The Medical Matchmaking Machine

Summary

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Radiolab: "The Medical Matchmaking Machine"

Host: Latif Nasser (WNYC Studios)
Guest: Dr. David Fagenbaum (University of Pennsylvania, Every Cure)
Date: August 22, 2025

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Episode Overview

In this episode, Latif Nasser sits down with Dr. David Fagenbaum, a physician-scientist whose personal and professional journey through near-fatal illness led him to become a groundbreaking advocate for medical innovation. What began as his desperate, data-driven search for a treatment for his own rare disease has evolved into a global effort—powered by artificial intelligence—to revolutionize drug repurposing for all diseases. The episode traces David’s deeply personal origin story, the science behind his recovery, the glaring inefficiencies and economic challenges in our healthcare system, and finally, his ambitious plan to publicly release an AI-driven matchmaking tool—"the Matrix"—that could match existing drugs to untold diseases.

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Detailed Breakdown & Key Points

1. Dr. David Fagenbaum’s Origin Story: Crisis and Motivation

[02:12–07:15]

• Football Dreams and Trauma: David, once singularly focused on playing college football, had his life upended by his mother’s brain cancer diagnosis and eventual death.
  • Quote [06:58] David: “I told her, I was like, ‘Mom, I’m going to dedicate my life to trying to help people like you. …I’m going to be a doctor, and I’m going to dedicate my life to just find treatments for this horrible thing that was taking my mom from me.’”
• Resolve Transformation: This loss transformed David’s ambitions from athletics to medicine, fueling a deep resolve to take on intractable diseases.

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2. Facing His Own Medical “Beast”: Diagnosis with Castleman Disease

[07:20–12:49]

• During med school, David falls mysteriously and severely ill; doctors struggle to diagnose his rapidly progressing multi-organ failure.
• After 11 weeks, he’s diagnosed with idiopathic multicentric Castleman disease—something so rare he’d only vaguely heard of.
  • Quote [10:02] David: “When I heard it…I think I’ve heard that once in med school. That’s how rare it was.”
• The disease has a worse prognosis than lymphoma; doctors tell his family to prepare for his death.
  • Memorable Moment: [12:32] Last rites, family farewells in the ICU.

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3. Pivot to Action: Self-Research and the Hunt for a Cure

[13:00–19:20]

• On May 12, 2012, after multiple relapses and no remaining treatment options, David activates:
  • He assembles a team, gathers his medical records and biological samples, and analyzes his own blood for abnormal signals.
  • Discovers that his immune system’s mTOR pathway is hyperactive. He remembers an old drug, sirolimus (rapamycin), that could target this pathway.
    • Quote [17:36] David: “Rapamycin is the drug that saved my life.”
  • He convinces his doctor to try it, even with only a 10–20% chance of success—and it works. David has now been in remission for 11+ years.
    • Quote [19:20] David: “Amazingly, it weakens my immune system in the right way so that I don’t attack my own organs.”

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4. Scaling Up: From Personal Miracle to Systemic Change

[23:30–31:21]

• David and his lab expand their focus to help others, including using drug-repurposing strategies for his uncle’s rare cancer and his brother-in-law’s ALS.
  • His persistence leads to a trial of pembrolizumab for angiosarcoma, resulting in a new standard of care—without a formal clinical trial, simply by repurposing a known drug.
    • Quote [27:00] David: “About a third of people with this horrible cancer…will respond really well to pembrolizumab…It’s now standard of care for his form of cancer.”
  • Memorable Moment: [25:49] David’s “Dumb and Dumber” optimism: “So you’re saying there’s a chance.”

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5. The Systemic Problem: Why Drug Repurposing Is So Hard

[27:53–31:21]

• Legal and economic structures incentivize companies to seek approval for one disease and discourage wide repurposing, especially once drugs go generic.
  • 20–30% of prescriptions are “off-label,” but the system doesn’t financially reward discovering new uses for old drugs.
    • Quote [29:00] David: “…once a drug becomes generic…no one in our system makes any money off finding a new disease for that drug.”
  • Explanation: Complexity and cost drives how drug companies decide on which diseases to target first, limiting wider application.

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6. Enter AI: Building “The Medical Matchmaking Machine” (MATRIX)

[31:21–39:19]

• Motivated by COVID-19 and the broader potential for drug repurposing, David and his team build an AI/ML-based tool—a massive biomedical “knowledge graph”—to systematically map every known drug-disease-gene-pathway connection.
  • Score every possible combination (75 million in all) to surface hidden matches, accelerating new discoveries that would be impossible for humans alone.
    • Quote [34:24] David: “…now what we do is we train machine learning algorithms on all of those known treatments…And then we say, okay, algorithm, now go and score…the connection between every other drug versus every disease.”
  • The AI, called MATRIX (ML Aided Therapeutic Repurposing and Extended Uses Matrix), is set to soon go public:
    • Quote [38:15] David: “…we feel this tremendous responsibility that once we share it, that, you know, it’s out. …we will share it.”

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7. The Ethics & Risks of Public AI-Driven “Cures”

[39:19–55:12]

• Latif expresses both optimism and deep concern: is it helpful or reckless to unleash such a powerful tool to the public?
  • Doctor friends split: rare disease experts are excited; other clinicians worry about the impact on the doctor-patient relationship (cf. “ivermectin for cancer”).
    • Quote [49:17] Latif: “…the doctor-patient relationship is already in a bad place…if patients come in with these drug recommendations…she has to be the doorstop, she has to be the one who crushes the hopes and dreams and has to hold the line.”
  • David assures: MATRIX will be caveated—meant as a research idea generator, not as a prescription engine.
    • Quote [44:34] David: “…if we’re going to put our eyes on them, the world should be able to put their eyes on them…”
    • Quote [48:29] David: “…this is not a solution engine. This is an idea generator…if you’re a patient, that might mean working with a research lab to do the work to figure this out…”
  • AI is prone to “hallucinations”—e.g., a rival tool suggested “car fume exhaust” for Castleman’s. Human oversight is essential.
    • [47:00] David: “…literally one of the top five predicted drugs for Castleman disease…was car fume exhaust as a treatment.”

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8. Hope, Reality, and the Limits of Fighting

[55:12–59:57]

• Philosophical tension: Should we always be “throwing Hail Marys” for more life, or is there value and dignity in not fighting everything? Latif contrasts David’s stance with Dr. Blair Bigham’s (“Death Interrupted”) more accepting philosophy.
  • David acknowledges: the decision must be personal. Echoes a recent patient who, despite benefiting from a repurposed drug, ultimately chose quality of life over continued treatment.
    • Quote [59:57] David: “…maybe that’s the big takeaway is that it seems like everyone wants to tell us what everyone else’s decision should be…But I think that maybe that’s the real fundamental thing this comes down to. It's got to be that patient’s decision.”

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Notable Quotes & Memorable Moments

• On Football and Grit:

  • [03:25] Latif: “But you actually get your dream. You get to…”
  • [03:27] David: “…I get my dream. I get this opportunity to go to Georgetown to play football…”

• On Fortune and Responsibility:

  • [19:27] David: “I just feel this tremendous sense of responsibility that…if you’re going to get lucky enough to have one of these medicines help you, you sure as hell better spend the rest of your time trying to find as many more of these medicines to help other people.”

• On Systemic Stagnation:

  • [29:00] David: “…no one in our system makes any money off finding a new disease for that drug.”

• On the Limits of AI:

  • [47:00] David: “I will tell you, there is a drug repurposing platform…where literally one of the top five predicted drugs for Castleman disease or predicted treatment…is car fume exhaust as a treatment.”

• On Personal Agency:

  • [59:57] David: “It's got to be that patient’s decision.”

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Selected Timestamps for Important Segments

• [06:58] – David’s vow to his dying mother to fight disease
• [10:02] – The shock of being diagnosed with a disease even doctors barely know
• [17:36] – Discovery of rapamycin and its lifesaving role
• [19:27] – Sense of mission to help others
• [27:00] – Breakthrough with uncle’s angiosarcoma (“now standard of care”)
• [34:24] – How the AI “Matrix” finds drug-disease matches
• [38:15] – Matrix to be released to the public for research
• [47:00] – The problem with AI “hallucinations” in medical predictions
• [49:17] – Dangers of undermining doctor-patient trust
• [59:57] – The ultimate question: agency and dignity at the end of life

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Episode Takeaways

• Hope and Individual Agency: David’s story is a testament to scientific curiosity, personal grit, and the power of existing medicines hiding in plain sight.
• AI as an Accelerator and Democratizer: The "Matrix" AI could massively accelerate global biomedical discovery, but only if coupled with responsible, human-centered oversight.
• Medical Ethics in the Algorithm Age: Democratizing access to AI-generated drug suggestions is both hopeful and fraught—patient safety, scientific rigor, and the doctor-patient bond must remain central.
• Medicine’s New Frontier: Beyond “precision medicine,” this is “precision repurposing”—mapping not just people to drugs, but drugs to untold medical mysteries.

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Further Listening

• “Death Interrupted” (Radiolab): On end-of-life choices and the limits of fighting.
• “The Dirty Drug and the Ice Cream Tub” (Radiolab): The saga behind rapamycin, the drug that saved David’s life.

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For more on Dr. Fagenbaum’s work: everycure.org
His book: Chasing My Cure

Transcript

[Latif Nasser]

Oh, wait, you're listening.

[Dr. David Fagenbaum]

Okay. All right. Okay. All right. You're listening to Radiolab Radio Lab from wnyc.

[Latif Nasser]

Hey, I'm Latif Nasser, this is Radiolab. And today I want to share a conversation that I had with a guy named David Fagenbaum. He's a doctor and a professor at the University of Pennsylvania. And there's a combination of reasons why I think his personal story is so extraordinary and why I wanted to share with you. Part of it is this staggering series of crises that he faced in his personal life, starting when he was in university. Part of it is kind of his personality, like, how he. What there was in him that made him stand up to these crises in a really particular way. And then part of it is the way that he. He took his response to those crises, and now he's scaling it up using one of the most controversial technologies around, AI. The result of all of this is that he is right now in the middle of doing something wildly ambitious, something I find kind of miraculous also, maybe troubling. Either way, it is definitely going to change the medical system down to the level of the pills that you put in your mouth. That said, I just found my conversation with David so fascinating and his personal backstory in general. I found it so dramatic that I wanted to let it unfold at its own pace without jumping too quickly to the end. So here we go.

[Dr. David Fagenbaum]

Yeah. And then I'll hit Join studio Latif. Hey, how's it going?

[Latif Nasser]

Oh, my God, it's great. How you doing?

[Dr. David Fagenbaum]

Doing good. We've got double mics here. I've got a friend who's here helping with.

[Latif Nasser]

Nice.

[Dr. David Fagenbaum]

Helping with the audio. So we're double mic'd right now.

[Latif Nasser]

Great. So are we good to begin?

[Dr. David Fagenbaum]

Sure.

[Latif Nasser]

Okay. Let's begin with the Beast. Tell me, who is the Beast and what is the Beast? And where did the Beast start?

[Dr. David Fagenbaum]

Yeah, I don't know if I've ever answered a question this way, but. So when I was in medical school, I worked out all the time. And part of that was because for the previous 15 years of my life, I was obsessed with wanting to be a college quarterback.

[Latif Nasser]

And why. Why was it. Why was that the thing, you know?

[Dr. David Fagenbaum]

So I grew up in Raleigh, North Carolina, where college sports are really big, and NC State had a football team. And I grew up sort of, like, loving their team. But I think maybe more than anything is once I started playing football and I started like, I'm biased, but I think football is. Is unique among team sports and that you connect with your teammates in such a way, because literally, like, your health and your life is, like, on the line. If someone else doesn't do the thing to protect, especially as a quarterback, you don't do that to protect them. As a quarterback. Yes. And so I just fell in love with football as a kid. I mean, as a kid, I just was in love with it. If you could have seen my walls when I was growing up. Literally every corner of every wall in my bedroom was covered with charts measuring, like, how far I could thr. Fast I could run, all with the goal of getting better.

[Latif Nasser]

But you actually get. You get your dream. You get to.

[Dr. David Fagenbaum]

I get my dream. I get this opportunity to go to Georgetown to play football. And it was the dream where it was like, okay, I can go to a great university that has a health science program, so I can keep studying health science and I can play football. I really love the coaches there. But then I got to school, and I was there for only a couple of weeks before I got this just horribly devastating call. My dad called and said, david, your mom has brain cancer. You need to come home right away. So I immediately went back home to. To Raleigh. I was able to just see my mom just before her brain surgery. And then she went. We went to Duke for her brain surgery. And.

[Latif Nasser]

And what. What was the. What was the. Like, what was the horizon of possibility here? Like, what did you think was going on? What did you think was possible?

[Dr. David Fagenbaum]

Yeah. So before the brain surgery, they just said, it's. It's a brain tumor. It looks like it's brain cancer, but we need to go in there and actually see what it is. So, you know, my family and I, we were just so. Just nervous about everything because, you know, they did warn us before that, you know, the person that comes out of surgery isn't always the person that goes into surgery.

[Latif Nasser]

Yeah.

[Dr. David Fagenbaum]

And I remember going back to see my mom with my dad, my two older sisters, and she had this wrap around her head. She had a bandage around her head from where the tumor had been resected. And she had this bulb that was coming out of the incision site. It drains out fluid from the incision. And we were all so nervous. No one really knew what to say. We said, you know, mom, how are you doing? And she pointed up at her, at her head, and with this bulb and the wrap around it, and she said, chiquita banana lady, which is, like, referring to, like, if you look at this sticker on your bananas, there's, like, you know, there's the chiquita banana lady. She has a wrap and she's got all the fruit.

[Latif Nasser]

Yeah.

[Dr. David Fagenbaum]

Her head kind of looked like the chiquita banana lady. And, like, it was exactly what we needed. It was like, exactly what we needed. Like, we all burst out laughing and crying, and we're not crying and, like, our mom's with us. Like, it just. Yeah, like that. Yeah, that's just.

[Latif Nasser]

She's still herself.

[Dr. David Fagenbaum]

She's still herself. That's like. That's who she was.

[Latif Nasser]

Yeah. What was this sort of prognosis after that? Or what was the timeline?

[Dr. David Fagenbaum]

Yeah, so the doctors came in and they explained that it was the. It was. They explained it as grade four glioblastoma, which the average survival is around six months. And I think they said the longest someone had survived, I think I remember it was around five years. So I spent a few more days at home after surgery and just, like, would not leave her side.

[Latif Nasser]

And then when and how long did your mom last?

[Dr. David Fagenbaum]

She lived 15 months after diagnosis. She was diagnosed July of 2003. She passed away October 26th of 2004. But while I was home, we had a lot of just really special time together. One of the things we did was actually go through old home videos. Like, you know, we had these, like, Betamax videos. I don't know if you remember these, like, old home videos. Went through them and just we did, like, all the things that you would, you know, want to do, all the things that, you know, you'd want to do before, you know, someone like, my mom passes. And this was 21 years ago, did all those things. And. And it was. It was really special. And it also, as you can even tell, this is 21 years later. It created such a drive in me to just say, yeah, I want revenge. I want to do whatever I can to take this thing on.

[Latif Nasser]

Yeah.

[Dr. David Fagenbaum]

And I told her I was like, mom, I'm going to dedicate my life to trying to help people like you. Like, that's just like, full stop. Like, this whole football thing that was fun these last eight years. But, yeah, I'm going to be a doctor, and I'm going to dedicate my life to just find treatments for this horrible thing that was taking my mom from me.

[Latif Nasser]

Yeah. Okay, so now cut to. So you finish college, you get into med school.

[Dr. David Fagenbaum]

Yeah.

[Latif Nasser]

The same way that you were calorie counting and. And quizzing yourself on playbooks like you're doing the same thing. Except now cancer is the. Is the other team.

[Dr. David Fagenbaum]

That's exactly right. And of course, the Challeng in med school is it's very much a training period, which is hard for someone like me. Right. It's like, you know, I wanted. I want to take this on. I want to make a difference, But I'm in this period where, yeah, I've just got to train, train, train.

[Latif Nasser]

So you're doing that and then. And then at some point, yeah. Okay. And so what happens?

[Dr. David Fagenbaum]

So I'm on my OBGYN rotation and just started noticing that I was more tired than I'd ever felt. And I sort of always was able to run on low amounts of sleep and lots of caffeine, but I was really, really tired. Like, this fatigue that I had never felt before. And I remember sort of like, trying to just, like, put it out of my mind, like, whatever this is, is going to go away. And I went into the hospital to take this medical school exam, and I remember during the exam, I was, like, dripping sweat head to toe, and then I was like, you've never felt like this before. Something's going wrong. I also had noticed these bumps appearing on my body. They're called blood moles, and they're normal as you get older, but they are abnormal to appear rapidly. And it's like, as I was this exam a couple days before, I, like, noticed these blood moles on my body. And so I actually handed in my exam, and I just walked down the hall to the emergency department in the same hospital that I was taking the exam in, and I just told them about my symptoms. They did blood work, and I had worked in that ER just a few months before, and doctors are usually really slow to come back. And it's like, things take a while unless there's something really wrong, and they come back really quickly. The doctor came back really quick, and he told me, he said, david, he said, your liver, your kidneys, your bone marrow, your heart and your lungs are shutting down. We have to hospitalize you right away. And I was just.

[Latif Nasser]

That's, like, the whole body. Like, what. What else is there in your body?

[Dr. David Fagenbaum]

Yeah, there's, like, your brains left, but, like, pretty soon that was gonna, you know, not be as clear.

[Latif Nasser]

Right.

[Dr. David Fagenbaum]

But, yeah, it's this concept called multiple organ system failure, where everything was shutting down. And so they hospitalized me. I, um. And I just. Just went downhill from there. I started getting really sick really quickly, and I knew things were bad, and the doctors were using the language that I had used when I talked to patients when things were really bad.

[Latif Nasser]

And, like, what were they saying exactly?

[Dr. David Fagenbaum]

You know, we're. We've run a lot of tests and, you know, we're, we're, you know, we're on top of things, but we're not really in a position yet to tell you exactly what we think is happening. And it took a total of about 11 weeks before we finally made the diagnosis. And with that diagnosis came almost immediate use of a type of chemotherapy.

[Latif Nasser]

Well, before we get there. Before we get there. So what was the diagnosis? What was.

[Dr. David Fagenbaum]

Oh, yes, yes. So the diagnosis was what's called idiopathic multicenter Castleman disease. Kastelman disease describes a group of these rare diseases where basically your immune system attacks your organs for an unknown cause. We call it idiopathic as we don't know what the cause is.

[Latif Nasser]

And had you ever heard of that? Like, as a med student?

[Dr. David Fagenbaum]

When I heard it, When I heard it the first time, I vaguely remembered, like, I think I've heard that once in med school. That's how rare it was. I was like third year med student and I think I heard it once. Yeah. But definitely not. I definitely wasn't familiar with it.

[Latif Nasser]

Right.

[Dr. David Fagenbaum]

And.

[Latif Nasser]

And was that you get the test done finally? Yeah. Can you talk about that moment?

[Dr. David Fagenbaum]

Sure, yeah. So we were really happy that it wasn't cancer. We were like, yes, this is not cancer. We thought it was lymphoma this whole time, and it's not. And then there was this really quick realization shortly thereafter that my subtype of calcium is idiopathic. One of these intracalcinom disease actually has a worse survival rate than lymphoma does. And that actually the thing that we were hoping it was not actually would have been better than the thing that it turned out to be. And I was so sick when the diagnosis came in that the doctor told my family, we don't know if this medicine is going to work, but he's so sick that we don't think he's going to survive much longer. You should go ahead and say goodbye to him and prepare him for not being here.

[Latif Nasser]

And you were awake and aware of that happening?

[Dr. David Fagenbaum]

I don't know if I was. Mentally, I wasn't totally there, but I do have some memories. And those memories are the room being really dark, my family hugging me and crying. And they just started telling me all the things that I told my mom. Right. Like what I meant to them. And we're reminiscing on old memories. And then I remember the priest coming in. I mean, of course, I'd never had my last rites read to me before, so it sort of like confirmed my Biggest fears, which is that, like, this is going to kill me. But just a couple days before the priest had come in, the doctors had tried this one chemotherapy. It was the only chemotherapy they thought to try. Like there actually are others they could have tried, but this was the one they tried. And amazingly it just started to kick in really within days. And it didn't last long term. I relapsed about a month later and it was a real roller coaster because the euphoria that we all had when I was feeling better and the hope that we had, and then just a few weeks later when it would come back, just the heartbreak. And that cycle happened a total of five times in three and a half years where I went from being totally, totally in a critically ill and ICU to much better to then back again.

[Latif Nasser]

And what was the moment? Was there a moment where you kind of engaged, where you were like, okay, I need to sort of activate?

[Dr. David Fagenbaum]

Oh, yeah, yeah. That moment, for me, I remember very Vividly it was May 12th of 2012. It was sort of. I mean, if I think back on, like, I'm my life in these moments, like the moment when I got the call from my dad that my mom had brain cancer. And the moment I was sitting in the hospital room and my doctor explained to me that the only drug that had ever been studied for my disease wasn't working and that there was nothing else. And I was just searching for something like, is there a gene or a protein or a cell or something that we might know about this thing? Give me something. Begging for some lead. And he just was clear, there's nothing like, like you are going to die from this disease. The chemotherapy is going to stop working and there is nothing out there. That was when I. Everything changed. Everything in me shifted. If I want to survive, like, if I want to spend more time with this girl beside me that I love, Caitlyn, and I want to get married to her one day. I want to spend more time with my family. Like, I've got to activate. And it was right around that time I was learning about how a drug that was being used for Kasselman's was also working for other diseases. And I was like, wait a minute, there's a Castleman's drug working for other diseases. Is there anything somewhere, maybe there's another drug for another disease that could work for me. Like, it just was sort of like this like, very simple concept. And it frankly, it was the only path. It wasn't like, I was like, oh, it would be great to do this or to do that, it was like this was the only path was to find an existing medicine. And that became just my central focus.

[Latif Nasser]

So what do you do? How do you even start that?

[Dr. David Fagenbaum]

Yeah, first thing I did is I went to my mentor, Arthur Rubenstein. He was the dean of the medical school before, and he just retired. And so I went to him for advice and his support, and he said, david, I'll support you. And he's been amazing over these years, but so I wanted to go to someone who sort of, like, could give me advice. I didn't know what I was doing.

[Latif Nasser]

So you're like, I just need. I need help. I need a team. I need people.

[Dr. David Fagenbaum]

I need to build a team. Exactly. It was like, I don't know what I'm doing, but I need to build a team. So first went to Arthur. He came on board. The second task would be to understand what was going on in my blood and in my immune system and see if there was something that was already approved for another disease that could maybe be repurposed to treat me. And that's when I, you know, I guess they did the equivalent of, you know, covering my walls in poster boards for throwing the football, and it just became all encompassing. I gotta find a drug for this disease. And I remember turning to Gina, my sister, and saying, g, I need you to call Unc and Duke. I need you to get all my medical records, ship them to Philadelphia. I need you to get all the blood samples and lymph node samples at each of the hospitals. They need to be in Philly, because I'm gonna get out of here in a few weeks. And when I get to Philly, like, the clock's ticking. I need to get to work. And her and Caitlin just got to work. And a few weeks later, I was back in Philly. And the blood samples were there, the lymph node samples were there, the medical records were there. And I just. It was all day, every day, to try to find a drug.

[Latif Nasser]

And I presume at that moment, too, you're like. And another. Cause another flare is, like, right around the corner.

[Dr. David Fagenbaum]

It's coming. Exactly. Yeah. And Caitlyn and I.

[Latif Nasser]

It's like a train coming.

[Dr. David Fagenbaum]

It's a train. And it's hit me. It's hit me five times. There's no chance. It's not coming back. This was. It's. It's coming, and. And I don't have another shot. And I had a really big date in front of me. May. May 24, 2014, was Caitlin and I's Wedding day. We were. We were engaged. And now we're talking January of 2014. So I had, you know, about four months between getting out of the hospital and making it to our wedding day.

[Latif Nasser]

Like, if you last that long.

[Dr. David Fagenbaum]

If I last that long, yeah, exactly.

[Latif Nasser]

Yeah. Okay, so then. So what do you. What. What do you do?

[Dr. David Fagenbaum]

So I thaw all those samples, and I started doing something called serum prote, where the idea is you measure a thousand different things in your blood or a thousand analytes or proteins in your blood. And then we did something called pathway analyses, where we try to understand what are the signals in the blood that are coming from these proteins being up or down. I did something called flow cytometry to look to see which of my immune cells were turned off and turned on. And then cytokine panels where we measured these 13 different proteins and their changes in the blood. And what emerged was that my MTOR was in overdrive. And MTOR is a communication line your immune system uses to turn on, to turn off, to proliferate. And when I saw that result, I immediately remembered that there's a drug called sirolimus, the other name for its rapamycin, that is really good at turning MTOR off. It's an MTOR inhibitor. So, like, I saw the result. It's like, MTOR is on. And I was like, oh, my gosh, isn't there a great MTOR inhibitor? And it.

[Latif Nasser]

Rapamycin. That's the drug.

[Dr. David Fagenbaum]

Rapamycin is the drug that saved my life.

[Latif Nasser]

Oh, my God. We did a. We already did a story about rapamycin. I didn't even connect it in my head.

[Dr. David Fagenbaum]

And I loved that story, Latif. I listened to that story and I loved that story. And of course, it's found on the island of Rapa Nui.

[Latif Nasser]

Yeah, yeah, yeah.

[Dr. David Fagenbaum]

Hidden in a freezer in Canada.

[Latif Nasser]

Like, I connected mtor, but I didn't connect that it was rapamycin. It was literally rapamycin.

[Dr. David Fagenbaum]

Yeah.

[Latif Nasser]

So it's like you find in the tests of your blood and your lymph node and whatever. Like, it's like that is leading you to a problem. And then you're like, is there a drug that solves this problem? And you're like, oh, there's one drug right there.

[Dr. David Fagenbaum]

That's exactly right. And so I told one of my doctors, and I went through all the data, and I just said, like, do you think that we should try this? Like, I know it's never been used before for Castleman's, but, like, can we try like, should we try it? And his thought process was like, probably it's about a 10 to 20 chance it could work, but it's a 0% chance if I don't take it. And. And I'm willing to take that risk. And so he said, yeah, I'll prescribe it.

[Latif Nasser]

And so you do it and then what happens? You take it. It's a pill.

[Dr. David Fagenbaum]

It's a pill. It's three pills. Well, at first it was. I took five pills, and then. And now it's three pills. But within a couple days, I started to feel better and the blood work started to get better more rapidly than it would have otherwise. But again, I still wasn't ready to say, like, this drug is working. And so for me, I was like, I'm not going to get my hopes up. It's going to be a test of time. Am I going to make it to my wedding day? Am I going to make it a year? Am I going to make it longer than that? And yeah, just four days ago marks 11 and a half years that I've been in remission on this drug. I mean, I almost died five times in three and a half years before, and now it's 11 and a half without this disease coming back.

[Latif Nasser]

Wow.

[Dr. David Fagenbaum]

Amazingly, it weakens my immune system in the right way so that I don't attack my own organs.

[Latif Nasser]

Wow.

[Dr. David Fagenbaum]

And I mean, the moment that that drug, the moment that I started thinking that drug was helping me and knowing that it was always there for something else. And then certainly as the time went on when I got to marry Caitlin, and then as the years have gone on, I've just gotten more and more obsessed with this idea because I'm literally breathing and alive because of a drug that wasn't made for my disease. I just feel this tremendous sense of responsibility that, like, hey, David, if you're going to get lucky enough to have one of these medicines help you, you sure as hell better spend the rest of your time trying to find as many more of these medicines to help other people.

[Latif Nasser]

What happens next is that this story moves from being a personal story about David finding his own medicine for his own disease. And thanks to some supercharged technology, it becomes a story about all medicines and all diseases. And the entire way we figure out which works for which. That's after the break. Radiolab is supported by Capital One Banking with Capital One helps you keep more money in your wallet with no fees or minimums on checking accounts and no overdraft fees. Just ask the Capital One bank guy. It's Pretty much all he talks about. In a good way. He'd also tell you that Radiolab is his favorite podcast too. Oh, really? Thanks. Capital One Bank Guy. What's in your wallet? Terms apply. See capitalone.com bank capital1na member FDIC.

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[Planet Money Narrator]

Planet Money helps you understand the economy. We find the people at the center of the story.

[Latif Nasser]

Garbage in New York that was like a controlled substance.

[Planet Money Narrator]

We show you how money influences everything.

[Dr. David Fagenbaum]

Tell me what you like by telling.

[Planet Money Narrator]

Me how you spend your money. And we dig until we get answers.

[Latif Nasser]

I had a bad feeling you're gonna bring that up.

[Planet Money Narrator]

Planet Money finds out, all you have to do is listen. The Planet Money podcast from npr.

[Latif Nasser]

This is Radiolab. I'm Latif Nasser, and we are back with a conversation I had with Dr. David Fagenbaum, who, after almost dying five times, started obsessively studying his own body, his own disease, to try to find a drug, any existing drug out there that might be able to help him. And he did. And after three years of being repeatedly at death's door, he's now been in remission for 11 years. After he found that cure, he turned his kind of monomaniacal mind, and not just that, his whole lab at the University of Pennsylvania, toward understanding his disease, Castleman's disease, hoping to do the same for other people who are suffering from it.

[Dr. David Fagenbaum]

So that led us to then say, okay, we need to do more laboratory Work. We need to start uncovering more pathways that might be important, more genes, more, more proteins that are important. And so we started getting really involved in that sort of laboratory work. And in parallel, the next probably big milestone to go from like, okay, we help someone else. My disease was actually, my uncle was diagnosed with angiosarcoma, which is a horrible form of cancer. The same week that my brother in law was diagnosed with als. I went down to Raleigh to be with my brother in law. Happened to be the same week my uncle got diagnosed with angiosarcoma. So I went with my uncle to his doctor's appointment and the doctor explained, you know, there are these two chemotherapies and they'll, you know, give you a couple months to live, but they're, they're going to stop working. And so I suggested that we start, you know, looking for drugs that could be repurposed. And his doctor explained, like, there just, there isn't anything for angiosarcoma. I'm like, yeah, I know, but like, there wasn't anything else for Castleman's and like, you know, I'm here, maybe we can find something else for angiosarcoma. And that's when we came across a study that had been published.

[Latif Nasser]

And is that annoying? Like, are you annoying to them when you do that?

[Dr. David Fagenbaum]

I'm so annoying to them. They're like, they're looking at me and they're like, your uncle has a terminal illness. The last thing he needs is for his nephew to tell him or me that there's a treatment out there that could help him. Like, that's not what he needs right now is what they're thinking. And in my mind I'm like, are you kidding me? He's still here. He's still breathing. I just walked past the CVS and last time I checked, there's 4,000 drugs in that CVS. And I know those 4,000 drugs haven't been tried for him. So until we've tried all 4,000 drugs, you can't tell me there isn't a drug in there that can help him. Okay? And so we find a study that had been published three years earlier that basically says that four out of five people with my uncle's cancer have very high expression of something called PD L1. I'm here saying, like, let's test this tumor for PD L1. And the doctor says, I'm not going to test it because no one with angiosarcoma has ever been given a PD1 inhibitor. I think there's like a less than 10% chance that this gene panel that you want to order for Michael is going to come out with anything helpful. And I hear less than 10%. And I'm like, that's great. Less than 10%? Like, you mean like 5%? He's like, yeah. I'm like, amazing. So you're telling me there's a 5% chance that this test is gonna give us something that's gonna keep him alive longer than two months? Amazing.

[Latif Nasser]

You're like the dumb and dumber guy.

[Dr. David Fagenbaum]

So you're saying there's a chance.

[Latif Nasser]

That's right. Yeah. Yeah, yeah. That's the guy. You're that guy.

[Dr. David Fagenbaum]

Yes. And so I don't blame them, because when you're a doctor and you do this a hundred times and it works one in a hundred times, that is frustrating. But when you're a patient and it helps you, that one in a hundred times, it's everything.

[Latif Nasser]

Yeah.

[Dr. David Fagenbaum]

And so I got another doctor to order the test. So we get the test results back.

[Latif Nasser]

You are such an annoying patient.

[Dr. David Fagenbaum]

Relative. I'm so annoying. I am. Yes.

[Latif Nasser]

Yeah. Okay.

[Dr. David Fagenbaum]

So it comes back. Well, first I should say I had him order two tests. The first of the test, it came back with nothing informative. He was totally right. And that was actually the expensive test. That was a test that cost $2,000 that came back with nothing useful. So I will totally give it to him. The inexpensive test that I wanted him to order came back. 99% of his cancer cells were positive for PD L1 expression. 99%, which is not a guarantee, but it is a high likelihood that, therefore, a drug that inhibits this might be useful. And we got Michael on this medicine, and April of this year marked nine years that he's been in remission from his angiosarcoma.

[Latif Nasser]

Oh, wow.

[Dr. David Fagenbaum]

Other patients have been treated with this. Other doctors learned about this and started treating their patients. And it turns out about a third of people with this horrible cancer, previously uniformly fatal cancer, will respond really well to pembrolizumab, to this medicine. It's now standard of care for his form of cancer.

[Latif Nasser]

It's now standard of care.

[Dr. David Fagenbaum]

It's now standard of care without ever doing a clinical trial. And that goes to show you when you have a disease that's this bad and you find a drug that works this well, you can change the paradigm for the disease for relatively, I mean, as close to $0 as humanly possible.

[Latif Nasser]

But, like, why is it that everything is so like. It's like we almost have this idea of like lock and key, like this medicine does this thing for this drug and da, da, da, da. But then it's like. And then you're like, no, no, no. But this lock, this key works in this lock over here. Like, why is it that. That. Is that anyway? Yeah, tell me there.

[Dr. David Fagenbaum]

So the reason I think that our system is like this drug works for this disease is because in order to get a drug approved, a drug company has to develop a drug for a specific disease and submit it to the FDA for that disease. The FDA approves it for that disease. And if that drug company mentions a single word about that drug working in another disease, they will get fined billions of dollars for what's called off label promotion. So when the FDA approves a drug, what they're really doing is they're approving a drug company to market a compound for a specific disease. And that company cannot market that compound for any other diseases until they come back to the FDA to get that change made. But every time a drug company does that, it costs lots and lots and lots of money. So they don't go after all the opportunities they have. But insurance companies and payers realized, well, if this drug that's approved for this one thing could also be useful in this other thing, and it would be good for patients, shouldn't we allow doctors to prescribe things off label? And so that's something that happens very commonly. About a quarter of all prescriptions in the US are off label.

[Latif Nasser]

No.

[Dr. David Fagenbaum]

Yeah. So it's somewhere between 20 and 30% of all prescriptions written every day in the US are off label.

[Latif Nasser]

Are not for the reason they're supposed to be.

[Dr. David Fagenbaum]

Yeah, exactly. So that includes examples like doxycycline for Lyme disease, where every doctor in the world would be like, yes, use doxycycline for Lyme disease. But doxycycline is a cheap, old generic antibiotic. So Whoever made doxycycline 100 years ago, 30 years ago, when people figured out it worked for Lyme disease, they aren't going to submit for a label change. And that gets into the other factor here, which is that once a drug becomes generic, whoever originally made the drug, they stopped making money off of the drug because you have generic competition. You have multiple companies that make the identical drug and the price plummets per pill. And so no one in our system makes any money off finding a new disease for that drug.

[Latif Nasser]

But why wouldn't. You would think from the drug company's perspective that they would want to go to the FDA get as many uses approved as possible. Because then they could go out and say, this helps this, this helps that. This helps this help that. They would make their market as big as possible.

[Dr. David Fagenbaum]

Except it's more complicated than that because you can only sell a drug for one price. Regardless of what disease you sell it for, it always has to be the same price. So what that means is that you have to pick the first disease that you get your drug approved in. You have to pick the optimal market for that drug for the optimal price, because pricing is actually not based on the cost of the medicine. Pricing is based on the value for that disease. So the fewer competitors there are for a disease, the more expensive the drug, the rarer the disease, the more expensive the drug. There's all these factors that affect how expensive the drug is going to be. And you want to. If you're a drug company, you have to maximize your profit. So you need to come up with the highest price for the highest number of people. But it might be that a low number of people at a higher price is better than a high number of people at a lower price. So you can imagine it gets really complicated really quickly. And it's all about the first disease. You get your approval. And so companies have to be really thoughtful and strategic to maximize their profits about what their first approval is. Once they get that first approval, now they have to remember that they can't change the price for the next disease. And so this is this horrible economic issue, which is just so depressing because, like, on the other side of these economic issues are people suffering.

[Latif Nasser]

Okay, I want to hear more about what you're doing now. You're like, amazing. This works for me. How does that then go to. Oh, no, wait a second. I'm not just doing this for my family. I can. I can big this up.

[Dr. David Fagenbaum]

Yeah. The next big milestone was early in the pandemic. I was actually driving down to Raleigh, North Carolina, had my wife in the car, and I'm listening to the radio about this pandemic. And I'm sitting there thinking, gosh, this involves the immune becoming activated and causing all these problems. And, gosh, it's going to take us months or years to come up with new drugs. I really wish there was a lab somewhere out there that was really good with inflammatory stuff and could repurpose drugs and could, like, direct drugs at this thing. And then I was like, oh, maybe we should do that. And so that. So we decided to create a program called the Corona Project, where basically we redirected my, like, 15 member lab to focus specifically on Covid. And early on, as you'll remember, there was a lot of drugs that were repurposed. Some worked, some didn't work, but there's a lot of repurposing. This is the first time we did, like, a very concerted effort to be like, what else is out there for this one disease? Very much informed by what we'd done previously. And Covid, of course, there's lots of controversy about what worked and what didn't. But the two drugs that unquestionably worked incredibly well were dextamethasone and tocilizumab. They saved millions of lives, and they were old drugs, have been around for a long time. And so that further got my wheels turning on, like, what if we could create a system to automate what my little lab was doing for one disease? But we did it for all diseases and all drugs simultaneously. And thankfully, and in parallel to those dreams, the field of machine learning, artificial intelligence, has matured so much that we can actually do that.

[Latif Nasser]

Okay, so tell me about AI. How are you using AI to matchmake here? How did you think? Like, okay, this part of it can be done by AI or this part of it or whatever, that kind of thing.

[Dr. David Fagenbaum]

So in my case, you can think about this. We use what are called biomedical knowledge graphs, which are just sort of mapping out every medical concept on a map. So you can imagine, like, if you had this giant wall and every single gene, every disease, every protein, every pathway was put against the wall. So if we were to start with that concept and say, well, what do we do for me? Well, you'd find Castleman's on that wall. It would only be there in one place. You'd find Castlemans. And what you'd find is you'd find an edge or a line between Castleman's and activated T cells. Because I discovered that T cells were activated in my disease, you'd find another line to MTOR activation, because I discovered that MTOR activation was really up in my particular immune cells. And then you would find a drug from T cell activation and MTOR activation to Sirolimus. Right, the drug, because sirolimus is able to inhibit MTOR activations and able to inhibit these activated T cells. And so now, within this giant graph of every disease, every gene, every protein, you would find Castlemans with lines or edges to these two concepts, and then lines or edges to sirolimus, and you would see a connection between them. And so now imagine doing that for every disease, every gene, every protein Basically, what the world knows about all of medicine.

[Latif Nasser]

It's almost like mechanical, what you're doing. It's like.

[Dr. David Fagenbaum]

It is.

[Latif Nasser]

It's like you're trying to make like the mechanical blueprint of what is going on.

[Dr. David Fagenbaum]

That's exactly right. This leads to this, leads to this. And this reverses this, which reverses this, reverses that. Everything is there. It's this, it's the. It's. It's everything. Well, now what we do is we train machine learning algorithms on all of those known treatments. Treatments. So, like the sirolimus for Castleman's, sildenafil for pulmonary arterial hypertension, you know, insulin for diabetes. Imagine training this algorithm. Because machine learning algorithms are so good at finding patterns. And so we're giving the machine learning algorithm lots of information about known treatments. And we're saying this is an example of when a drug works for a disease. And we do it thousands of times with all of the treatments that are out there for all the diseases that are out there. And then we say, okay, algorithm, now go and score the how close of a pattern the connection is between a known treats relationship for every other drug versus every disease. So if a toenail fungus drug looks like there's no way it could work for pancreatic cancer, you need to give it as close to a zero as possible. 000-000-0001. Right.

[Latif Nasser]

Right.

[Dr. David Fagenbaum]

But if leucovorin looks really promising for a subtype of autism because the pattern of connections are there, and there's a clear intermediary between that subtype of autism and that metabolite, give it a high score. So you get a 0.99. And so now what we do, we do all 4,000 drugs, all 18,000 diseases. So it's about 75 million scores that we generate that our machine learning algorithms generate. And then that gives us a list in rank order from the things that are 0.99 all the way down to things that are 0.00 of every drug versus every disease. And so we come across matches that are incredible, that we never could have imagined that. Now the algorithm is saying, you should really look at this. This.

[Latif Nasser]

It's like the body is so complicated. These drugs are so versatile. It's like our minds can't even comprehend that. It's like, that's why you need to.

[Dr. David Fagenbaum]

Go to AI you would have to, as humans, think about 75 million possibilities. My lab's really good at looking at dozens of possibilities for one disease. My lab can spend a year, we get through a few dozen for one disease. But we could never think about 75 million possibilities and then compare them. And I'm not saying AI is perfect, but directionally it's really good. The things that are the point nine nines are way better than things that are the zero point fives.

[Latif Nasser]

How likely do you think it is that, like, if there's an ordinary person with an ordinary disease that existing treatments don't work for that there is something in there for them?

[Dr. David Fagenbaum]

Yeah, I guess there's two probabilities here. I think that one is that what is the likelihood that there is a drug out of those 4,000 that could work for that disease? And then what's the likelihood that, that you or anyone else is going to find it? Right. Because it's just like A, does it exist? And B, can you find it? Yeah, I think that A, does it exist? This is obviously a really hard thing to guesstimate on, but like I'm going to say somewhere in the realm for any given disease, somewhere in the realm of maybe 10 to 20% that there's something out there. And then in the realm of are you or is a team going to find it in time for you? It becomes much lower than 10 to 20% likelihood. Right. Just because the steps that have to happen. And so for us, we're going to be the organization that is going to identify and unlock as many of these drugs as possible. So that way we don't have to be throwing Hail Marys so that when you get diagnosed, it's, oh wow, you have pulmonary artery hypertension. You should just take this medicine. Oh wow, you have glioblastoma, you should take this medicine. And so we've intentionally taken the approach of let's use AI and data to find the best uses for the best drugs so that we can move them forward. So that way we aren't doing Hail Marys. But the reality is, Latif, is that like, people are suffering all the time and we are contacted all the time and we want to help any way we can. And, and we're going to be making our algorithms publicly available in about nine months time.

[Latif Nasser]

Interesting.

[Dr. David Fagenbaum]

But until then, we want to continue to improve them. We feel this tremendous responsibility that once we share it, that, you know, it's out. Right. And so, so we're going to continue to improve over the next nine to 12 months, but then we will share it.

[Latif Nasser]

And are you imagining patients would use that or are you imagining doctors would do that?

[Dr. David Fagenbaum]

So the intention will be for doctors and researchers to use it. So that way they can come up with new areas for research. They can think about it for their patients. But the reality, I think, is that patients will also use it.

[Latif Nasser]

I'm trying to imagine. So that is really interesting that you're making that public. And I think it's also like, it's. There's something beautiful and hopeful. So the conversation went on for a while after this, but I was honestly surprised and a little taken aback that this algorithm that David had made, that he was going to take it public. And it took me a while to kind of process that and figure out, like, what I thought about that or what I even wanted to ask him about that. That part of the conversation, which actually felt a little bit trickier to me, is coming up right after the break. Stick around.

[Planet Money Narrator]

Planet Money helps you understand the economy. We find the people at the center of the story.

[Latif Nasser]

Garbage in New York, that was like, a controlled substance.

[Planet Money Narrator]

We show you how money influences everything.

[Dr. David Fagenbaum]

Tell me what you like by telling.

[Planet Money Narrator]

Me how you spend your money. And we dig until we get answers.

[Latif Nasser]

I had a bad feeling you're gonna bring that up.

[Planet Money Narrator]

Planet Money finds out. All you have to do is listen. The Planet Money podcast from npr.

[Latif Nasser]

Okay, so I did that interview with David Fagenbaum. And it's funny, he genuinely surprised me when he said he was taking this thing public. Like, I had not heard or seen that before. It has since been reported that he's doing that, but when we did the interview, like, I didn't know he was gonna say that. And so when he said it, I was, like, kind of shocked that he would do that. It, like, re slotted the story in my brain from being like a slam dunk, like a no br or best possible use case for AI to something that was like, wait, wait, wait, What. What do I think about this? Should ordinary people be able to look up what drugs AI thinks will help them? Is that. Is that helpful? Is that reckless? So I really didn't know what to think. I called up a bunch of my doctor friends. Some thought it was, like, so exciting, especially for people with rare diseases, you know, where there's not a lot of research money. They were like, yeah, this tool is going to be so useful for so many people. But then there were other doctor friends of mine who said, no, no, no, this is gonna make my job harder, and it's gonna hurt people, which you will hear more about in a minute. Anyway, so I called David back, and I had way more questions. And I was just like, okay, just tell me the specifics. What are you Putting out there. Exactly. And why are you so sure this is a good idea?

[Dr. David Fagenbaum]

Sure.

[Latif Nasser]

I don't even know what to call it. Like, okay, your AI matchmaking tool. What do you call it? How do you use it?

[Dr. David Fagenbaum]

Yeah, so we call it the Matrix. So it's an acronym. Everything has to have an acronym in my life. It's so it's ML Aided Therapeutic Repurposing and Extended Uses Matrix.

[Latif Nasser]

Okay, so ML Aided Machine Learning Aided Therapeutic.

[Dr. David Fagenbaum]

T for Therapeutic Repurposing Ring. Yeah, I. In. And then it gets a little sloppy. Then extended. We're using the X in extended.

[Latif Nasser]

Okay.

[Dr. David Fagenbaum]

X for matrix uses.

[Latif Nasser]

Oh, okay. Then uses.

[Dr. David Fagenbaum]

There's no uses. Doesn't get a letter. It's not matrix to use, it's just matrix.

[Latif Nasser]

Okay, because you're a fan of the movie or something.

[Dr. David Fagenbaum]

It actually is a matrix in that it's 4,000 drugs, it's 18,000 diseases. So it's actually. We're building actually a matrix of drugs versus diseases and a fan of the movie.

[Latif Nasser]

Okay, so how does it work? Like, say I'm just somebody. I'm a random patient with random disease and I want to use it. What do I do?

[Dr. David Fagenbaum]

Yeah, so we're still working on some of these things. We're actually, like, literally, like, talking about prototypes and processes. But I can tell you that there'll be the ability to type in the name of your disease or maybe the drug that you care about, probably more likely the disease that you care about, because most people care about diseases as opposed to drugs, but then actually to look at a rank order list for that disease. So say like, oh, wow, I care about ALS. These are the 4,000 drugs ranked in order for ALS according to this AI platform that I'm almost certain will be available in a format like that. But the bells and whistles we sort of. We still have to work out.

[Latif Nasser]

Is it like a chatgpt style thing? Like, I'm imagining? Like, you put your disease name into the thing, and then it'll like, spit back out at you a bunch of names of drugs and it'll give you the percentage.

[Dr. David Fagenbaum]

Yes.

[Latif Nasser]

But then you can also be like, hey, by the way, I'm also a smoker and I have diabetes, or whatever other conditions you have. And then it'll like, how much information would you put in, like, as a user?

[Dr. David Fagenbaum]

I mean, what you're describing would be sort of like a holistic patient support treatment tool. And we're really not building that. I hope someone does. Like, someone should build that. But we're not building A tool that is. Yeah. Is going to be that sort of treatment copilot though I would love for someone else to do it.

[Latif Nasser]

Okay, so this is very much just insert name of disease and what's going to come out is a list of names of drugs that may or may not work. And here's the odds that they will.

[Dr. David Fagenbaum]

Yeah. And these are in the same list that we're getting on our medical team and our research and development team. We're giving you the same results and same scores that we're getting because we feel this obligation or this responsibility that if we're going to put our eyes on them, the world should be able to put their eyes on them. You know, here are the tools that we use. Like our medical team uses these same machine learning algorithms. You can use them too. But it's important to remind them that when our medical team uses those machine learning algorithms and they come up with something like lidocaine for breast cancer, we still then go on to do a bunch of laboratory work of lidocaine and breast cancer and then we think about doing the right clinical trial of lidocaine and breast cancer. So it's not like we use the algorithm to immediately move forward into action. We use it to then and plan out what to do next.

[Latif Nasser]

Okay, so why did you make the decision to make it public?

[Dr. David Fagenbaum]

So our feeling is that we, as a non profit, at every cure, we're only going to be able to go through like dozens. I mean if we can get into the hundreds, I would be over the moon about it. But like there are still thousands of diseases that like could potentially benefit from our scores that we'll just never be able to get to. Unless it's like.

[Latif Nasser]

Because the list that matrix is spitting out is just so big. Is that it?

[Dr. David Fagenbaum]

It's so big and it's so powerful. The things like when we look at the top, we are blown away by the number of promising drugs. We're like, wow. And actually some of the cases, there's actually been clinical trials that have shown the drug works, but someone stopped after the small trial because there was no way to commercialize it. So one part is let's make it available to the world so that other people can pursue these things that we're not able to go after. And the other is sort of probably a little bit inspired by maybe we shouldn't be so paternalistic in medicine and may we should allow this information to be out there. Of course, when I say that, I do cringe just a little bit because I don't want us to create problems by putting this out there. But it feels like the responsible thing is to share the scores, but to appropriately caveat them and disclaim them to say, these are for research purposes at every cure or nonprofit. We don't take a score and then put that drug into a person. We take a score, we evaluate it by MDs, PhDs and MD PhDs. We spend months on it. And then we do laboratory studies, we do clinical trials. We work with experts to get into guidelines. That's our process. So we want other people to take a similar process.

[Latif Nasser]

Have you thought about what could go wrong by making this public?

[Dr. David Fagenbaum]

Yeah, a couple things immediately come to mind. I mean, number one is patient harm. A patient taking a medicine that causes harm to them that had not undergone the studies necessary to evaluate it in that disease. Now, the good news is that every drug we score is already FDA approved for something. So we're not. There's no drugs on there that like, someone be like, oh, my gosh, just never got a regulatory approval. They all have been approved.

[Latif Nasser]

You're not recommending cyanide to people.

[Dr. David Fagenbaum]

Yes, exactly. Yeah, Cyanide is not on her list.

[Latif Nasser]

Right.

[Dr. David Fagenbaum]

Actually, I will tell you, there is a drug repurposing platform that I will not name on this podcast where literally one of the top five predicted drugs for Castleman disease or predicted treatment for Castleman disease is car fume exhaust as a treatment. No, this was the top predictions that like, I guess inhaling car fumes, like, fumes.

[Latif Nasser]

This is just like an AI hallucination kind of thing.

[Dr. David Fagenbaum]

It was like, AI was like, AI made the connection to be like, you know what? You just. And I was like, oh, my gosh, that's the problem. I just haven't been inhaling enough perfumes. Like, that's. That's why my calcium is out of control.

[Latif Nasser]

Right.

[Dr. David Fagenbaum]

I just need to do inhale every morning after breakfast. So. So I say that. Not just to say that, oh my gosh, this one platform had this bad prediction, but it's to say that AI is going to make silly predictions that make no sense.

[Latif Nasser]

Not silly. Like harmful.

[Dr. David Fagenbaum]

Harmful. Yes. Harmful, yes.

[Latif Nasser]

Right.

[Dr. David Fagenbaum]

That's why humans have to be a part of this. And humans who can critically evaluate this and say, like, this is not good. So I think the most important thing is going to be, I think how we communicate around these scores when they are made publicly available that, that these scores are intended for our research team to find things for us to research more. These were not ever intended to be, you know, Scores to say this thing that's number one is what I should get because that's gonna save me. And so I think it's gonna be. Context is gonna be really important.

[Latif Nasser]

But like, what's the thing you say? Like, how do you expectation set in a really clear way to make it super distinct? Like, this is a machine that generates research ideas vers that tells you what drug to take.

[Dr. David Fagenbaum]

Now I see what you're saying. Your point is that you can say it all you want, but for that not that like, just may not stick, right?

[Latif Nasser]

It may not stick. And also people are desperate. Like a lot of these people. I mean, you, you know, you know better than I do.

[Dr. David Fagenbaum]

Yes, they will do anything. It's a great point. I think that the way to make it stick, I think it's, it's trying to explain that, that we, we don't use these predictions to decide how to treat someone. This is not, and maybe even to use the terminology, this is not a solution engine. This is an idea generator. And we at everycure do a lot of further work. And so we hope you, if you're going to use these scores, will also do further work. And so if you're a patient, that might mean working with a research lab to do the work to figure this out. What we recommend is talking to the disease organization that you're a part of. Whether it's the ALS association or you name it, it's talking to a lab to see if there's further work you can support. But none of those options are go take this medicine.

[Latif Nasser]

I'm trying to imagine. So that is, there's something beautiful and hopeful and democratic about that. I can also see though, there's a big danger here. So I talked to a friend of mine about what you're doing, and she was like, I've already seen this play out. She's like, I know exactly what's gonna happen here. I saw this play out with Ivermectin during COVID So all my patients were coming in asking me for ivermectin. Even though, like, I knew that that wasn't gonna help. She was like, last week someone asked me for ivermectin for cancer. It's an anti parasitic drug. It's not gonna help you for your cancer. So I said no. Like, no, I'm not gonna sit here and prescribe you a thing that there's no evidence for. But what then this is doing is it's like driving a wedge between the patient and the doctor. Because now once the doctor says no to the patient. Then the patient now doesn't trust the doctor. Now the patient is either gonna probably, you know, go doctor shopping until they find a doctor who will prescribe it to them or they'll wind up at the a black market or do medical tourism or some other, you know, non ideal situation. But anyway, like, like, her point was that the doctor patient relationship is already in a bad place. Like, it's already in a really bad place. And now if patients come in with these drug recommendations, like, who knows, maybe they'll be great, but also maybe they won't. And then she has to be the doorstop. Like, she has to be the one who crushes the hopes and dreams and has to hold the line. And, and that's like, I agree and.

[Dr. David Fagenbaum]

I, and I totally empathize and you can really, like, see the concerns. I think that where I go when I think about COVID is not so much ivermectin, but I go to dexamethasone. So dexamethasone saved millions of lives during the pandemic. It was the only drug, Latif, that was recommended against when the pandemic started. It was, whatever you do, don't give people a corticosteroids. Corticosteroids weaken your immune system. Don't take dexamethasone literally. There was no recommendation for what to take. There was only a recommendation for what not to take. Well, some amazing pioneering doctor in the UK still decided to do the trial of dexamethasone and it worked to reduce mortality by 35%. But the prevailing medical system believed that it would actually be harmful. So we didn't know what to do. We just don't do dexamethasone. Turns out dexamethasone actually reduces risk of death by 35%. So I'm so glad that someone asked the question, are we sure dexamethasone shouldn't be used? So I love that. I'm glad that dex saved millions of lives and I'm glad that there was sort of one doctor who was willing to go against everyone else. And so I think that the whole point of this is to find dexamethasone, not ivermectins. If there's a drug that someone thinks might work for a disease and it's snake oil and it's not working, we want to study it, we want to prove that it doesn't work. If there's a drug that looks kind of promising, but no one's studying it, we want to study it and prove that it does work. We just want to prove that they work or they don't work.

[Latif Nasser]

So do you feel like. Like what you're doing? Do you feel like, oh, this existing medical system needs to be respected, it needs to be shored up, and it's like you're trying to, like, fix a part of it that's wrong? Or do you feel like it's like. Like, no, no, no, no, no. The existing systems are failing us in these key ways. We can't be bogged down by them. Like, I'm building a whole new thing here.

[Dr. David Fagenbaum]

Yeah. I think where my mind is is that I think I'm still so appreciative for what doctors do for patients and that doctors bring just this laser focus on helping the person in front of them. I'm so grateful for that, and I'm so grateful for all the things that our biomedical system has figured out are true. Like, this drug works for this disease. Like, I'm so grateful for that. So I don't want to break down any of that. Like, I want everything about our doctors caring about patients and the relationship, and I want everything about all the known knowns, like, where we know this drug works for this disease. I think what I really, really want to bring forward is uncovering the unknowns so that way those doctors can use that unknown, can become a known, so it can be easy for them to use it. I don't want to create some crazy new system where patients are picking drugs off AI. Like, I want to use AI so we can find out what we can elevate to the level that a doctor feels comfortable. Like, wow, that steroid actually could be useful for this thing. Huh? Never would have thought about it. But you know what? They did a clinical trial, and it works. So, like, I'm going to do that. So. So in my opinion, it's not about breaking down the system. It's about enabling the system to do exactly what it's trying to do, but that we're caught up in these assumptions that I think we have around what we know and what we don't know. And I think we're really. We're certain we're very good at what we know. Like, I totally. I believe everything we know in the system is rock solid. I think we're just not as good at understanding what we know to be not the case versus what we just don't know at all. Like, the amount of our. And actually, there's a term for it that the computer scientists use, and that's the ignorome which is basically the things we don't know about medicine. Like the ignorome I think is a lot bigger than most of us in medicine want to appreciate. And I think if we can be a part of uncovering the ignoram and making it less ignoromous or whatever it is, then I think that that's where we can serve medicine, doctors, patients, and not to try to break it down. And it's really about, you know, lifting things up.

[Latif Nasser]

Yeah, I mean, like, I mean, look, you've already been doing miraculous work. At the same time. I can't help thinking about this other Radiolab story that we did. I don't know, it was like a year or two ago about this ICU doctor named Blair Bigham, who was kind of like you was like the annoying patient relative. And the story is kind of about him watching his dad basically contract cancer and die. And his takeaway from that experience was like, we don't need more hope, we don't need more like Hail Marys at the end. We need more dignity. Like we just, we glamorize doing everything we can, you know, because we, because we want to like keep the people we love alive. But actually the reality is like those last ditch efforts, like tend to make things worse for the patient, for the family, for the hospital. And now it's funny because I'm talking to you and I feel like you have the exact opposite 180 degrees different takeaway. Fight, fight, fight, Never say die. Like, try every drug in every pharmacy. So like, like, I just don't even know, like how do you square those two things?

[Dr. David Fagenbaum]

Things. So I actually think that during this discussion, I think you've actually sort of opened my eyes a little bit just because you sort of like highlighted to me, I just told you the three most special months of my life were the last three months of my mom's life when we weren't fighting for a treatment yet. I just tried to extend other people's lives with the drugs we already have in my own. And so I think everything's context dependent. And I mean if, if, if I, I think that what he said is, is conceptually correct, but I think that when you feel it, when you experience it, especially when you experience like the positive side, when, when you do make, creates a new sort of value that you put on if you, if you do get extra time. But of course this, at the end of the day this is like philosophical around like individual versus collective, societal. Like, you know, there are people that will say like, like I want to die at 70 years old because I don't want society to have to take on my burden. Like, even if I'm not sick, like, I just should die at 70 years old so society doesn't have to pay for my costs. And then there's other people who are like, we're only on this earth once. Like, like I'm going to like squeeze out all the time I can get. You know, I'm going to live as long as I can get. I don't think that I'm sort of on either camp. I think you can, you know, you know, be reasonable and decide. I mean, I should also share about a patient recently that, that I had helped to discover a repurposed drug for. And I mean it got him out of the icu. And I remember sitting with my team and jumping up and down and like when we got the news that, that he was responding to this medicine, it.

[Latif Nasser]

Was like, literally what was the sickness he had?

[Dr. David Fagenbaum]

He has cast him the same exact subtype that I have. Wow. It was just, I was so excited. I remember I cried tears of joy. I was so happy that we found this drug for Paul. And the next couple weeks went by and you know, he kept getting better and he got out of the hospital and I got in touch with him and, and he explained to me, David, this drug got me out of the hospital. It turned everything around to save my life. But I feel horrible on it. It makes me nauseous, I'm vomiting all the time. Like it is controlling my disease, but I don't like the way that I'm living. And he was a 70 year old gentleman and he decided to go off that medicine for the exact reason you mentioned, Latif, is I want to spend the time that I've got with my kids and with my wife. And I was like, Paul, but we already found something for you and it got you out. We've shown that we can do it. Let's try another one. And he said, no, David, I don't want to. And then the two of us just cried tears of sadness, cried tears of joy before that, cried tears of sadness. But it was, but it was okay. Like this was his decision. Like he knew that if he put me on the case, he knew that I was gonna be all in. And he knew that I'd been able to do it once before. But he told me he didn't want to. I was very sad, but I felt that it was absolutely the right thing and I 100% respected it. I understood that for him at this moment in his life, that was the right decision and he passed away a few days later.

[Latif Nasser]

So you're saying it just basically it needs to be personal. It needs to be case by case.

[Dr. David Fagenbaum]

Yeah, maybe that's the big takeaway is that it seems like everyone wants to tell us what everyone else's decision should be. So, like, it's best for society for you to do this, or it's selfish of you for you to do this, But I think that maybe that's the real fundamental thing this comes down to. It's got to be that patience decision.

[Latif Nasser]

This episode was reported by me, Latif Nasser, produced by Maria Paz Gutierrez, edited by Pat Walters and fact checked by Natalie Middleton. Special thanks to all of the folks at ted, including Chloe, Sasha Brooks and Helena Bowen, who introduced me to David and his work. I was right there in the wings when he did his talk on the TED stage. That talk should be on their website, the TED website, very soon. And in the meantime, for more on David's story, you can check out his book Chasing My Cure. Or for more on the work that him and his team are doing, you can go to their website, everycure.org Special thanks to Peyton and the rest of the staff at Every Curve here. If you have not had enough Radiolab, we referenced two prior episodes today and I think they're both totally worth a listen. The first was the one I mentioned about that ICU Dr. Blair Bigham, who basically writes a book about how we should make our peace with death and we should die with dignity. And then while his book is on the back best seller list, his dad gets pancreatic cancer and all of a sudden everything he wants to do completely contradicts everything he wrote in his book. That one is called Death Interrupted. Second Radiolab episode that we mentioned was kind of the backstory of the drug that saved David's life, Rapamycin. It is an entirely improbable backstory. It is shockingly dramatic. It's about one immigrant scientist who basically single handedly saves this potential drug from the trash can by smuggling it across a border. That episode is called the Dirty Drug and the Ice Cream Tub. That is all for us today. Thank you so much for listening. Until next time. I wish you good health.

[Radiolab Staff Announcer]

Hi, I'm Connor and I'm from Minneapolis, Minnesota. And here are the staff credits. Radiolab was created by Jad Abumrad and is edited by Soren Wheeler. Lulu Miller and Latif Nasser are our co hosts. Dylan Keefe is our director of sound design. Our staff includes Simon Adler, Jeremy Bloom, Becca Bressler, W. Harry Fortuna, David Gable, Maria Paz Gutierrez, Sindhu Ngan Sambandan, Matt Kilty, Annie McKeown, Alex Neeson, Sara Kari, Sarah Sandbach, Anissa Vitza, Arianne Wack, Pat Walters, Molly Webster, Jessica Young, with help from Rebecca Rand. Our fact checkers are Diane Kelly, Emily Krieger, Anna Pujol Mazini, and Natalie Middleton. Hi. This is Jenny from Brooks, Maine. Leadership support for Radiolab Science programming is provided by the Simons foundation and the John Templeton Foundation. Foundational support for Radiolab was provided by the Alfred P. Sloan Foundation.

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[Radiolab Staff Announcer]

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[Latif Nasser]

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[Dr. David Fagenbaum]

Wait.

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[Latif Nasser]

Take it or leave it.

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