Good Life Project - Hope, Not Fear: New Conversations on Cancer Breakthroughs | Future of Medicine [Ep. 6]

Episode Date: December 8, 2025

From breakthrough AI diagnostics to personalized immunotherapy treatments, cancer care is undergoing a revolution that's already saving lives.Dr. Ross Levine, Chief Scientific Officer at Memorial Sloan Kettering, shares how new technologies are helping doctors detect cancer earlier, treat it more effectively, and transform what was once untreatable into manageable conditions. Whether you're navigating cancer personally or professionally, this conversation offers crucial insights into the future of medicine and why there's unprecedented hope in cancer treatment today.You can find Ross at: Website | Episode TranscriptIf you LOVED this episode, don't miss a single conversation in our Future of Medicine series, airing every Monday through December. Follow Good Life Project wherever you listen to podcasts to catch them all.Check out our offerings & partners: Join My New Writing Project: Awake at the WheelVisit Our Sponsor Page For Great Resources & Discount Codes Hosted on Acast. See acast.com/privacy for more information.

Hey, before we dive in, I want to share something a little more personal. We are a small team. We've been pouring our hearts into the show for more than a dozen years now. And through all the ups and downs in the podcast world, every single one of you who follows a show helps sustain this work. And I'll be honest, creating from behind a microphone can feel a little lonely at times. But when we see you hit that follow button, it's this beautiful reminder that you're out there,

listening, growing, and connected to this mission of bringing conversations and ideas that add more ease, meaning, and joy to your life. So if you haven't yet, it would mean the world to us if you take just a moment and tap follow, truly. Thank you. Now, let's get to today's episode. So what if I told you that everything you think you know about cancer is about to change and maybe already has, that we're living through a moment where our understanding and ability to treat this collection of diseases is transforming at a page. that would have seemed impossible just years ago. I mean, picture a future where we can identify and intercept cancer potentially even before it becomes cancer, where treatments are tailored to

your specific molecular profile, where AI helps doctors make better decisions faster. That's what we're talking about in today's sixth installment in our future of medicine series. My guest is Dr. Ross Levine, chief scientific officer at Memorial Sloan Kettering Cancer Center, one of the world's premier cancer research and treatment institutions. As a physician researcher, his lab focuses on understanding the genetic basis of blood cancers, and his work has earned him countless accolades. In our conversation, we explore why cancer isn't actually one disease, but hundreds of distinct conditions, and how this understanding is revolutionizing treatment. You'll learn about fascinating advances in immunotherapy that are already changing lives, new diagnostic tests and approaches, and treatment

protocols that are changing the face of how we understand, treat, and even eliminate cancer. You'll hear stories that will fill you with hope about where medicine is headed, and wait until you hear what Dr. Levine reveals about the role artificial intelligence is playing in cancer diagnosis and treatment. It is transforming everything. So excited to share this conversation with you. I'm Jonathan Fields, and this is Good Life Project. As we have this conversation,

I want to say six of the most terrifying letters in the English language strung together into a single word, cancer, is something that people, we all know it. If we're not touched by it personally, we've been touched by it relationally, especially once you move further into life. What do people think is true about cancer today that in your experience, having been in this field for so long, no longer is? Well, it's a really good point that it exposes, I think, for all of us, whether it experiences something we experience personally or someone in our sort of friends or family or being a care provider, you know, it's a vulnerable moment for everyone. And I think that fundamentally, it's this sense that there's this disease that you feel like you have

no control over what's going to happen, that it's growth or a tumor or whatever it is, depending on the type of cancer, that it's got, quote, unquote, a life of its own and that you feel like almost you're rolling the dice and that fate's going to delineate it. And I think what isn't true, and I think getting to your point is, in many cases, we're able to bring exciting, effective treatments that actually can, you know, harness, whether it's the one's own body or novel drugs. Like, we're able actually to treat many cancers. I think everyone, when they're first diagnosed, doesn't appreciate that.

They're much more focused on the, oh, my goodness, this thing is now in front of me that just is going to be this giant tilt on the pill and pinball machine I'm playing. And I don't know what this is going to bring, and I fear the worst. And helping people understand that that's not the journey necessarily they're going to be on, that's our job as care providers, as scientists, as family members. If you know what I mean. You mentioned something also, I don't want to tease out a little bit, which is you kind of said, like depending on what type of disease this is, which makes me curious how our understanding

has shifted from, quote, cancer to potentially hundreds, thousands of distinct diseases. And talk to me a little bit about this and also why it matters. I think it's a really important fundamental concept and one that I think the average oncologist or cancer researcher understands, but probably not people that aren't thinking about this every day. When we began thinking about cancer as a disease and treatments in the late 60s and early 70s, you know, when it was largely chemotherapy and then surgery, we didn't really understand that every cancer is different and even within a cancer classified by where it originates, the lung, the brain, that there are molecularly defined subtypes. And that was because,

Because one, we didn't have the tools to actually understand that. You know, every puzzle piece looked the same to us. And it's almost like if you looked, you know, from far away, and then you realize that when you look at every snowflake, they're different. But probably more important than that, the understanding part is that we now have treatments that leverage that understanding, that not in every case and we yet have much work to do, we're able in many cases to say, listen, because of the unique molecular aspects of your cancer, aspects of your treatment are going to be tailored to that. And the more we're able

to do that, the more effective and better tolerated our treatments are overcoming. And that's, I think, what gives us cause for optimism, that that understanding is fundamentally the bedrock to actually informing better treatments. And again, we have lots to do. But it's a very different story than I think it was 25 years ago, but I don't think the average person, because they're not living it in their sort of journey every day, appreciate it. And I think there's still a lot of the same intellectual and emotional reactions that people have had for decades when they have a diagnosis. Yeah. And I wonder if part of that, I'm so curious what your take is, I wonder if part of this is that while all these incredible advances in understanding and knowledge and

differentiating what's really happening here, they're happening on the research side, on the medical side. So you as a scientist, as a leader, somebody who's been in the field for decades, you live and breathe this all day, every day, and you talk about it. You talk about it with your peers, whereas the typical person, you only have a conversation about it, if and when this becomes in some way real in the lives of you or someone that you know. And even then, you don't want to have the conversation about it. Like, you do everything humanly possible not to have the conversation. So I wonder if part of what's happening here is there's stunning new insights happening on the research side. But on the side of the people who are affected by it,

personally, people don't actually know about it in part because you kind of want to talk about it as little as humanly possible because then maybe it's not as real. Does that land at all for you? It totally does. Obviously, every person and their journey is different, and we have to respect how people process and approach such an overwhelming diagnosis. But I do think there's a lot of people where that is spot on. And I think to be candid, there are also people that when they confront and engage, maybe engage being a better word, the health care system, because I don't think most people confront it. I think they engage it. They don't always immediately land with someone who appreciates that complexity. And that's not meant to say that folks that are at the front

lines when people get diagnoses, whether they're general practitioners or even general oncologists, aren't doing incredible work. They are. I want to be clear. But the analogy I use, I'm a sports fan, is that our job at a place like Slim Kettering or other referral centers is often we're like Mariana Rivera in the ninth inning, meaning that we're not necessarily talking to the person when they have that diagnosis. We're talking to them either when they get to us, sometimes we hope early on in their journey, and sometimes when things go sideways. You have to appreciate that we're seeing a very rarefied set of folks that need us and that we have to respect that there are people out there across this country and in the world that are helping people process it who don't sit

every day and talk to people with one type of cancer where they can be, you know, very clear and say, my life's work is what you have. And I can tell you up down left and right. And I think our message to people is always to advocate for themselves and to ask the people that, are in their care system, is there more I should know about what I'm going through? But as you said, I think very thoughtfully, if they're already struggling with like how much they want to know about it, those two things kind of run, if you will, at odds with each other. And my message to people always is be your own best advocate and be your own best questioner. And if you can't do it because you're processing it, you should have people in your care network who can help you do it.

And I think that's the other thing I see that's incredibly informative and heartening is sometimes when a patient's struggling, they'll have someone in their side who does it. And, you know, I want everyone to have advocates with them. It doesn't always work that way. But I think it's super instructive and important. And when I am on the care side, inspiring when it's not only a patient, but they have other people there to sort of help them sort of advocate for themselves and ask all the questions. One thing that obviously has been coming up as we're deepening into this series is AI. I want to touch back into it in a couple different ways during a conversation. But in this very particular context, there's this phenomenon that's come up a few times now where, and I guess there's some interesting research around this now that shows that for a significant number of people, they're actually more comfortable asking a chatbot, all the questions that they're really concerned about asking a person. And on the one hand, we're like, what we're concerned because it's still hallucinates,

there's misinformation, there's all this stuff. But on the other hand, I wonder if you look at AI as maybe a way to help people do the outreach or seek information, even when they're not quite comfortable asking for help from a human being or having a conversation with a health care provider. Or I would imagine the answer is it's a little bit fraught too. Yeah, and we should talk about every aspect of it. But I think you bring up one of the more powerful, positive aspects of it is that if it allows people one to get more information more readily, as long as it's accurate and we could talk about that, but more importantly, if it gives them the confidence to sort of deal with the decisions in front of them, it's not my area, but I've heard about examples where there are AI-enabled tools that encourage people to get screening for cancer. and just knowing that those are AI-enabled, in some cases, encourages people to get screened.

We as doctors, you know, our attitude is people should just get their screening, and I don't personally care whether AI is actually changing the screening message or not if it's based on guidelines, but if it gives people the confidence to go do it, I'm all for it. Obviously, we hope as well that it's going to provide very important, useful and accurate information of people that comes to them. So it's easier for the thing to engage the system. But obviously that's something that we all need to figure out how to navigate together. Yeah. And it seems like there are a lot of really good minds working on that problem right now. As you scan the horizon, you know, we're having this conversation. It feels like over last

decade or so, we see news about the prevalence of particular types of cancer changing in pretty meaningful ways and not necessarily in a good way. Looking out, are you seeing what's showing up clinically changing in a meaningful way or in a concerning way? And if so, do you have a sense for what's going on there? Yeah, I think you bring up a good point. I would just maybe abstract for one moment and make the point that maybe the average person who doesn't think about some doesn't realize that there have been major sort of changes in cancer incidents and prevalence over the entire historical journey where we have that data. You know, the most famous example would have been that before we had widespread use of refrigeration.

So we're talking early 20th century. There were specific types of stomach cancer that were very prevalent, that as soon as we were able to use refrigeration more broadly, those kinds largely reduced and almost went away. And that's because they were associated with certain food spoiling and, bacteria that then people weren't exposed to. And so that sort of journey of how the lives we live and the cancers that we get changes is not new. I think what's new for me fundamentally is two things. One is I think you got to it. There are some concerning trends that there are certain cancers that are going up where we either may partially understand why or maybe we don't even fully

understand. And in particular, an area that's getting a lot of attention for all appropriate reasons is some cancer is increasing in their, you know, incidents in younger people. And that, I think, is something that causes us significant concern or something we pay a lot of attention to. I think a lot of us worldwide are trying to understand, for example, why colon cancer is more prevalent and younger people. And I think there's a lot we have to figure out there. And how much of that is due to factors we can appreciate and how much that we need to learn. I think there's a lot to figure out. And on the other side, I would say that, you know, we should always remember, that is, we're in a society where things like cardiovascular disease, whether they are being

prevented or not, and the impact, for example, of GLP1 agonist on that, we're going to learn. But if you even take that aside, just our ability with medical therapy and stents and to reduce mortality from cardiovascular disease, as people get older, the incidence of cancer does increase. And so we're dealing with the population living longer, and that also is leading to increases in cancers that occur with aging. So we almost have this duality where we have some cancers where they are occurring at higher frequency and younger people. That's something I think a lot we need to get our arms around. But we also have to acknowledge that incidents in cancer, especially in older adults, is quote unquote a victim of our own success in treating many

other diseases in really effective ways. Of course, that leads to an interesting question, which I don't know the answer to, which is if the use of these new medicines that improve metabolic parameters continues to increase both in the number of people take them for how long. We don't know what that's going to do to overall cancer incidents. I don't want to get ahead of my skis on this, but I wouldn't take the over on the over under that we're going to see a lot more overall cancer if people are leaner and fitter and have better metabolic parameters. I would take the, but we may find that there are some specific cancer types that increase. It's like everything else.

You have to let the data emerge and learn from it and ask then if we can make modifications that might ultimately then attenuate those increases. I want to make sure I understand. I think a lot of what you're referencing here in that last point is really it's this category of DLP-1 Agenda set. Yeah. We're seeing, and what's fascinating, I think a lot of people, in the last two, three, years, it's come on to everybody's radar. But these are not, it's not a new class of substance.

Like, this has been around for a very long time, but it's a new generation. The delivery systems have changed. The approval for different use cases have changed. So now we're just seeing it kind of explode in application. But you make such a, I think, an interesting point, which is, okay, so if across the board, it looks like what we're seeing is reductions in the lifestyle factors or the the indicators that often are associated with all costs, like all the major causes of mortality. It would make sense that, you know, they'd be in that positive.

But you raise a really important question, which is we just don't have the data, the really long-term data, to know, like, is there something where it's going to actually increase the risk of yet? And we're just not there yet. Yeah, and I think that what we have to do, honestly, is not be afraid of getting that,

data as expeditiously, even as incomplete as possible, meaning that, you know, we're going to get into, I think, AI and big data, I hope. But one of the messages for people who don't think about it all the time, and I'm not a computational expert, I'm a scientist, but I live in that world, is that scale, meaning the number of people studied, the number of data points, really is our friend here. We're able to see patterns with greater confidence when you get bigger numbers. And so, for example, I would feel differently about data on, you know, using these medicines and tens of millions of people than I would if it was on tens of thousands, including early data on the prevalence of cancer, and those do and don't. And it won't be perfect,

but it's going to be instructed. I mean, I think, again, getting back to the pandemic, we can talk about whether the right trials were done. But I think that when you get you know, hundreds of millions of people at different points, whether it's the vaccines or other factors, you learn a lot about, you know, what are the morbidity and mortality that it really does teach us. So I think the most important thing for us is doctors and scientists and for the lay public to appreciate is that there's going to be a lot of information on it. But when that information comes from very large, powered studies, it's going to be very instructive. Yeah, I mean, that makes a lot of sense.

And we'll be right back after a word from our sponsors. I want to get into diagnosis and treatment today and the future, but we've kind of dipped into one area that I do want to touch on before we head there, which is this notion of cancer as something that is preventable. So we were just talking about this particular class of drugs that tends to have the across-the-board effect of giving us better measures of things that are associated with all sorts of scary things in our lives. More broadly, when we look at cancer as a category,

are we looking at something that is a little bit preventable, medium preventable, largely preventable, or does it really just very wildly based on what we're talking about? This is an area near and dear to my heart, because I think it's an area where we're really in the early phases of what I think could be a really transformative opportunity. I think what we're understanding is, we study cancer with better and better scientific technologies and tools, especially genomics,

but imaging others, is that we're able more and more to understand that cancer in virtually all cases, maybe not every case, and they never want to be absolute, is a process that takes time, and that there are early states we think about polyps and why we do colonoscopy, we think about, you know, moles that the dermatologist checks. We believe that more and more that almost all cancers will have these early states that are pre-cancerous. And they're not normal, but they're not cancer. And in many people, they never will develop into cancer. So by no means, do we argue that it's fatal complete. But if you could identify those using non-invasive technologies, I believe that we're going to be able to not only find those early growths, if you want to.

call them, but we can call them by whatever. But if you could then use, I think, better and better technologies to estimate risk and identify the people who, when they have them, are at highest risk, that could be a combination of not just, for example, the size of the mole or the polyp or the abnormal blood cells that we can detect in the circulation, but it could be other parameters in the patient. It could be even microscopy looking with image analysis and how normal, abnormal both cells are. We might be able to tell people one person, and I study these people that have these pre-leukemia diseases called clonal metapulases. Some of these people have a 0.1% chance of getting leukemia, but others have a 5% or 10% chance. And you might envisage a future that

for the 5% and 10%, if we could develop therapies that could turn that 5% and reduce it, we could ultimately reduce significantly the number of people that show up with overt leukemia. And so my own research lab is trying to study what really makes those early cells at that fork on the rope. Are they going to progress or not? And do they have therapeutic opportunities? And today, it's mostly a lab question. But my view is that in the same way that mammography and colonoscopy and the HPV vaccine and, again, careful surveillance of, you know, lesions on the skin, those have all reduced the incidence of cancers in people that take advantage of that. And in some cases, HPV vaccine, you know, is reduced cervical cancer. I think we're going to see that in

many other cancers. And it's not a tomorrow thing. But my view is that whether you call that prevention or whether you call it interception, you know, we can decide on the term. So I almost think of the idea of finding the early stage and then intercepting it. But I think like, you know, I view these early sort of growths, if you will, abnormal cells that are dividing. We probably all have them, especially as we age. So the early steps are probably almost inevitable. But if we can identify the ones that are sort of picking up steam and have things we can do about it, that could change the whole game. And so I believe we need to really double down on that idea. There are large groups studying what we call pre-cancer worldwide and using technologies to do it. And then we need

to also study bringing treatments to that stage. But you can't bring like, you know, toxic treatments. doesn't yet have cancer. We need really molecularly informed or immunologically informed treatments that are effective and that we can give to people and say this was going to benefit you. A part of what you're saying here that I really want to make sure is just really brought out is this understanding that the time of interception is really, really important when it comes to, it sounds like pretty much all forms of cancer that so often it's not actually identified and found until you, somebody is strongly symptomatic and at that point it's fairly advanced, whereas, and tell me if I'm getting this right, if we could identify this, not only in the earliest

stages of cancer, but even in sort of like a cellular form that is curious, questionable, not quite normal, but also not clearly identifiable as cancer, that, and then either monitor or intervene appropriately, our ability to treat it and stop it from becoming something much scarier and potentially more harmful goes up dramatically. Is that accurate? I think so. And then the other part is there might be lifestyle things people can choose to do that can modify that. We don't know, for example, if changing your metabolic parameters or exercise might, but we have to study it. And I think that we also want to empower people that if there's things they can do that can impact, you might encourage people to do it. I think, again, to the cardiovascular example, that a lot of

of the great successes in cardiovascular disease started with people that had had a heart attack. And you take people that have had a heart attack and you say, if we roll all your cholesterol and you exercise more, we can markedly reduce the likelihood of you getting a second one. And ultimately, though, the real win was finding the people who had not yet had it and bringing that. And that's the journey I think we're on in cancer that we have to sort of get that knowledge base and set of things we can do into. that population and bring patients and their family members on that journey with us. Because I think a lot of people never want to be in our offices and I don't want them there.

I don't like treating leukemia. I would much rather say, you could get leukemia someday, but if we do these things, I can reduce, that would be an incredibly important thing that would change the landscape. Yeah, 100%. So you mentioned this notion of lifestyle. It does seem like there is a meaningful amount of research that, shows correlation with certain lifestyle choices, whether nutrition, movement, stress reduction, that correlate to reductions and all sorts of things. Are we at a point with the science where we can

actually show causation, where we can show that if you change the way you eat, there's a causal relationship between cancer reduction or the way you move, things like that? I think there are specific nuggets where that's true. I think there's data suggesting that, you know, for example, diet, which can affect your microbiome, can affect either cancer. incidents are more in the current sort of moment often how cancer treatments work. I think we've got a lot to learn there, though. I would say that I'm optimistic that we're going to have a much, that that book that we maybe only have written a few pages in is going to be much bigger and fuller. And I think we want people to be on that journey. But I always tell people when they come to me and they have these

early states, I'm like, I can say with a lot of confidence that you taking control of your life in doing those things, at worst is a wash, and I'm optimistic that it's actually going to be beneficial. And probably we don't need to wait for all of the data to say that it also gives people some sense of control. I'm going to try and do some things while there are other things that might not, again, where we started the conversation, that loss of control, I think, is really hard for people because it feels like a disease where they feel like they have things done to them and they're not really part of that. And I think that's scary for people. Yeah. And that notion that says, okay, so there may be things inside of me that I don't quite understand and I feel like

I don't have control over. But I can go for a walk today. I can have more plants on my diet, whatever it may be, like these things I actually do have agency over like that is still within the realm of control. Yeah. Exactly. Now that lands. So if we broaden the lens a bit here and we start to look out into the world of diagnosis, what are some of the big shifts that you're seeing, happening in cancer diagnosis right now? Well, there's sort of two parts. The part that I think, again, we're excited about, but it's still early, is detection of cancer before earlier, whether that's through these genomic tests that can find early genetic changes before they would have been detectable, or the improvement in radiology, or, you know, again, approaches this survey. I really do

believe that one journey that we're going to see a lot of progress and we've seen some already is our ability to start to tell people we can without being super invasive begin to look and identify things that indicate risk or a diagnosis months to years before and I think that as we improve things like radiology and molecular diagnostics and our ability to interpret then amalgamate that data into complex heuristics is going to be great. And I'm super excited about it. But the part that I don't think the average person appreciates, and this is super important for people out there,

is that not just detection, but actually making a correct, precise, and molecularly informed diagnosis is the single most important thing that you get early on in your journey. I always tell people, you know, MSK, which is an incredible place to work, and we're super proud of us. And if you go out to the street in 68th Street, right where I am, there are these banners and of some of our amazing doctors and scientists. There are billboards that talk about us and all the health centers do it. We can have a long conversation about it.

But what I keep saying is that we need to put a molecular sequencer on a billboard. We need to put the pathologists with a microscope. What we often do is say to somebody, there's things about your diagnosis, whether we can refine it, sometimes change it, or just with the molecular analysis. We can get really, you know, granular about what you have and what that information can tell us on how to treat. And that's not necessarily always true if you don't get access to sort of the most modern tools. And I tell people all the time that my chemotherapy, I give it Sloan Kettering, is no different than chemotherapy at other places. But I have pathologists and radiologists and molecular experts who tell me things about that biopsy

that inform what I can and can't do. Often is not just like what I'm going to do for you today, but it like lays out, well, what are we going to do if things change a little bit or the first treatment, which is the obvious one, doesn't work as well. well, like, I want to know what all my options are to help a patient as early in the journey as possible, and that molecular and path information helps us. And so I tell people all the time, it's not just the doctor you see. It's the whole team of people that's analyzing your cancer that are giving the doctor and team and then the patient the information to empower them.

That's the differentiating thing of why I believe that people should go to, you know, incredibly high-quality cancer specialists. Yeah. And that brings up, again, I'm going to bring back AI. Like when you're referencing individuals, you have this incredible team of people at your disposal, are we at a moment now or are we going to be at a moment soon where some of those people are going to be AI, where some of the team, like all of this, the data is being fed into and observed by and translated and the diagnostic outcomes are also coming from specially tuned models and massive data sets that help us dial us in. The answer is yes. And it's happening already in some cases. So the way I think about it is twofold. The first way I think about

it is that for any of us that have gone to medical school or nursing school or, you know, any sort of health care provider, a lot of what you learn in training is not, you know, I get result X and then I do Y. It's that I sit with a patient and I have these lab parameters and this radiology and these symptoms and that exam. And then my brain is able to sort of, you know, put that together and say, I think you have X and I think we should do Y. And we spend a lot of time honing that. And then the other thing we do really well, I always tell people is, you know, doctors and nurses are really good when someone's very ill. It takes us like a nanosecond to like look at the patient and go, I am worried about you or I am not. We call it the door test. We look from the door. So that,

It's sort of, to me, prima facie proof that the human brain, when you're providing care, is trying as best it can to amalgamate many different parameters and to make a decision that if you ask the doctor to articulate what was it, they often can struggle and be like, I can't tell you that it was that time. It was actually that summed together. So to me, a lot of what AI algorithms can do is allow us to amalgamate more information. And I call it decision support. it's going to allow a doctor or a nurse the algorithms are going to say we've amassed all the data even more than your brain thought we can do and it tells us the likelihood of these things is x or y or c now the doctor or the nurse is still going to make the call but they're going to make an informed and enabled call and that to me is super important the other thing that it can do is it can reduce the time like imagine you have a really good radiologist or pathologist and the algorithms can read the images up front and then say,

I can do 98% of it, but then I need an expert to sort of then figure out, like imagine if they can read 100 cases instead of five because the 95% of the work's being done. I think we're sort of in this transformative era. That does lead to an interesting conundrum, which is that, you know, not so much in what I do when I'm a leukemia doctor. I don't think AI can replace me yet. But I do think we worry a little bit that if the heuristics for analyzing radiology or pathology gets so good, we still need radiologists and pathologists that are so damn

expert that they add value on top of it. And so we're going to need to think about how we train those people so that they still sometimes do the whole thing themselves. So they kind of build it. And I think really wonderful places like ours think a lot about that. Like how do we build AI into our systems? but still train people that are sort of the answer of last resort. Now, I know we're getting on a little bit of a tangent, but it's super important.

And then the other part is it's got to, like, you know, we've got to use it to, like, do all the stuff that, like, just saves us time. When you prescribe a medicine for someone, these algorithms can immediately look at a patient's medical history and all the other medicines are on. And then eight nanoseconds go, change the dose. Or use that one and not this one. instead of like me having to remember, oh, that medicine and it's just obvious to me that it's going to make us better at delivering care. So that's like the patient-centered part. The how we do

medicine is going to change. And then on the other part, it's going to be we're going to discover things about how cancer works because we're going to just amass so much data that these algorithms are going to be like, I can look at the shape of a shell and tell you things about the biology even before you do the molecular test. I'm excited about that too. It'd be so fascinating to have this conversation again to retouch back down in five years. I can't imagine the changes that we would be talking about then. Yeah. And we'll be right back after a word from our sponsors.

Two other things I wanted to ask you about on the diagnostic side that I'm hearing more and more about these days. One is these things that are commonly classed as, quote, liquid biopsies. And the other is this idea of full-body MRIs. Talk to me about your thoughts on what these are. and what's your take on them? Well, on the one hand, they're super exciting. The idea that we can use these circulating DNA tests or liquid biopsies or whatever phraseology you want to use

to detect abnormal cells or the fingerprints of abnormal cells at an early, early stage is super exciting. And it really feels like it has the potential to be a transformative opportunity. Likewise, the idea that we have better and better MRI and they can find a tumor lung before it would have been found is really exciting. But for me, the challenge is twofold. One is, can we get enough specificity in what those tests tell us that we can give people

a clear next step? The early tests, like the Galeri test, it says you have a reasonable chance of having cancer, but the first version of it doesn't tell you what cancer you have. So then the patient goes on a pretty frightening journey with their doctor of, like, what test do I run? What cancers do I look for? What do I do if I've looked for these eight and not these nine? I think what's beginning to happen and what has to happen is it's got to give us a lot of information on we think that it's not just that you have a high risk of cancer, but these are the two cancers we think you're at highest risk for. I think a doctor and a patient

can handle that. All right, you need a biopsy of your prostate and a PSA because that was the cancer you thought you had. It said kidney. I know exactly what test you need. The other aspect of the MRI is the number of biopsy you do where then the pathologist goes, actually, it was a growth, but it wasn't cancer. And how many of that? And the confidence that you can tell people that the MRI is meaningful and tells you there's something really to be concerned about, because there's two issues. One is the emotional part, right? You go through it and you don't have it. But then the other is the next steps often are not without risk. A biopsy is not without risk. And so I think we need better technology and better use of it. They have to refine. And we need studies then

that show you how it can actually do it. But I do believe fundamentally those things are going to happen. Like I'm not worried about whether they'll get there. It's all about when they get there and which ones. Yeah. So it's a matter. It sounds like what you're saying is this is the really good technology. This is maybe a matter of timing. Like we need more time for them to be more refined and to give more granular information. And so that if there is some version of of a positive signal kicked out by them, there's enough clarity and specificity to, A, believe that it actually, there is a very high likelihood that the positive signal is accurate, and then B, give you direction on, like, where do I focus on? Like, what is, this is going to give me

a high level of confidence about what the next intelligent test to do is to validate or invalidate this. Yeah, I think doctors probably much more than people that don't do medical training, you know, you learn over time that you think about not only that what if it's positive, but the sort of what if it's negative and I do harm and there's no, like, I didn't get anywhere. And I think, you know, we have to respect that aspect of making these decisions and be upfront with people about what we do and don't know and not trying to sort of be paternalistic and say, you need this. If we're seeing all of these developments happen on the diagnostic side right now, and it sounds like we are in this, like literally as we're having this

conversation. It's like we're a handful of years into what feels like a revolution. It's moving faster and faster and there's still a lot more refining and data and growth and discovery that needs to be made. But it's an exciting moment. We're seeing things and being able to see things that could be potentially truly groundbreaking. If we switch gears now onto the therapeutic side and I ask you a similar question, what are the biggest shifts happening that you're seeing on the treatment side now. A lot. I mean, and it's almost dizzying to think about the sort of breath and depth and pace of that innovation. You know, there's a number of different threads one can pull on, so I'll just mention a couple, but understand these are just examples. Yeah. So one is that, you know, when we develop

drugs, usually we say, all right, we develop a drug like a small molecule chemical entity, and I'm going to get right into this pocket, that is where the enzyme works, and I'll block it. And we have many cancer drugs that are like that. But as you develop better and better chemistry and better AI-enabled structural biology, alpha-fold, being the classic example, we now can develop drugs that bind other parts of the protein, that then you can predict that they secondarily do that. We call those allosteric interactions. And the idea that we can open up the space of what's struggleable with chemicals, therefore, is expanding in real time. Our ability to think about what small molecules can do and can't do. It's almost getting, the analogy I use is imagine for

people yours in my age, but not our children, that they cannot imagine a world where you had a type on a typewriter and didn't have the ability to select the text and delete it, right? Once you have that, you don't go back. And that's what the chemical biology field is. not being able to do it. It can almost like program and do things. And then you add CRISPR and gene therapy. Our ability to manipulate the biological system to what we wanted to do is expanding every day. And then the other one that I'm super excited about in the cancer space is the ability to harness the patient's own immune system. And whether that's drugs that just activate the immune system, whether it's vaccines that teach the immune system to attack the

cancer or cellular therapies where you can take cells out of a patient and then turn them into cancer killers. Like, I just think we're, like, at this moment where a lot of things that were science fiction and were like, the ideas were there for a lot of this 20 years ago, but the implementation wasn't. And I think that is sort of the moment we're in. That when I started my career, I think we were excited that we could understand cancer, but we had so many examples where we said, we understand it now, but I can't yet do

anything about it. And we're now in an era where the understanding continues expand, but the what we can do about it is catching up. And that is, I think, what I'm most excited about. It's really incredible that the things that I've been hearing also. I know somebody whose wife had, I guess, multiple myeloma. Is that blood cancer? Yeah. She would get treatment basically like every year and she was on sort of like a chronic treatment protocol. And I remember him telling me that the doctor was saying he's basically like something akin to a cure is coming fairly soon. We can see it in the horizon. My job right now is to keep you okay until that.

comes. And for her, it seems like it came, you know, and she had literally went in for one immunotherapy-based treatment, and it was like the clouds lifted. And it was this, you know, after five or seven years, all of a sudden everything was back to the way it was before. It was this stunning moment, you know. And I would imagine things like that are becoming just more and more possible and more common. That's right. I think that's really well said. And again, That's why I think we view it, you know, and again, not to use words that are tried as a war. You know, the war on cancer, I think, is a great analogy because we are winning battles now in different fronts all the time, but yet we've got many more.

If you break back to where we started, if cancer is 500 or 600 or 700 or 800 diseases, we're often able to pick them off now one by one, but we've got to keep it up. Now is the time to double down not to sort of rest in our laurels. And I do think when you see those moments, when a disease goes from being not treatable to treatable, and it goes from being treatable to potentially being treatable with long-term remission, you can use the word cure or not. I'm very careful with that word, and I don't like to promise it to people. But I think when you start to see those more than incremental improvements, you're like, oh, my goodness.

And I think myeloma is a great example, melanoma, too, some types of, lung cancer where, you know, when I was in training, these were awful diseases. And when you were in training as a doctor, you're like, I won't want to go into that because I just don't want to spend all day telling people, you know, this is going to be hard and it's not going to end good. And there are some people, wonderful people who chose to do it. And they really brought meaning and purpose to that. A lot of us really said that's going to be really hard to do. But ultimately, some of those diseases are in a different, like, there's a lot of bell ringing in clinics and wonderful moments. And I give credit to the science, but I give credit to two groups of people,

the patients, their courage, their willingness to be on those trials, to try things. And a lot of times there was those doctors who chose to go into those areas when they were really hard and emotionally draining, who are the same doctors who get to give those treatments. And I have incredible admiration for my colleagues that really spearheaded those journeys. Yeah, and I mean, you're also, you're really speaking to the human side of the practitioners' experience at the same time here. As we have this conversation, you are fairly recently appointed Chief Science Officer at MSK. For those who don't know, by the way, we keep referencing MSK, which is one of the premier research institutes in the world when it comes to cancer

in New York City, Manhattan, Morris Sloan Kettering. So you're in this really interesting role right now also, where you're sort of like looking at the wide scope of everything that's going on there right now. I'm curious, you also have a really good understanding of what it takes to bring something from idea and then to research and then have that translate to actual clinical application. In my mind, like I pictured this just wildly complex, years, if not decades, long process. Is that real? And is it changing in any meaningful way? I think, you know, back to the conversation we've been having. For me, the most exciting thing is that it's accelerating. The thing I'm most excited about is that I see more of these amazing discoveries

about how cancer works, amazing new treatments, and then outcome trials with that. There's almost, I said this earlier today on a call. Like, it's almost every day that you can, I can pick up a journal and just from my own institution, which I love, but many others do, that's something amazing happened. And it's happening with a pace and impact that just didn't seem possible 10 years ago. So I'm very optimistic about just the overall pace of it. I think for me, the two things that I see that stand out about why a place like here is special and why we really are so excited and why I'm so excited to be here and to take on this role and to work with my colleagues. The first is we have an incredible cadre of remarkably bright and fearless and creative people that are trying to do

things that are high risk and disruptive, but they bring incredible courage to that. What I get excited about every day is talking to young scientists who work here, who want to try something that just seems insane. And then the number of times in five years later that it works, or that they tried and then they did something. That gives me hope and gives me a very good reason to come into this office every day. I sit here in my office. My lab is right out there. And in addition to my leadership role, I run a research lab. And right at that table right there earlier today, people from my lab come in and they show me data they generated like that day or the day before. Like that's the fun

of it, right? It's special and unique. But there's another part of it, which is that We at MSK and at other amazing places, we have these teams that work well together. You know, we have basic scientists that have never seen a patient but have incredible ideas. We have people who are at the bedside who've never been in a research lab, but they work together. And they say, all right, I know this, you know that, let's do something together. Let's take something from the lab and I'm going to partner with somebody who runs a trial. And then when the trial teaches us things different, we go back to the lab. What we encourage here is team science.

What we tell people is the sum is very often greater than the parts. And I think part of my job is to do, you know, to one, pick and support really smart, brave, courageous and fearless people to take risk, but to encourage those people to work together. And that's what I'm going to do. That's how I'm going to approach my job. And my job is to help them think about how they can do that and, you know, reduce the friction in accomplishing things. Yeah, such a powerful moment. The seat you're in has got to be just deeply fascinating also. And bouncing back to what we're just talking about before this also. So you have been living, serving, researching, learning, teaching in this world where you're surrounded by cancer.

And I have to imagine that living in this space, we're devoting so much of your waking hours to this space, it changes a person. I'm wondering just on a personal level how doing what you done. Do you feel like it's, it's impacted you just as a human being in a meaningful way? I'm sure it has. It's very hard to sort of get sort of philosophic. You know, you need to, you know, take a step back. I think it happens in moments. You know, I'm wearing a cycle for survival, you know, jacket. You know, we do this event every year where we get more than 20,000 people to ride with us and raise money. But the thing that sticks with me is when patients get up and tell their stories of each of the rides.

And you get everything from patients who've been through an incredible experience and are really looking back in their journey hard, but they've had a really good outcome to people that sometimes are in a vulnerable moment where we know it may not work out or people that have lost somebody. And to me, that's the why. Like, I always tell people that when I ran the marathon and I got to run past Len Kettering and the Fred's team people because we raise money, like, That, to me, just makes me more charged up to go to the lab the next day.

And to me, I always tell people like, go out, I tell our side is go out to these events. Not because you're going to get support for your research. Of course, we will figure that out. But I want you to take whatever it is that fills your bucket that day and bring it back. And then, you know, you get personal events. My sister was diagnosed with myeloma two years ago here. she had a very scary initial diagnosis because it was a tumor in her spine. We didn't know what it was. And she had to have emergency neurosurgery. And she's been very open about telling her story. But as you might imagine, as her brother, not her doctor, I got to see what this place can do for someone in difficult moments. And it was a very poignant moment. It is to this day. And, you know, I'm grateful. But as you can tell, probably after talking with me for the last hour, I approach everything, with this sort of, you know, high energy, and I'm going to, like, keep going and pushing and

inspiring others to keep on this journey with us. And I always tell people, patients, their families, the people that support us and support cancer research worldwide, they're like as much a part of this journey as we are. And we want everyone to own the success and also to understand the challenges. And let's do it all together, you know? As we wrap up, is there anything that I haven't asked you about that you think would be important to fold into the conversation? Well, I mean, I think the only other thing I'd say is that I am incredibly excited about the idea of studying thousands, if not millions of people that have or might have cancer someday, an understanding cancer at that level using these complex algorithms.

I just think we're in the early days of understanding what that means, and it's going to give us the power to understand this, not just cancer when it occurs, but cancer when it might occur and what it means. I'm super excited about it. And for me, the reason we do this is for moments like what you describe with your friend. It's those victories that we appreciate, we crave and we want and we need. And we're going to keep going. And we just thank everyone for being with us on this journey. and, you know, that we're going to keep at it. And we know that we've got a lot of responsibility in front of us and we're just going to take it on all together.

Thank you. Hey, before you leave, quick reminder, this conversation is a part of our special Future of Medicine series. Every Monday through December, we're exploring breakthrough treatments, diagnostics, and technologies, transforming health care from cancer and heart disease to aging, pain management, and more. If you found today's conversation valuable,

you won't want to miss a single episode in the series. You may even want to go back and listen to the first five. Next week's conversation is with Dr. Yoni Ashar, where we'll dive deep into groundbreaking research on chronic pain and the fascinating intersection of neuroscience and psychological treatment. We'll explore how our brains process pain, discover new approaches to pain management, and understand how cutting-edge treatments are offering hope to million suffering with chronic pain.

Often, without even any sort of, of procedures or medication. Dr. Schar brings unique insights from his work using brain imaging and computational tools to revolutionize our understanding of pain treatment. So be sure to follow Good Life Project wherever you listen to podcasts to catch every conversation. Thanks for listening. See you next time. This episode of Good Life Project was produced by executive producers Lindsay Fox and me, Jonathan Fields, editing help by Alejandro Ramirez, and Troy Young, Christopher Carter crafted our theme music. And of course, if you haven't already done so, please go ahead. and follow Good Life Project in your favorite listening app or on YouTube too.

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