and then they don't bring them benefit. We believe that there would be a great reduction in that pattern, and that will come from being

able to predict a lot better which patient will benefit from which medicine, so that we can come in a much more fine way rather than with broad strokes. This understanding of the cells and their internal mechanisms opens up so many possibilities there's also going to be earlier disease treatment and even preventative disease treatment that today is simply not possible. If you cannot predict that the disease will develop and you cannot provide treatment for it. But if you can and you can understand the early, early mechanisms of what happens in that disease, then you can imagine providing this therapy for the patient.

We're also going to see, I believe, therapies that are one and done more, more cure rather than continuous care. We're going to see this also with a much broader range of vaccines that can be used. Those are things that do not exist yet. And you can never tell exactly when they will exist, how impactful they would be. But it is really exciting prospects for us going forward.

And while I talk about it in the future tense, this is what people are doing right now. And it's getting better every year. Actually, it's getting better every six months. It's actually a scientific breakthrough that is happening right now. That's Aviv Regev. She is the executive vice president and head of research and early development at Genentech. And the co-founder of the Human Cell Atlas Project.

You can see her full talk at ted.com. On the show today, how a new wave of biotechnology could change our lives, including what we eat. In the 1990s, genetically modified foods or GMOs hit the market. Scientists developed these crops to make them more resistant to weeds and insects and to be more hardy so that farmers could yield more of them. But GMOs were controversial. Anti-GM activists stormed the field about a month ago. To be sure, humans have been cross-breeding plants for thousands of years. But to some, the idea of messing with the genes of organisms that they would eat sounded dangerous. There were worries that GMOs would cause allergies or antibiotic resistance or other long-term health effects.

Today, concerns remain about cross-contamination with wild species or farmers relying on GMO seeds that can withstand herbicides and pesticides. The consensus on the whole, though, is that GMOs are just as safe as non-GMOs are just as non-GMOs. GMO foods to eat, which is why you don't hear much about genetically modified food these days. That might be about to change because of CRISPR. The beauty is that this is a technology that can work on human cells. It can work on microorganisms, bacteria, and it can work on plants. This is Brad Renghuyzen. He's a physical chemist and head of the Innovative Genomics Institute.

Brad says the gene editing tool CRISPR could make it popular. to feed the world's 8 billion people without destroying our planet in the process. I think when you hear CRISPR for climate, people sometimes sort of shake their head and they don't understand the impact that this amazing technology has to help stabilize food supply into the future. So I'm old enough to remember when GMO or genetically modified crops were introduced. And there was in Europe, especially a huge uproar about this idea of genetically changing plants, seeds, so that they are resistant to insects, to heat, all those sorts of things. How is CRISPR different than what's been used for the last three or so decades?

So this is a really important question. And the good news is that CRISPR is a tremendously precise. precise tool. I think people don't understand that nature itself produces genetic changes. And that's been occurring over generations and generations of all plants in the world. But GMOs specifically really have very uncontrolled genomic changes. There are changes throughout the entire genome. And oftentimes you're doing this in a way that is not very precise. most of the food that we eat, at least in the United States, for sure, and there are very high-yielding crops called hybrid crops. Several decades ago, during the Green Revolution, people realized that you could actually cross two parents, two distinct different genetically distinct parents, and the offspring actually have better traits, better yields, much, much higher yields than the parents did.

And those are all just genetic changes that have resulted that dramatically increased yields. Well, the problem is, is that when those seeds from hybrid crops are planted the next generation, you see changes then in the genome of those seeds because the parents, some of the mix-up of genes that have occurred don't translate into that next generation. So people do not plant hybrid seeds into the next generation. So they have to go back to the seed suppliers and buy the seeds every single year. So if you enter CRISPR into this equation now, the beauty of CRISPR is that you can go into a very controlled location on the genome and make one very small change. In some cases, just at the base pair level, where you're really just making one very small change.

You're maybe just turning off a gene. In many cases, you can actually have a disease-resistant crop, for instance, where you're just changing one gene. And that's a very precise way to make controlled changes. And at least in the United States and in countries like India and many countries in Africa and South and Central America, these changes that I was just talking about, if it's done with CRISPR, actually are not considered GMOs from a regulation standpoint. So there's actually a very fast-tracked way to be able to get these CRISPR products to market around the world. Okay. So legally, the law understands the difference. I was reading about a barley trial that began in spring of 2024 in Switzerland where they're testing to see if CRISPR can increase barley grain yields. But, you know, in Switzerland, they are not GMO friendly. And so this field is enclosed by an electric fence.

It is patrolled by security and a guard dog. Yeah, I think there is a lot of misunderstanding. And Europe is still one of the holdouts that they consider even CRISPR edits, those precise edits that I talked about that could occur in nature. Europe is one of the sole holdouts that still consider those a GMO. And the regulatory aspect of that is very, very difficult in a place like Europe. But look, I've talked with the Danish ag minister. I've talked with Danish dairy farmers. And when I talk about CRISPR with the agricultural aspects in places like Germany and Denmark, the agricultural ministers are very much in support of this technology because they understand the climate implications and the greenhouse gas emissions and the threat to food security.

And so they're pushing the European Union to make changes. and they want to make those changes in support of sustainability. There's just so much impact that you can have on the world to potentially feed billions of people using this technology to do it in a sustainable way. I became the executive director of the Innovative Genomics Institute, the IGI in 2020. Here's Brad Renghuyzen on the TED stage.

The same year that our founder, Jennifer Dowden, won the Nobel Prize in Chemistry for her pioneering work in CRISPR. That's right. Let's go, Jennifer. I was drawn to the IGI as a place where CRISPR could be applied to help improve the lives of nearly every person in the world to help create a sustainable future. The work to improve food security is already underway.

Our scientists at the IGI can already edit over 30 different crops, rice, wheat, brides. broccoli, sunflowers, tomatoes. We're even trying to develop crops that can persist against emerging pathogens by knocking out disease susceptibility genes, or create drought-tolerant crops by reducing the number of pores that are on the water-losing pores on their leaves. We're even trying to save the banana and chocolate from emerging pathogens. So the idea is that you take a particular crop and, you take a particular crop, and, you're

you edit the genes so that they are more climate friendly so that they grow more heartily without using resources. Is it that simple? Yeah. Well, I mean, nothing's ever simple in science, but yes, it is, the concept is indeed that simple. And, you know, Jennifer and I have developed sort of a climate strategy at the IGI. And the first leg of that strategy is that we are looking at areas of the world that are on the front lines of climate change. So I just got back from a big trip to India where I met with a lot of agricultural scientists and government officials in India. Look, they have to feed nearly 1.4 billion people, and they're seeing a tremendous threat to their food supply. They're seeing it from heat. They're seeing it from drought. They're seeing it from floods. They're

seeing it from salinity as there's a storm. If you're growing food on the coastline, you now have to deal with ocean water that has contaminated your soils. And so what I learned in that trip to India was that it's becoming very much more difficult to predict what those threats to their food supply are going to be. There used to be traditional areas that were drought prone, traditional areas that were flood prone. And now what they're seeing is a very large degree of uncertainty. And in some of those drought-ridden areas, they're seeing floods. And in some of the flood areas, they're seeing droughts. They're seeing temperatures of 50 degrees Celsius or higher. And life is just not meant to live. Plants are not meant to live at those temperatures, which really puts a lot of stress and strain on the

food supply. And that's just one country. You're seeing this around the globe. And so what we're going to do in sort of that first leg of our climate strategy is use CRISPR to really try to build in resilience of these crops that we all eat to survive. So producing climate resilient crops, tell me more about that, what that looks like. Well, one of our partners, Pam Ronald, who just won the Wolf Prize a couple years ago at UC Davis, has worked with many collaborators to develop a flood-tolerant rice. And you would say, oh, well, rice sometimes grows underwater. Well, yeah, it grows underwater in a controlled way. But if you have a storm that comes in or several storms that come in,

and those rice plants are submerged for one week, two week, three weeks, traditional rice crops cannot survive. And so Pam's rice variety is now being growing by millions of farmers in Southeast Asia. And what you see are, I've seen pictures of farmers so proud of being able to grow this crop because they're standing next to a flooded field. And guess what? Pam's variety looks beautiful. It's this lush green field of rice. And then on the side of the traditional crop, you see a rice field that's just sort of decimated by the flood. So I think there's a real potential to scale this because one thing that biology does is scale very well. If you can generate seeds, the farmers will put those seeds in that can guarantee yields that can guarantee things like flood tolerance or temperature tolerance. And I really do think that we can scale quickly, and ultimately it helps the citizens of the world. And the rice that is then grown, having already been edited, are the seeds that come from that rice pre-edited, so to speak?

Yes, that's the beauty of this, is that you literally are editing the germ line. You're making permanent changes so that the generations and the seeds would be able to have the same traits. I was reading about these researchers in Florida who had edited sugar cane that as a result the sugar cane leaves would grow at a different angle and collect more sunlight, which was amazing. So they were stronger. So this is one of the big challenges is that all of these require genetic changes. So this concept of stacking changes, taking large amounts of genomic information and putting them into. a single crop is going to be really, really important. So can you change those branching angles? Can you, can you provide flood tolerance? Can you provide heat tolerance and put them all together? Because I think

one thing that is guaranteed in climate change and in the coming decades is that there's going to be more uncertainty. There's going to be vast oscillation of storms. One year you might have drought. The next year you might have too much rain. The next year it might be disease. And so, One thing, that certainty of uncertainty of uncertainty, I think means that you're going to have to stack these desirable traits. In a minute, more with Brad Renghisen on how CRISPR is a tool for dealing with climate change in other ways, from altering the microbiome of cows to boosting photosynthesis in plants. On the show today, the new wave of biotechnology. I'm Anousse Zamorodi, and you are listening to.

to the TED Radio Hour from NPR. Stick with us. It's the TED Radio Hour from NPR. I'm Manoosh Zamorodi. On the show today, the new wave of biotechnology. And we were just talking to Brad Renghisen from the Innovative Genomics Institute about how scientists are using CRISPR to develop crops and livestock that can withstand even help us deal with climate change. I think most of us, you know, have heard we should eat less meat because livestock are huge emitters.

We have had scientists on the show to talk about different feed that they're trying to develop to reduce the emissions that come out of all those cattle burps and the other end too. But this is a different approach with CRISPR. Yeah, it is. And I think I want to say, first of all, that we need all approaches. You know, I think the single biggest question that I get when I start talking about, cows and livestock methane emissions, is they say, Brad, why, why, why aren't we just pushing, you know, vegetarian diets and meat alternatives and cultured meat to move away from cows?

And my answer is we need all solutions. And, you know, but I think we can't ignore the fact that global meat consumption and global beef consumption specifically are still increasing around the world. So Jennifer and I have made this a priority inside the institute. Our goal at the IGI is to eliminate methane emissions. We believe that CRISPR can be used in the cow rumen to affect not the cow cells. We're not talking about cow breeding here. We're not talking about genetically modified cows. We're going to add CRISPR directly into the microbiome, what's called the rumen, the gut of the cow to shift the microbiome. We're away from a heavy methane state. And I believe, based on the experiments that I've been seeing, that we can actually create an alternative state of that microbiome where there is almost no methane being emitted. And I think that that's an exciting, really big stretch goal that we have for the IGR. Okay. So we have talked about crops and livestock emitting less, higher yields.

But the third application you're working on is using crisp. to remove carbon from the atmosphere and put it into soil. That's right. That's right. And I really do believe that it's, that is a very scalable solution to carbon dioxide removal. This brings me to my plan to help remove atmospheric carbon and return it to ag soils. And we think it's a perfect place to put carbon because those soils have already lost close to 500 gigatons of carbon dioxide equivalents since humans have started farming. What if we could use CRISPR to help put this carbon back?

It would help achieve global climate goals, but it would also let farmers help work in marginal and underutilized lands and convert those into more fertile soils, helping to reduce the need for deforestation. It's a win, win, win. So our plan is to enhance photosynthesis, to capture more carbon, to be able to edit crops,

to be able to create roots that grow deeper and more dense, to push carbon into the soil, and then ultimately work with that soil microbiome to be able to keep that carbon and have it stay put in the soil. Now, even with all that carbon that photosynthesis absorbs every year, it's actually a pretty inefficient process. But IGI scientists think we can edit those crops to improve both the way plants absorb light energy and the way that they build biomass to help improve the efficiency of photosynthesis by up to 30 percent.

That's more carbon for food and more carbon to store. So this idea of capturing carbon with plants, that's exciting. But what do you see as the next steps to getting consumers on board? Because a lot of people are still very skeptical about GMOs. So where do we go from here? Yeah, I think the biggest thing is that people understand that genetic modification is not a bad word. It's not unsafe. It's not something that has ever been proven to produce a product or food that is unsafe.

And then when you add CRISPR and genome editing into this equation, it's an even more precise tool. It's a tool that can help speed innovation. It's a tool that can help feed the world in the face of a rapidly changing climate. And it can be done in a very sustainable way, much more so sustainable than using chemical fertilizer. and spraying pesticides. We're going to be doing this in a much, much more natural way. And I'm very excited to try to keep pushing this over the next decade. That was Brad Renghuyzen.

He's a physical chemist and the executive director of the Innovative Genomics Institute. You can see his full talk at ted.npr.org. So we have talked about gene editing, artificial intelligence, and the human cell atlas. But there are all sorts of other techniques that scientists are currently developing. And so now we want to focus on one particular biotech tool that may help doctors diagnose and even predict autoimmune disorders. This is when the body attacks itself. For example, psoriasis is an autoimmune disease that results in flaky, itchy skin. That's usually diagnosed by looking at somebody.

of these skin, right? It's a rash. You can see it. But many of these diseases are much more difficult to diagnose. Aaron Morris is an assistant professor of biomedical engineering at the University of Michigan. One that we study a lot in my lab is multiple sclerosis. Multiple sclerosis is an autoimmune disease that affects the brain and the spinal cord. So it's much more difficult to diagnose. You know, you can't just look at it. And although you could potentially take a biopsy, Nobody wants you to take a biopsy of their brain or spinal cord, and you certainly can't do it repeatedly, right? It's dangerous. It's painful. Blood tests aren't helpful for diagnosing MS, Aaron says.

MRI's not really either. On an MRI, you can see lesions. So you can see spots if somebody has MS that indicate that there's been some damage, but it doesn't give you cellular or molecular information. about the disease, it's a spot on an image. By the time you have a big spot, a lot of damage is already done. In many of the conditions that we're talking about, you are monitoring symptoms, and if someone is showing symptoms, it may have already caused substantial damage. So to help doctors diagnose autoimmune diseases, Aaron's research is adding to the growing world of implantable medical devices.

The device itself looks a lot like a sponge, about the size of like a pencil eraser. This tiny device may help doctors detect disease from within the body. And when you talk about putting this under someone's skin, it's barely noticeable. Somewhere sort of by the hip, perhaps on the arm or on the wrist. So here's how it works. When the device is implanted under a patient's skin, the body sends immune cells to a attack it. This is called the foreign body response. It's basically the body's response to try to protect itself from what it sees as something that is foreign and potentially dangerous.

Usually this is a problem for doctors. It's a reason why an implant like a heart stent might fail. But the foreign body response is exactly what's making Aaron's device work. It's highly porous and we actually think that porosity is really, really important for its ability to have blood vessels form throughout it and fill up with tissue. When those immune cells arrive, they fill up that sponge-like device, forming new tissue. Doctors can take that tissue and diagnose an autoimmune disease like MS. The idea is it's just under the skin, so it's very accessible. It's easy to get to.

But it's also not a vital tissue, right? So it's not performing some essential function for somebody. It's not their brain or their heart. It's something that we made. They don't need it. And so we can biopsy it and we don't have to worry about causing damage to vital organs. I mean, that's really cool. Instead of you going to get the tissue, you get the tissue to come to you?

That's a pretty good way of putting it, yeah. Are the cells that show up to the implant going to be the same ones that are showing up let's say with MS at the brain and the spine? Like, how do you know that they're the same thing that's happening in the places that are having problems? Your inkling is probably right that it's not entirely reflective of what's happening in the brain in the spinal cord, for example. Your brain has tissue-resident immune cells called microglia that aren't coming to our

implant. They live in the brain. They don't leave the brain. And so those aren't part of our implant. But they are involved in MS. So we're not creating a perfect mimic of the brain in someone's arm, but it does contain information that's reflective of disease. Aaron says that being able to monitor the immune system will be helpful for something called relapsing remitting MS,

where patients go through periods of worsening symptoms followed by remission. If we know somebody's about to relapse, we might be able to give them a stronger drug for a short period of time to prevent that relapse from happening. But more than just diagnosing and monitoring diseases, Aaron is hoping that this technology predicts them before they develop. His device has not been tested in humans yet, but he and his team have found promising results in animal trials. We did a study where we predicted the development of the mouse model of MS before they had any symptoms. Then they gave the mice preemptive treatment. When we were able to predict and then intervene with drugs, we dramatically reduced

disease. So only one in five animals had any symptoms of disease when we did that, as opposed to all of them having symptoms of disease if we didn't. Do you envision a scenario where someone who doesn't have a disease gets one of these implants as well? I guess maybe because someone in their family had it and they think genetically they're predisposed or I don't know, would that ever happen? That wouldn't be our first indication, but I do think eventually people would want to use this for that more preventative kind of approach. An example would be if you have a first degree relative that has, say, type 1 diabetes, you have approximately a 15-fold increased risk of developing type 1 diabetes yourself. For MS, it's something like 5 to 10 fold. So it would be a personal

decision. Do you know, do you want some monitor to be able to help you predict if you're going to develop one of these conditions? Another example of this would be if you have one autoimmune disease, approximately 25% of patients with one autoimmune disease will develop another one, a comorbid autoimmune disease. So those patients, you know, they're at very high rate. for developing a second autoimmune condition. And if we're able to monitor for multiple of these different kinds of conditions, they might really want the ability to do that. The pie in the sky idea is we have already been exploring how far we can take this,

what conditions can we analyze. So at this point, we've looked at models of multiple sclerosis, type 1 diabetes, organ transplant rejection, and even metastatic cancers. And so our hope is if you can monitor, you know, dozens of different disease, it's now a very attractive proposition to have one of these implanted because, sure, your risk of any individual one is low, but in aggregate, it's much higher. I do think people are getting more used to this idea of monitoring, like on their smartphone, what's going on in their bodies. The examples I'm thinking of are I know people who have diabetes who have a constant glucose monitor. going and they can check in and it'll ping them to tell them, you know, if they're, make sure they don't forget their insulin.

Is that sort of what you see being the future for people that starts to just become normal? You have something that's in your body and it's giving you information. That is very much what I think the future of monitoring these autoimmune diseases might look like. Those implantable glucose monitors can be life-saving for diabetic patients. a similar analogy is many people where all sorts of activity trackers that are tracking their heart rate, tracking their sleep, that's certainly a rapidly growing area, this sort of massive amounts of data that people are collecting on themselves. I think, you know, knowing what your immune system is doing is something that these systems can't yet do. But if paired with technology like we're developing, perhaps they could.

And there might be a lot of utility in that data. Just, Aaron, telescope out for us. Like, you know, let's say this all goes according to plan. What could the field of medicine look like when it comes to diagnosing and treating autoimmune diseases, let's say, you know, five, ten years from now? My hope is that we'll be able to better care for patients. So we'll know that somebody is developing a disease and we'll be able to intervene before they have symptoms or we'll know someone's about to have a relapse and we'll be able to prevent it. We know that preventative medicine is better than treating once somebody is sick.

The technologies that we're making, you know, we're very interested in using them to better diagnose and better monitor patients. But that's not all that they're useful for. So they give you cellular and molecular information about disease. that cellular and molecular information is really helpful when you're thinking about designing and developing new treatments for disease. Right now, when we want to develop new treatments, we do a lot of work in animal models, but it would be nice to know what the detailed molecular pathologies are in humans. We have some of this information, but we don't have a complete picture.

And some of the reason we don't have a complete picture is the same problem as it is with the diagnostics. It's really hard to get that information. How do you get the information about dynamics of cell-cell interactions in someone's brain? And we've actually shown in an animal model of MS that we're able to dig in and really look at how cells are communicating with each other. And we can use that to get a detailed picture of the cellular and molecular changes of disease that we can target with therapies. And we're learning. And we're learning. learning more that every single person is their own special soup of different molecules and biomarkers and how they live, their environment, combined with their genetics, combined with we don't even know what, right?

So is there a way to sort of tailor it to each individual as well? You're absolutely right. So every individual is different. They have different genetics unless they have an identical twin. They're exposed to different things. So as somebody goes about, day, they might encounter chemicals or something else in an atmosphere. There's, of course, lifestyle choices. So everybody's different. We talk about personalized medicine and can we create specific therapies for specific people. And I definitely think that personalized medicine approach would be better enabled by technologies like we're making with these materials that are able to help us better monitor disease. That was Aaron Morris. He's an assistant professor at the

University of Michigan, where he heads the precision immune microenvironments lab. You can see his full talk at TED.com. Thank you so much for listening to the show. This episode was produced by Rachel Faulkner White, Katie Montalione, and Kai McNamee. It was edited by Sana's Mashkinpur, Katie Montalione, and me. Our production staff at NPR also includes James Delahousie, Harsha Nihada, and Fiona Giron. Our executive producer is Irene Noguchi.

Our audio engineers were Gilly Moon and Simon Jensen. Our theme music was written by Romteen Arablewee. Our partners at TED are Chris Anderson, Roxanne Highlash, Alejandra Salazar, and Danielle Balerezzo. I'm Manus Shomerode and you have been listening to the TED Radio Hour from NPR.