The following is a conversation with Bob Langer, professor at MIT and one of the most cited researchers in history, specializing in biotechnology fields of drug delivery systems and tissue engineering. He has bridged theory and practice by being a key member and driving force in launching many successful biotech companies out of MIT.

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You can watch it on basically any device. Once again, sign up at masterclass.com/lex to get a discount and to support this podcast. And now, here's my conversation with Bob Langer. You have a bit of a love for magic. Do you see a connection between magic and science? - I do.

I think magic can surprise you and I think science can surprise you and there's something magical about science. I mean, making discoveries and things like that, yeah. - So, and then on the magic side, is there some kind of engineering scientific process to the tricks themselves? Do you see, 'cause there's a duality to it.

One is you're the, you're sort of the person inside that knows how the whole thing works, how the universe of the magic trick works. And then from the outside observer, which is kind of the role of the scientist, you, the people that observe the magic trick don't know, at least initially, anything that's going on.

Do you see that kind of duality? - Well, I think the duality that I see is fascination. You know, I think of it, you know, when I watch magic myself, I'm always fascinated by it. Sometimes it's a puzzle to think how it's done, but just the sheer fact that something that you never thought could happen does happen.

And I think about that in science too. You know, sometimes you, it's something that you might dream about and hoping to discover, maybe you do in some way or form. - What is the most amazing magic trick you've ever seen? - Well, there's one I like, which is called the invisible pack.

And the way it works is you have this pack and you hold it up. Well, first you say to somebody, this is invisible. And this deck, and you say, well, shuffle it. They shuffle it, but you know, they're sort of make-believe. And then you say, okay, I'd like you to pick a card, any card, and show it to me.

And you show it to me and I look at it. And let's say it's the three of hearts. I said, well, put it back in the deck, but what I'd like you to do is turn it upside down from every other card in the deck. So they do that imaginary.

And I said, do you want to shuffle it again? And they shuffle it. And I said, well, so there's still one card upside down from every other card in the deck. I said, what is that? And they said, well, three of hearts. So I said, well, it just so happens in my back pocket I have this deck, it's a real deck.

I show it to you and I just open it up and there's just one card upside down. And it's the three of hearts. - And you can do this trick. - I can, if I don't, I would have probably brought it. - All right, well, beautiful. Let's get into the science.

As of today, you have over 295,000 citations and H index of 269. You're one of the most cited people in history and the most cited engineer in history. And yet nothing great, I think, is ever achieved without failure. So the interesting part, what rejected papers, ideas, efforts in your life were most painful or had the biggest impact on your life?

- Well, it's interesting. I mean, I've had plenty of rejection too. But I suppose one way I think about this is that when I first started and this certainly had an impact both ways. You know, I first started, we made two big discoveries and they were kind of interrelated.

I mean, one was I was trying to isolate with my postdoctoral advisor, Judah Folkman, substances that could stop blood vessels from growing and nobody had done that before. And so that was part A, let's say. Part B is we had to develop a way to study that. And what was critical to study that was to have a way to slowly release those substances for more than a day, maybe months.

And that had never been done before either. So we published the first one, we sent to Nature, the journal, and they rejected it. And then we revised it, we sent it to Science and they accepted it. And the opposite happened. We sent it to Science and they rejected it and then we sent it to Nature and they accepted it.

But I have to tell you, when we got the rejections, it was really upsetting. I thought, you know, I'd done some really good work and Dr. Folkman thought we'd done some really good work. But it was very depressing to get rejected like that. - If you can linger on just the feeling or the thought process when you get the rejection, especially early on in your career, what, I mean, you don't know, now people know you as a brilliant scientist but at the time, I'm sure you're full of self-doubt.

And did you believe that maybe this idea is actually quite terrible, that it could have been done much better, or is there underlying confidence? What was the feelings? - Well, you feel depressed and I felt the same way when I got grants rejected, which I did a lot in the beginning.

I guess part of me, you know, you have multiple emotions. One is being sad and being upset and also being maybe a little bit angry 'cause you feel the reviewers didn't get it. But then as I thought about it more, I thought, well, maybe I just didn't explain it well enough.

And you know, you go through stages. And so you say, well, okay, I'll explain it better next time. And certainly you get reviews and when you get the reviews, you see what they either didn't like or didn't understand and then you try to incorporate that into your next versions.

- You've given advice to students to do something big, do something that really can change the world rather than something incremental. How did you yourself seek out such ideas? Is there a process? Is there sort of a rigorous process or is it more spontaneous? - It's more spontaneous. I mean, part of it's exposure to things, part of it's seeing other people like I mentioned Dr.

Folkman, he was my postdoctoral advisor. He was very good at that. You could sort of see that he had big ideas and I certainly met a lot of people who didn't. And I think you could spot an idea that might have potential when you see it, you know, because it could have very broad implications.

Whereas a lot of people might just keep doing derivative stuff. But it's not something that I've ever done systematically, I don't think. - So in the space of ideas, how many are just when you see them, it's just magic. It's something that you see that could be impactful if you dig deeper.

- Yeah, it's sort of hard to say because there's multiple levels of ideas. One type of thing is like a new, you know, creation, that you could engineer tissues for the first time or make dishes from scratch from the first time. But another thing is really just deeply understanding something and that's important too.

So, and that may lead to other things. So sometimes you could think of a new technology or I thought of a new technology, but other times things came from just the process of trying to discover things. So it's never, and you don't necessarily know, like people talk about aha moments, but I don't know if I've, I mean, I certainly feel like I've had some ideas that I really like, but it's taken me a long time to go from the thought process of starting it to all of a sudden knowing that it might work.

- So if you take drug delivery, for example, is the notion, is the initial notion kind of a very general one, that we should be able to do something like this? - Yeah. - And then you start to ask the questions of, well, how would you do it? And then digging and digging and digging.

- I think that's right. I think it depends. I mean, there are many different examples. The example I gave about delivering large molecules, which we used to study these blood vessel inhibitors. I mean, there we had to invent something that would do that. But other times it's different. Sometimes it's really understanding what goes on in terms of understanding the mechanisms.

And so it's not a single thing. And there are many different parts to it. But over the years we've invented different, or discovered different principles for aerosols, for delivering genetic therapy agents, all kinds of things. - So let's explore some of the key ideas you've touched on in your life.

Let's start with the basics. - Okay. - So first let me ask, how complicated is the biology and chemistry of the human body from the perspective of trying to affect some parts of it in a positive way? So that you know, for me, especially coming from the field of computer science and computer engineering and robotics, it seems that the human body is exceptionally complicated and how the heck you can figure out anything is amazing.

- Well, I agree with you. I think it's super complicated. I mean, we're still just scratching the surface in many ways. But I feel like we have made progress in different ways. And some of it's by really understanding things like we were just talking about. Other times, you know, you might, or somebody might, we or others might invent technologies that might be helpful on exploring that.

And I think over many years, we've understood things better and better, but we still have such a long ways to go. - Are there, I mean, if you just look, are there things that, are there knobs that are reliably controllable about the human body? If you consider, is there, is there, so if you start to think about controlling various aspects of, when we talk about drug delivery a little bit, but controlling various aspects chemically of the human body, is there a solid understanding across the populations of humans that are solid, reliable knobs that can be controlled?

- I think that's hard to do. But on the other hand, whenever we make a new drug or medical device, to a certain extent, we're doing that, you know, in a small way, what you just said. But I don't know that there are great knobs. I mean, and we're learning about those knobs all the time.

But if there's a biological pathway or something that you can affect or understand, I mean, then that might be such a knob. - So what is a pharmaceutical drug? How do you do, how do you discover a specific one? How do you test it? How do you understand it?

How do you ship it? - Yeah, well, I'll give an example which goes back to what I said before. So when I was doing my postdoctoral work with Judith Folkman, we wanted to come up with drugs that would stop blood vessels from growing or alternatively make them grow. And actually, people didn't even believe that those things could happen.

But-- - Can we pause on that for a second? - Sure. - What is a blood vessel? What does it mean for a blood vessel to grow and shrink? And why is that important? - Sure, so a blood vessel is, could be an artery or a vein or a capillary.

And it provides oxygen, it provides nutrients, gets rid of waste. So to different parts of your body, so the blood vessels end up being very, very important. And if you have cancer, blood vessels grow into the tumor and that's part of what enables the tumor to get bigger. And that's also part of what enables the tumor to metastasize, which means spread throughout the body.

And ultimately kill somebody. So that was part of what we were trying to do. We wanted to see if we could find substances that could stop that from happening. So first, I mean, there are many steps. First, we had to develop a bioassay to study blood vessel growth. Again, there wasn't one.

That's where we needed the polymer systems because the blood vessels grew slowly, took months. So after we had the polymer system and we had the bioassay, then I isolated many different molecules initially from cartilage and almost all of them didn't work. But we were fortunate, we found one. It wasn't purified, but we found one that did work.

And that paper, that was this paper I mentioned in Science in 1976. Those were really the isolation of some of the very first angiogenesis blood vessel inhibitors. - So there's a lot of words there. - Yeah. - First of all, polymer molecules, big, big molecules. So what are polymers?

What's bioassay? What is the process of trying to isolate this whole thing simplified to where you can control and experiment with it? - Polymers are like plastics or rubber. What were some of the other questions? - Sorry, so a polymer is some plastics and rubber, and that means something that has structure and that could be useful for what?

- Well, in this case, it would be something that could be useful for delivering a molecule for a long time, so it could slowly diffuse out of that at a controlled rate to where you wanted it to go. - So then you would find, the idea is that there would be a particular blood vessels that you can target, say they're connected somehow to a tumor, that you could target and over a long period of time to be able to place the polymer there and it'd be delivering a certain kind of chemical.

- That's correct, I think what you said is good. So that it would deliver the molecule or the chemical that would stop the blood vessels from growing over a long enough time so that it really could happen. So that was sort of what we call a bioassay, is the way that we would study that.

- So sorry, so what is a bioassay? Which part is the bioassay? - All of it, in other words, the bioassay is the way you study blood vessel growth. - The blood vessel growth, and you can control that somehow with, is there an understanding what kind of chemicals could control the growth of a blood vessel?

- Sure, well now there is, but then when I started, there wasn't, and that gets to your original question. So you go through various steps. We did the first steps, we showed that A, such molecules existed and then we developed techniques for studying them, and we even isolated fractions, you know, groups of substances that would do it.

But what would happen over the next, we did that in 1976, we published that. What would happen over the next 28 years is other people would follow in our footsteps. I mean, we tried to do some stuff too, but ultimately to make a new drug takes billions of dollars.

So what happened was there were different growth factors that people would isolate, sometimes using the techniques that we developed, and then they would figure out using some of those techniques ways to stop those, the growth factors and ways to stop the blood vessels from growing. But that, like I say, took 28 years, it took billions of dollars, and worked by many companies like Genentech.

But in 2004, 28 years after we started, the first one of those, Avastin, got approved by the FDA. And that's become one of the top biotech-selling drugs in history, and it's been approved for all kinds of cancers and actually for many eye diseases too, where you have abnormal blood vessel growth, macular.

- So in general, one of the key ways you can alleviate, so what's the hope in terms of tumors associated with cancerous tumors? What can you help by being able to control the growth of vessels? - So if you cut off the blood supply, you cut off the, it's kind of like a war almost, right?

If you have, if the nutrition is going to the tumor, and you can cut it off, I mean, you starve the tumor and it becomes very small, it may disappear, or it's gonna be much more amenable to other therapies, because it is tiny, like chemotherapy or immunotherapy is gonna have a much easier time against a small tumor than a big one.

- Is that an obvious idea? I mean, it seems like a very clever strategy in this war against cancer. - Well, in retrospect, it's an obvious idea, but when Dr. Folkman, my boss, first proposed it, it wasn't, a lot of people thought it was pretty crazy. - And so in what sense, if you could sort of linger on it, when you're thinking about these ideas at the time, were you feeling around in the dark?

So how much mystery is there about the whole thing? How much just blind experimentation, if you can put yourself in that mindset from years ago? - Yeah, well, there was, I mean, for me, actually, it wasn't just the idea, it was that I didn't know a lot of biology or biochemistry, so I certainly felt I was in the dark.

But I kept trying, and I kept trying to learn, and I kept plugging, but I mean, a lot of it was being in the dark. - So the human body is complicated, right? We'll establish this. Quantum mechanics and physics is a theory that works incredibly well, but we don't really necessarily understand the underlying nature of it.

So are drugs the same, in that you can, you're ultimately trying to show that the thing works to do something that you try to do, but you don't necessarily understand the fundamental mechanisms by which it's doing it? - It really varies. I think sometimes people do know them, because they've figured out pathways and ways to interfere with them.

Other times, it is shooting in the dark. It really has varied. And sometimes people make serendipitous discoveries, and they don't even realize what they did. - So what is the discovery process for a drug? You said a bunch of people have tried to work with this. Is it a kind of mix of serendipitous discovery and art, or is there a systematic science to trying different chemical reactions and how they affect whatever you're trying to do, like shrink blood vessels?

- Yeah, I don't think there's a single way, you know, a single way to go about something in terms of characterizing the entire drug discovery process. If I look at the blood vessel one, yeah, there, the first step was to have the kinds of theories that Dr. Folkman had.

The second step was to have the techniques where you could study blood vessel growth for the first time, and at least quantitate or semi-quantitate it. Third step was to find substances that would stop blood vessels from growing. Fourth step was to maybe purify those substances. There are many other steps too.

I mean, before you have an effective drug, you have to show that it's safe, you have to show that it's effective, and you start with animals, you ultimately go to patients, and there are multiple kinds of clinical trials you have to do. - If you step back, is it amazing to you that we descendants of great apes are able to create things that are, you know, that create drugs, chemicals that are able to improve some aspects of our bodies, or is it quite natural that we're able to discover these kinds of things?

- Well, at a high level, it is amazing. I mean, evolution's amazing. You know, the way I look at your question, the fact that we have evolved the way we've done, I mean, it's pretty remarkable. - So let's talk about drug delivery. What are the difficult problems in drug delivery?

What is drug delivery? You know, starting from your early seminal work in the field to today. - Well, drug delivery is getting a drug to go where you want it, at the level you want it, in a safe way. Some of the big challenges, I mean, there are a lot.

I mean, I'd say one is, could you target the right cell? Like we talked about cancers, or some way to deliver a drug just to a cancer cell and no other cell. Another challenge is to get drugs across different barriers. Like, could you ever give insulin orally? Could you, or give it passively transdermally?

Can you get drugs across the blood-brain barrier? I mean, there are lots of big challenges. Can you make smart drug delivery systems that might respond to physiologic signals in the body? - Oh, interesting. So smart, they have some kind of sense, a chemical sensor, or is there something more than a chemical sensor that's able to respond to something in the body?

- Could be either one. I mean, you know, I mean, one example might be if you were diabetic, if you had more, got more glucose, could you get more insulin? But I don't, but that's just an example. - Is there some way to control the actual mechanism of delivery in response to what the body's doing?

- Yes, there is. I mean, one of the things that we've done is encapsulate what are called beta cells. Those are insulin-producing cells, in a way that they're safe and protected. And then what'll happen is glucose will go in and, you know, cells will make insulin. And so that's an example.

- So from an AI robotics perspective, how close are these drug delivery systems to something like a robot? Or is it totally wrong to think about them as intelligent agents? And how much room is there to add that kind of intelligence into these delivery systems, perhaps in the future?

- Yeah, I think it depends on the particular delivery system. You know, of course, one of the things people are concerned about is cost. And if you add a lot of bells and whistles to something, it'll cost more. But I mean, we, for example, have made what I'll call intelligent microchips that can, you know, where you can send a signal and you'll release drug in response to that signal.

And I think systems like that microchip someday have the potential to do what you and I were just talking about, that there could be a signal like glucose and it could have some instruction to say when there's more glucose, deliver more insulin. - So do you think it's possible that there could be robotic type systems roaming our bodies sort of long term and be able to deliver certain kinds of drugs in the future?

You see that kind of future? - Someday, I don't think we're very close to it yet, but someday, you know, that's nanotechnology and that would mean even miniaturizing some of the things that I just discussed. And we're certainly not at that point yet, but someday I expect we will be.

- So some of it is just the shrinking of the technology. - That's a part of it, that's one of the things. - In general, what role do you see AI sort of, there's a lot of work now with using data to make intelligent, create systems that make intelligent decisions.

Do you see any of that data-driven kind of computing systems having a role in any part of this, into the delivery of drugs, the design of drugs, in any part of the chain? - I do. I think that AI can be useful in a number of parts of the chain.

I mean, one, I think if you get a large amount of information, you know, say you have some chemical data 'cause you've done high throughput screens, and let's, I'll just make this up, but let's say I have, I'm trying to come up with a drug to treat disease X, whatever that disease is, and I have a test for that, and hopefully a fast test, and let's say I test 10,000 chemical substances, and a couple work, most of them don't work, some maybe work a little, but if I had a, with the right kind of artificial intelligence, maybe you could look at the chemical structures and look at what works and see if there's certain commonalities, look at what doesn't work, and see what commonalities there are, and then maybe use that somehow to predict the next generation of things that you would test.

- As a tangent, what are your thoughts on our society's relationship with pharmaceutical drugs? Do we, and perhaps, I apologize as this is a philosophical, broader question, but do we over-rely on them? Do we improperly prescribe them? In what ways is the system working well? In what way can it improve?

- Well, I think, you know, pharmaceutical drugs are really important, I mean, the life expectancy and life quality of people over many, many years has increased tremendously, and I think that's a really good thing. I think one thing that would also be good is if we could extend that more and more to people in the developing world, which is something that our lab has been doing with the Gates Foundation, or trying to do.

So I think ways in which it could improve, I mean, if there were some way to reduce costs, you know, that's certainly an issue people are concerned about. If there was some way to help people in poor countries, that would also be a good thing. And then, of course, we still need to make better drugs for so many diseases.

I mean, cancer, diabetes, I mean, we, you know, there's heart disease and rare diseases. There are many, many situations where it'd be great if we could do better and help more people. - Can we talk about another exciting, another exciting space, which is tissue engineering? What is tissue engineering, or regenerative medicine?

- Yeah, so that tissue engineering or regenerative medicine have to do with building an organ or tissue from scratch. So, you know, someday maybe we can build a liver, you know, or make new cartilage. And also would enable you to, you know, someday create organs on a chip, which people, we and others are trying to do, which might lead to better drug testing and maybe less testing on animals or people.

- Organs on a chip, that sounds fascinating. So what are the various ways to generate tissue? And how do, so, you know, the one is, of course, from stem cells. Is there other methods? What are the different possible flavors here? - Yeah, well, I think, I mean, there's multiple components.

One is having generally some type of scaffold. That's what Jay Vacanti and I started many, many years ago. And then on that scaffold, you might put different cell types, which could be a cartilage cell, a bone cell, could be a stem cell that might differentiate into different things. Could be more than one cell.

- And a scaffold, sorry to interrupt, is kind of like a canvas that, it's a structure that you can, on which the cells can grow? - I think that's a good explanation of what you just did. I'll have to use that. The canvas, that's good. Yeah, so I think that that's fair.

You know, and the chip could be such a canvas. Could be fibers that are made of plastics and that you'd put in the body someday. - And when you say chip, do you mean electronic chip? Like-- - Not necessarily. It could be, though. But it doesn't have to be.

It could just be a structure that's not in vivo, so to speak, that's outside the body. - So is there-- - Canvas is not a bad word. - So is there a possibility to weave into this canvas a computational component? So if we talk about electronic chips, some ability to sense, control some aspect of this growth process for the tissue?

- I would say the answer to that is yes. I think right now people are working mostly on validating these kinds of chips for saying, well, it does work as effectively, or hopefully as just putting something in the body. But I think someday what you suggested, it certainly would be possible.

- So what kind of tissues can we engineer today? What kind of tissues? - Well, so skin's already been made and approved by the FDA. There are advanced clinical trials, like what are called phase three trials, that are at complete or near completion for making new blood vessels. One of my former students, Laura Nicholson, led a lot of that.

- So that's amazing. So human skin can be grown. That's already approved through the entire FDA process. So that means, one, that means you can grow that tissue and do various kinds of experiments in terms of drugs and so on. But what does that, does that mean that some kind of healing and treatment of different conditions for inhuman beings?

- Yes, I mean, they've been approved now for, I mean, different groups have made them, different companies and different professors. But they've been approved for burn victims and for patients with diabetic skin ulcers. - That's amazing. Okay, so skin, what else? - Well, at different stages, people are, like skin, blood vessels, there's clinical trials going now for helping patients hear better, for patients that might be paralyzed, for patients that have different eye problems.

I mean, and different groups have worked on just about everything, new liver, new kidneys. I mean, there've been all kinds of work done in this area. Some of it's early, but there's certainly a lot of activity. - What about neural tissue? - Yeah. - In the nervous system and even the brain?

- Well, there've been people that have worked on that too. We've done a little bit with that, but there are people who've done a lot on neural stem cells. And I know Evan Snyder, who's been one of our collaborators on some of our spinal cord works, done work like that.

And there've been other people as well. - Is there challenges for the, when it is part of the human body, is there challenges to getting the body to accept this new tissue that's being generated? How do you solve that kind of challenge? - There can be problems with accepting it.

I think maybe in particular, you might mean rejection by the body. So there are multiple ways that people are trying to deal with that. One way is, which is what we've done and with Dan Anderson, who was one of my former postdocs, and I mentioned this a little bit before, for a pancreas, is encapsulating the cells.

So immune cells or antibodies can't get in and attack them. So that's a way to protect them. Other strategies could be making the cells non-immunogenic, which might be done by different either techniques, which might mask them, or using some gene editing approaches. So there are different ways that people are trying to do that.

And of course, if you use the patient's own cells or cells from a close relative, that might be another way. - It increases the likelihood that it'll get accepted if you use the patient's own cells. - Yes. And then finally, there's immunosuppressive drugs, which will suppress the immune response.

That's right now what's done, say, for a liver transplant. - The fact that this whole thing works is fascinating, at least from my outside perspective. Will we one day be able to regenerate any organ or part of the human body, in your view? I mean, it's exciting to think about future possibilities of tissue engineering.

Do you see some tissues more difficult than others? What are the possibilities here? - Yeah, well, of course, I'm an optimist, and I also feel a timeframe, if we're talking about someday, someday could be hundreds of years. But I think that, yes, someday, I think we will be able to regenerate many things.

And there are different strategies that one might use. One might use some cells themselves. One might use some molecules that might help regenerate the cells. And so I think there are different possibilities. - What do you think that means for longevity? If we look, maybe not someday, but 10, 20 years out, the possibilities of tissue engineering, the possibilities of the research that you're doing, does it have a significant impact on the longevity, human life?

- I don't know that we'll see a radical increase in longevity, but I think that in certain areas, we'll see people live better lives and maybe somewhat longer lives. - What's the most beautiful scientific idea in bioengineering that you've come across in your years of research? I apologize for the romantic notion.

- No, that's an interesting question. I certainly think what's happening right now with CRISPR is a beautiful idea. That certainly wasn't my idea. I mean, but I think it's very interesting here. What people have capitalized on is that there's a mechanism by which bacteria are able to destroy viruses.

And that understanding that leads to machinery to sort of cut and paste genes and fix a cell. - So that kind of, do you see a promise for that kind of ability to copy and paste? I mean, like we said, the human body's complicated. Is that, that seems exceptionally difficult to do.

- I think it is exceptionally difficult to do, but that doesn't mean that it won't be done. There's a lot of companies and people trying to do it. And I think in some areas it will be done. Some of the ways that you might lower the bar are not, you know, are just taking, like not necessarily doing it directly, but you know, you could take a cell that might be useful, but you want to give it some cancer killing capabilities, something like what's called a CAR T cell.

And that might be a different way of somehow making a CAR T cell and maybe making it better. So there might be sort of easier things and rather than just fixing the whole body. So the way a lot of things have moved with medicine over time is stepwise. So I can see things that might be easier to do than say fix a brain.

That would be very hard to do, but maybe someday that'll happen too. - So in terms of stepwise, that's an interesting notion. Do you see that if you look at medicine or bioengineering, do you see that there is these big leaps that happen every decade or so or some distant period, or is it a lot of incremental work?

Not, I don't mean to reduce its impact by saying it's incremental, but is there sort of phase shifts in the science, big leaps? - I think there's both. You know, every so often a new technique or a new technology comes out. I mean, genetic engineering was an example. I mentioned CRISPR.

You know, I think every so often things happen that make a big difference, but still there's to try to really make progress, make a new drug, make a new device. There's a lot of things. I don't know if I'd call them incremental, but there's a lot, a lot of work that needs to be done.

- Absolutely. So you have over, numbers could be off, but it's a big amount. You have over 1,100 current or pending patents that have been licensed, sub-licensed to over 300 companies. What's your view? What in your view are the strengths and what are the drawbacks of the patenting process?

- Well, I think for the most part, they're strengths. I think that if you didn't have patents, especially in medicine, you'd never get the funding that it takes to make a new drug or a new device. I mean, which according to Tufts, to make a new drug costs over $2 billion right now.

And nobody would even come close to giving you that money, any of that money, if it weren't for the patent system because then anybody else could do it. That then leads to the negative though. Sometimes somebody does have a very successful drug and you certainly wanna try to make it available to everybody.

And so the patent system allows it to happen in the first place, but maybe it'll impede it after a little bit or certainly to some people or to some companies, once it is out there. - What's the, on the point of the cost, what would you say is the most expensive part of the $2 billion of making the drug?

- Human clinical trials. That is by far the most expensive. - In terms of money or pain or both? - Well, money, but pain goes, it's hard to know. I mean, but usually proving things that are, proving that something new is safe and effective in people is almost always the biggest expense.

- Could you linger on that for just a little longer and describe what it takes to prove, for people that don't know in general, what it takes to prove that something is effective on humans? - Well, you'd have to take a particular disease, but the process is you start out with, usually you start out with cells, then you'd go to animal models.

Usually you have to do a couple animal models. And of course the animal models aren't perfect for humans. And then you have to do three sets of clinical trials at a minimum, a phase one trial to show that it's safe in small number of patients, phase two trial to show that it's effective in a small number of patients, and a phase three trial to show that it's safe and effective in a large number of patients.

And that could end up being hundreds or thousands of patients, and they have to be really carefully controlled studies. And you'd have to manufacture the drug. You'd have to really watch those patients. You have to be very concerned that it is gonna be safe. And then you look and see, does it treat the disease better than whatever the gold standard was before that?

If there was, assuming there was one. - That's a really interesting line. Show that it's safe first and then that it's effective. - First do no harm. - First do no harm, that's right. So how, again, if you can linger on it a little bit, how does the patenting process work?

- Yeah, well, you do a certain amount of research. Though that's not necessarily has to be the case, but for us, usually it is. Usually we do a certain amount of research and make some findings. And we had a hypothesis, let's say we prove it, or we make some discovery, we invent some technique.

And then we write something up, what's called a disclosure. We give it to MIT's Technology Transfer Office. They then give it to some patent attorneys, and they use that, and plus talking to us, and work on writing a patent. And then you go back and forth with the USPTO, that's the United States Patent and Trademark Office, and they may not allow it the first, second, or third time, but they will tell you why they don't.

And you may adjust it, and maybe you'll eventually get it, and maybe you won't. - So you've been part of launching 40 companies, together worth, again, numbers could be outdated, but an estimated $23 billion. You've described your thoughts on a formula for startup success, so perhaps you can describe that formula, and in general, describe what does it take to build a successful startup?

- Well, I'd break that down into a couple categories, and I'm a scientist, and certainly, from the science standpoint, I'll go over that. But I actually think that, really, the most important thing is probably the business people that I work with. And when I look back at the companies that have done well, it's been because we've had great business people, and when they haven't done as well, we haven't had as good business people.

But from a science standpoint, I think about that we've made some kind of discovery that is almost what I'd call a platform, that you could use it for different things. And certainly, the drug delivery system example that I gave earlier is a good example of that. You could use it for drug A, B, C, D, E, and so forth.

And I'd like to think that we've taken it far enough so that we've written at least one really good paper in a top journal, hopefully a number, that we've reduced it to practice in animal models, that we've filed patents, maybe had issued patents that have what I'll call very good and broad claims.

That's sort of the key on a patent. And then in our case, a lot of times, when we've done it, a lot of times, it's somebody in the lab, like a post-doc or graduate student, that spent a big part of their life doing it, and that they want to work at that company 'cause they have this passion and they want to see something they did make a difference in people's lives.

- Maybe you can mention the business component. It's funny to hear great scientists say that there's value to business folks. - Oh yeah, well-- - It's not always said. So what value, what business instinct is valuable to make a startup successful, a company successful? - I think the business aspects are, you have to be a good judge of people so that you hire the right people.

You have to be strategic so you figure out, if you do, of that platform that could be used for all these different things. What one are you, and knowing that medical research is so expensive, what thing are you gonna do first, second, third, fourth, and fifth? I think you need to have a good, what I'll call FDA regulatory clinical trial strategy.

I think you have to be able to raise money, credibly. So there are a lot of things. You have to be good with people, good manager of people. - So the money and the people part I get, but the stuff before, in terms of deciding the A, B, C, D, if you have a platform, which drugs to first take a testing, you see, nevertheless, scientists as not being too, always too good at that process.

- Well, I think they're a part of the process, but I'd say there's probably, I'm gonna just make this up, but maybe six or seven criteria that you wanna use, and it's not just science. I mean, the kinds of things that I would think about is, is the market big or small?

Is the, are there good animal models for it so that you could test it and it wouldn't take 50 years? Are the clinical trials that could be set up ones that have clear endpoints where you can make a judgment? And another issue would be competition. Are there other ways that some companies out there are doing it?

Another issue would be reimbursement. You know, can it get reimbursed? So a lot of things that you have, manufacturing issues you'd wanna consider. So I think there are really a lot of things that go into whether you, what you do first, second, third, or fourth. - So you lead one of the largest academic labs in the world with over $10 million in annual grants and over 100 researchers, probably over a thousand since the lab's beginning.

Researchers can be individualistic and eccentric. How do I put it nicely? There you go, eccentric. So what insights into research leadership can you give having to run such a successful lab with so much diverse talent? - Well, I don't know that I'm any expert. I think that what you do to me, I mean, I just want, I mean, this is gonna sound very simplistic, but I just want people in the lab to be happy, to be doing things that I hope will make the world a better place, to be working on science that can make the world a better place.

And I guess my feeling is if we're able to do that, you know, it kind of runs itself. - So how do you make a researcher happy in general? - I think when people feel, I mean, this is gonna sound like, again, simplistic or maybe like motherhood and apple pie, but I think if people feel they're working on something really important that can affect many other people's lives and they're making some progress, they'll feel good about it.

They'll feel good about themselves and they'll be happy. - But through brainstorming and so on, what's your role and how difficult it is as a group in this collaboration to arrive at these big questions? That might have impact. - Well, the big questions come from many different ways. Sometimes it's trying to, things that I might think of or somebody in the lab might think of, which could be a new technique or to understand something better.

But gee, we've had people like Bill Gates and the Gates Foundation come to us and Juvenile Diabetes Foundation come to us and say, gee, could you help us on these things? And I mean, that's good too. It doesn't happen just one way. And I mean, you've kind of mentioned it, happiness, but is there something more, how do you inspire a researcher to do the best work of their life?

So you mentioned passion and passion is a kind of fire. Do you see yourself having a role to keep that fire going, to build it up, to inspire the researchers through the pretty difficult process of going from idea to big question to big answer? - I think so. I think I try to do that by talking to people, going over their ideas and their progress.

I try to do it as an individual. Certainly when I talk about my own career, I had my setbacks at different times and people know that, that know me. And you just try to keep pushing and so forth. But yeah, I think I try to do that as the one who leads the lab.

- So you have this exceptionally successful lab and one of the great institutions in the world, MIT. And yet sort of at least in my neck of the woods in computer science and artificial intelligence, a lot of the research is kind of, a lot of the great researchers, not everyone, but some are kind of going to industry.

A lot of the research is moving to industry. What do you think about the future of science in general? Is there drawbacks? Is there strength to the academic environment that you hope will persist? How does it need to change? What needs to stay the same? What are your thoughts on this whole landscape of science and its future?

- Well, first I think going into industry is good, but I think being in academia is good. I have lots of students who've done both and they've had great careers doing both. I think from an academic standpoint, I mean the biggest concern probably that people feel today at a place like MIT or other research heavy institutions is gonna be funding and particular funding that's not super directed, so that you can do basic research.

I think that's probably the number one thing, but it would be great if we as a society could come up with better ways to teach, so that people all over could learn better. So I think there are a number of things that would be good to be able to do better.

- So again, you're very successful in terms of funding, but do you still feel the pressure of that, of having to seek funding? Does it affect the science or can you simply focus on doing the best work of your life and the funding comes along with that? - I'd say the last 10 or 15 years, we've done pretty well funding, but I always worry about it.

You know, it's like you're still operating on more soft money than hard, and so I always worry about it, but we've been fortunate that places have come to us, like the Gates Foundation and others, Juvenile Diabetes Foundation, some companies, and they're willing to give us funding, and we've gotten government money as well.

We have a number of NIH grants, and I've always had that, and that's important to me too. So I worry about it, but I just view that as a part of the process. - Now, if you put yourself in the shoes of a philanthropist, like say I gave you $100 billion right now, but you couldn't spend it on your own research.

So how hard is it to decide which labs to invest in, which ideas, which problems, which solutions? You know, 'cause funding is so much, such an important part of progression of science in today's society. So if you put yourself in the shoes of a philanthropist, how hard is that problem?

How would you go about solving it? - Sure, well, I think what I do, the first thing is different philanthropists have different visions, and I think the first thing is to form a concrete vision of what you want. Some people, I mean, I'll just give you two examples of people that I know.

David Koch was very interested in cancer research, and part of that was that he had cancer, and prostate cancer, and a number of people do that along those lines. They've had somebody, they've either had cancer themselves or somebody they loved had cancer, and they wanna put money into cancer research.

Bill Gates, on the other hand, I think when he had got his fortune, I mean, he thought about it and felt, well, how could he have the greatest impact? And he thought about helping people in the developing world, and medicines, and different things like that, like vaccines that might be really helpful for people in the developing world.

And so I think first you start out with that vision. Once you start out with that vision, whatever vision it is, then I think you try to ask the question, who in the world does the best work, if that was your goal. I mean, but you really, I think, have to have a defined vision.

- Vision first. - Yeah, and I think that's what people do. I mean, I have never seen anybody do it otherwise. I mean, and that, by the way, may not be the best thing overall. I mean, I think it's good that all those things happen, but what you really wanna do, and I'll make a contrast in a second, in addition to funding important areas like what both of those people did, is to help young people.

And they may be at odds with each other because a far more, a lab like ours, which is, you know, I'm older, is, you know, might be very good at addressing some of those kinds of problems, but, you know, I'm not young. I train a lot of people who are young, but it's not the same as helping somebody who's an assistant professor someplace.

So I think what's, I think, been good about our thing, our society or things overall are that there are people who come at it from different ways. And the combination, the confluence of the government funding, the certain foundations that fund things and other foundations that, you know, wanna see disease treated, well, then they can go seek out people or they can put a request for proposals and see who does the best.

You know, I'd say both David Koch and Bill Gates did exactly that. They sought out people, most of them, you know, or their foundations that they were involved in sought out people like myself, but they also had requests for proposals. - You mentioned young people, and that reminds me of something you said in an interview of "Written Somewhere" that said some of your initial struggles in terms of finding a faculty position or so on that you didn't quite, for people, fit into a particular bucket, a particular-- - Right.

- Can you speak to that? How, do you see limitations to the academic system that it does have such buckets? Is there, how can we allow for people who are brilliant but outside the disciplines of the previous decade? - Yeah, well, I think that's a great question. I think that, I think the department has have to have a vision, you know, and some of them do.

Every so often, you know, there are institutes or labs that do that. I mean, at MIT, I think that's done sometimes. I know mechanical engineering department just had a search and they hired Gio Traverso, who was one of my, he was a fellow with me, but he's actually a molecular biologist and a gastroenterologist, and, you know, he's one of the best in the world, but he's also done some great mechanical engineering and designing some new pills and things like that, and they picked him, and boy, I give them a lot of credit.

I mean, that's vision to pick somebody, and I think, you know, they'll be the richer for it. I think the media lab has certainly hired, you know, people like Ed Boyden and others who have done, you know, very different things, and so I think that, you know, that's part of the vision of the leadership who do things like that.

- Do you think one day, you've mentioned David Koch and cancer, do you think one day we'll cure cancer? - Yeah, I mean, of course, one day, I don't know how long that day will come. - Soon. - But, yeah, soon, no, but I think-- - So you think it is a grand challenge?

- It is a grand challenge, it's not just solvable within a few years. - I don't think very many things are solvable in a few years. There's some good ideas that people are working on, but I mean, all cancers, that's pretty tough. - If we do get the cure, what will the cure look like?

Do you think which mechanisms, which disciplines will help us arrive at that cure, from all the amazing work you've done that has touched on cancer? - No, I think it'll be a combination of biology and engineering. I think it'll be biology to understand the right genetic mechanisms to solve this problem, and maybe the right immunological mechanisms, and engineering in the sense of producing the molecules, developing the right delivery systems, targeting it, or whatever else needs to be done.

- Well, that's a beautiful vision for engineering. So on a lighter topic, I've read that you love chocolate, and mentioned two places, Ben and Bill's Chocolate Emporium, and the chocolate cookies, the Soho Globs from Rosie's Bakery in Chestnut Hill. I went to their website, and I was trying to finish a paper last night, and there's a deadline today, and yet I was wasting way too much time at 3 a.m.

instead of writing the paper, staring at the Rosie Bakers cookies, which just look incredible. The Soho Globs just look incredible. But for me, oatmeal white raisin cookies won my heart, just from the pictures. Do you think one day we'll be able to engineer the perfect cookie with the help of chemistry, and maybe a bit of data-driven artificial intelligence, or is cookies something that's more art than engineering?

- I think they're some of both. I think engineering will probably help someday. - What about chocolate? - Same thing, same thing. You have to go to see some of David Edwards' stuff. You know, he was one of my postdocs, and he's a professor at Harvard, but he also started Cafe Art Sciences, and it's just a really cool restaurant around here.

But he also has companies that do ways of looking at fragrances and trying to use engineering in new ways. And so I think, I mean, that's just an example, but I expect someday that AI and engineering will play a role in almost everything. - Including creating the perfect cookie.

- Yes. - Well, I dream of that day as well. So when you look back at your life, having accomplished an incredible amount of positive impact on the world through science and engineering, what are you most proud of? - My students. You know, I mean, I really feel when I look at that, I mean, we've probably had close to 1,000 students go through the lab, and I mean, they've done incredibly well.

I think 18 are in the National Academy of Engineering, 16 in the National Academy of Medicine. I mean, they've been CEOs of companies, presidents of universities. I mean, and they've done, I think, eight are faculty at MIT, maybe about 12 at Harvard. I mean, so it really makes you feel good to think that the people, you know, they're not my children, but they're close to my children in a way, and it makes you feel really good to see them have such great lives and them do so much good and be happy.

- Well, I think that's a perfect way to end it, Bob. Thank you so much for talking today. - My pleasure. - Good questions, thank you. Thanks for listening to this conversation with Bob Langer, and thank you to our sponsors, Cash App and Masterclass. Please consider supporting the podcast by downloading Cash App and using code LEXPODCAST and signing up at masterclass.com/lex.

Click on the links, buy all the stuff. It's the best way to support this podcast and the journey I'm on in my research and startup. If you enjoy this thing, subscribe on YouTube, review it with 5,000 Apple Podcast, support it on Patreon, or connect with me on Twitter at Lex Friedman, spelled without the E, just F-R-I-D-M-A-N.

And now let me leave you with some words from Bill Bryson in his book, "A Short History of Nearly Everything." If this book has a lesson, it is that we're awfully lucky to be here. And by we, I mean every living thing. To attain any kind of life in this universe of ours appears to be quite an achievement.

As humans, we're doubly lucky, of course. We enjoy not only the privilege of existence, but also the singular ability to appreciate it, and even in a multitude of ways to make it better. It is talent we have only barely begun to grasp. Thank you for listening, and hope to see you next time.

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