Transcript
00:00:00 The following is a conversation with Bob Langer, professor at
00:00:03 MIT, and one of the most cited researchers in history,
00:00:07 specializing in biotechnology fields of drug delivery systems
00:00:11 and tissue engineering. He has bridged theory and practice by
00:00:15 being a key member and driving force in launching many
00:00:19 successful biotech companies out of MIT. This conversation was
00:00:23 recorded before the outbreak of the coronavirus pandemic. His
00:00:27 research and companies are at the forefront of developing
00:00:30 treatment for COVID 19, including a promising vaccine
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00:03:01 podcast. And now here’s my conversation with Bob Langer.
00:03:07 You have a bit of a love for magic. Do you see a connection
00:03:10 between magic and science?
00:03:12 I do. I think magic can surprise you. And, uh, you know, and I
00:03:17 think science can surprise you. And there’s something magical
00:03:20 about, about science. I mean, making discoveries and things
00:03:23 like that. Yeah. So on the, and then on the magic side, is
00:03:26 there some kind of engineering scientific process to the tricks
00:03:30 themselves? Do you see, cause there’s a duality to it. One is
00:03:34 you’re the, um, you’re, you’re sort of the person inside that
00:03:39 knows how the whole thing works, how the universe of the magic
00:03:42 trick works. And then from the outside observer, which is kind
00:03:45 of the role of the scientists, you, the people that observe
00:03:49 the magic trick don’t know at least initially anything that’s
00:03:52 going on. Do you see that kind of duality?
00:03:55 Well, I think the duality that I see is fascination. You know,
00:03:58 I think of it, you know, when I watch magic myself, I’m always
00:04:03 fascinated by it. Sometimes it’s a puzzle to think how it’s done,
00:04:06 but just the sheer fact that something that you never thought
00:04:09 could happen does happen. And I think about that in science too,
00:04:13 you know, sometimes you, it’s something that, that you might
00:04:17 dream about and hoping to discover, maybe you do in some
00:04:21 way or form.
00:04:22 What is the most amazing magic trick you’ve ever seen?
00:04:26 Well, there’s one I like, which is called the invisible pack.
00:04:30 And the way it works is you have this pack and you hold it up.
00:04:35 Well, first you say to somebody, this is invisible and this deck
00:04:40 and you say, well, shuffle it. They shuffle it, but you know,
00:04:43 they’re sort of make believe. And then you say, okay, I’d like
00:04:46 you to pick a card, any card and show it to me. And you show it
00:04:50 to me and I look at it. And let’s say it’s the three of
00:04:55 hearts. I said, we’ll put it back in the deck. But what I’d
00:04:57 like you to do is turn it up upside down from every other
00:05:00 card in the deck. So they do that imaginary. And I say,
00:05:04 do you want to shuffle it again? And they shuffle it. And I said,
00:05:07 well, so there’s still one card upside down from every other
00:05:10 card in the deck. I said, what is that? And they said, well,
00:05:12 three hearts. So what just so happens in my back pocket, I
00:05:15 have this deck, it’s, you know, it’s a real deck. I show it to
00:05:18 you and I just open it up. And there’s just one card upside
00:05:22 down. And it’s the three of hearts.
00:05:27 And, and you can do this trick.
00:05:30 I can, if I don’t, I would have probably brought it.
00:05:33 All right. Well, beautiful. Let’s get into the, into the
00:05:37 science. As of today, you have over 295,000 citations. An H
00:05:43 index of 269. You’re one of the most cited people in history and
00:05:47 the most cited engineer in history. And yet nothing great,
00:05:53 I think is ever achieved without failure. So the interesting
00:05:57 part, what rejected papers, ideas, efforts in your life or
00:06:01 most painful, or had the biggest impact on your life?
00:06:04 Well, it’s interesting. I mean, I’ve had plenty of rejection too,
00:06:07 you know, but I suppose one way I think about this is that when
00:06:11 I first started, and this certainly had an impact both
00:06:14 ways, you know, I first started, we made two big discoveries and
00:06:19 they were kind of interrelated. I mean, one was, I was trying to
00:06:22 isolate with my postdoctoral advisor, Judah Folkman,
00:06:25 substances that could stop blood vessels from growing and nobody
00:06:29 had done that before. And so that was part A, let’s say part B
00:06:35 is we had to develop a way to study that. And what was
00:06:38 critical to study that was to have a way to slowly release
00:06:42 those substances for, you know, more than a day, you know, maybe
00:06:47 months. And that had never been done before either. So we
00:06:50 published the first one we sent to Nature, the journal, and they
00:06:55 rejected it. And then we sent it, we revised it, we sent it to
00:06:59 Science and they accepted it. And the other, the opposite
00:07:04 happened, we sent it to Science and they rejected it. And then
00:07:06 we sent it to Nature and they accepted it. But I have to tell
00:07:10 you, when we got the rejections, it was really upsetting. I
00:07:12 thought, you know, I’d done some really good work. And Dr.
00:07:15 Folkman thought we’d done some really good work. And, and, but
00:07:19 it was very depressing to, you know, get rejected like that.
00:07:24 If you can linger on just the feeling or the thought process
00:07:27 when you get the rejection, especially early on in your
00:07:30 career, what, I mean, you don’t know, now people know you as a
00:07:39 brilliant scientist, but at the time, I’m sure you’re full of
00:07:42 self doubt. And did you believe that maybe this idea is actually
00:07:48 quite terrible, that it could have been done much better? Or
00:07:51 is there underlying confidence? What was the feelings?
00:07:54 Well, you feel depressed and I felt the same way when I got
00:07:58 grants rejected, which I did a lot in the beginning. I guess
00:08:02 part of me, you know, you have multiple emotions. One is being
00:08:07 sad and being upset and also being maybe a little bit angry
00:08:11 because you didn’t feel the reviewers didn’t get it. But
00:08:14 then as I thought about it more, I thought, well, maybe I just
00:08:17 didn’t explain it well enough. And you know, that, you know,
00:08:20 that you go through stages. And so you say, well, okay, I’ll
00:08:24 explain it better next time. And certainly you get reviews and
00:08:26 when you get the reviews, you see what they either didn’t like
00:08:29 or didn’t understand. And then you try to incorporate that into
00:08:32 your next versions.
00:08:34 You’ve given advice to students to do something big, do
00:08:37 something that really can change the world rather than something
00:08:40 incremental. How did you yourself seek out such ideas? Is
00:08:45 there a process? Is there a sort of a rigorous process? Or is it
00:08:49 more spontaneous?
00:08:51 It’s more spontaneous. I mean, part of its exposure to things,
00:08:55 part of its seeing other people, like I mentioned, Dr. Folkman,
00:08:58 he was my postdoctoral advisor, he was very good at that, you
00:09:02 could sort of see that he had big ideas. And I certainly met a
00:09:05 lot of people who didn’t. And I think you could spot an idea
00:09:08 that might have potential when you see it, you know, because it
00:09:11 could have very broad implications, whereas a lot of
00:09:14 people might just keep doing derivative stuff. And so I
00:09:19 don’t know. But it’s not something that I’ve ever done.
00:09:24 Systematically, I don’t think.
00:09:26 So in the space of ideas, how many are just when you see them?
00:09:31 It’s just magic. It’s something that you see that could be
00:09:34 impactful if you dig deeper.
00:09:38 Yeah, it’s sort of hard to say because there’s multiple levels
00:09:42 of ideas. One type of thing is like a new, you know, creation
00:09:49 that you could engineer tissues for the first time or make
00:09:51 dishes from scratch on the first time. But another thing is
00:09:54 really just deeply understanding something. And that’s important
00:09:58 too. So and that may lead to other things. So sometimes you
00:10:04 could think of a new technology, or I thought of a new
00:10:07 technology. But other times, things came from just the
00:10:11 process of trying to discover things. So it’s never and you
00:10:15 don’t necessarily know, like people talk about aha moments,
00:10:19 but I don’t know if I’ve, I mean, I certainly feel like I’ve
00:10:23 had some ideas that I really like. But it’s taken me a long
00:10:27 time to go from the thought process of starting it to all of
00:10:32 a sudden, knowing that it might work.
00:10:35 So if you take drug delivery, for example, is the notion is
00:10:39 the initial notion, kind of a very general one, that we should
00:10:43 be able to do something like this. And then you start to ask
00:10:48 the questions of Well, how would you do it and then and then
00:10:51 digging and digging and digging?
00:10:52 I think that’s right. I think it depends. I mean, there are
00:10:54 many different examples. The example I gave about delivering
00:10:58 large molecules, which we used to study these blood vessel
00:11:01 inhibitors. I mean, there, we had to invent something that
00:11:05 would do that. But other times, it’s, it’s, it’s different.
00:11:10 Sometimes it’s really understanding what goes on in
00:11:13 terms of understanding the mechanisms. And so it’s, it’s,
00:11:16 it’s not a single thing. And there are many different parts
00:11:19 to it, you know, over the years, we’ve invented different or
00:11:23 discovered different principles for aerosols for delivering,
00:11:27 you know, genetic therapy agents, you know, all kinds of
00:11:30 things.
00:11:31 So let’s explore some of the key ideas you’ve touched on in your
00:11:34 life. Let’s start with the basics. Okay. So first, let me
00:11:39 ask, how complicated is the biology and chemistry of the
00:11:42 human body from the perspective of trying to affect some parts
00:11:46 of it in a positive way? So that you know, for me, especially
00:11:50 coming from the field of computer science and computer
00:11:54 engineering and robotics, it seems that the human body is
00:11:57 exceptionally complicated, and how the heck you can figure out
00:12:00 anything is amazing.
00:12:02 I agree with you. I think it’s super complicated. I mean,
00:12:05 we’re still just scratching the surface in many ways. But I feel
00:12:08 like we have made progress in different ways. And some of its
00:12:12 by really understanding things like we were just talking about
00:12:16 other times, you know, you might, or somebody might we or
00:12:19 others might invent technologies that might be helpful on
00:12:23 exploring that. And I think over many years, we’ve understood
00:12:26 things better and better, but we still have such a long ways to
00:12:29 go.
00:12:29 Are there? I mean, if you just look at the other things that
00:12:35 are there knobs that are reliably controllable about the
00:12:39 human body, if you consider is there is it? So if you start to
00:12:46 think about controlling various aspects of when we talk about
00:12:49 drug delivery a little bit, but controlling various aspects
00:12:54 chemically of the human body, is there a solid understanding
00:12:57 across the populations of humans that are solid, reliable knobs
00:13:02 that can be controlled?
00:13:03 I think that’s hard to do. But on the other hand, whenever we
00:13:06 make a new drug or medical device, to a certain extent,
00:13:09 we’re doing that, you know, in a small way, what you just said,
00:13:12 but I don’t know that there are great knobs. I mean, and we’re
00:13:16 learning about those knobs all the time. But if there’s a
00:13:20 biological pathway or something that you can affect, or
00:13:23 understand, I mean, then that might be such a knob.
00:13:27 So what is a pharmaceutical drug? How do you do? How do you
00:13:31 discover a specific one? How do you test it? How do you
00:13:34 understand it? How do you ship it?
00:13:36 Yeah, well, I’ll give an example, which goes back to
00:13:40 what I said before. So when I was doing my postdoctoral work
00:13:43 with Judah Folkman, we wanted to come up with drugs that would
00:13:46 stop blood vessels from growing or alternatively make them grow.
00:13:50 And actually, people didn’t even believe that, that those things
00:13:54 could happen. But
00:13:56 could we pause on that for a second? Sure. What is a blood
00:13:58 vessel? What does it mean for a blood vessel to grow and shrink?
00:14:01 And why is that important?
00:14:03 Sure. So a blood vessel is could be an artery or vein or a
00:14:08 capillary. And it, you know, provides oxygen, it provides
00:14:14 nutrients gets rid of waste. So, you know, to different parts of
00:14:19 your body if you so so the blood vessels end up being very, very
00:14:23 important. And, you know, if you have cancer, blood vessels grow
00:14:29 into the tumor. And that’s part of what enables the tumor to get
00:14:32 bigger. And that’s also part of what enables the tumor to
00:14:36 metastasize and which means spread throughout the body and
00:14:39 ultimately kill somebody. So that was part of what we were
00:14:42 trying to do. We tried what we wanted to see if we could find
00:14:45 substances that could stop that from happening. So first, I
00:14:49 mean, there are many steps. First, we had to develop a bio
00:14:51 assay to study blood vessel growth. Again, there wasn’t
00:14:54 one. That’s where we needed the polymer systems because the
00:14:57 blood vessels grew slowly took months. That so after we had the
00:15:03 polymer system and we had the bio assay, then I isolated many
00:15:07 different molecules initially from cartilage. And almost all
00:15:12 of them didn’t work. But we were fortunate we found one it wasn’t
00:15:17 purified, but we found one that did work. And that paper that
00:15:21 was this paper I mentioned science in 1976. Those were
00:15:24 really the isolation of some of the very first angiogenesis and
00:15:27 blood vessel inhibitors.
00:15:29 So there’s a lot of words there. Yeah, let’s go. First of all,
00:15:34 polymer molecules, big, big molecules. So the what are
00:15:38 polymers? What’s bio assay? What is the process of trying to
00:15:45 isolate this whole thing simplified to where you can
00:15:46 control and experiment with it?
00:15:48 Polymers are like plastics or like plastics or rubber. What
00:15:54 were some of the other questions?
00:15:55 Sorry, so a polymer, some plastics and rubber, and that
00:15:59 means something that has structure and that could be
00:16:01 useful for what?
00:16:03 Well, in this case, it would be something that could be useful
00:16:05 for delivering a molecule for a long time. So it could slowly
00:16:10 diffuse out of that at a controlled rate to where you
00:16:13 wanted it to go.
00:16:15 So then you would find the idea is that there would be a
00:16:17 particular blood vessels that you can target, say they’re
00:16:22 connected somehow to a tumor that you could target and over
00:16:27 a long period of time to be able to place the polymer there
00:16:31 and it’d be delivering a certain kind of chemical.
00:16:34 That’s correct. I think what you said is good. So so that it
00:16:37 would deliver the molecule or the chemical that would stop
00:16:41 the blood vessels from going over a long enough time so that
00:16:44 it really could happen. So that was sort of the what we call
00:16:47 the bio assay is the way that we would study that.
00:16:50 So, sorry, so what is a bio assay? Which part is the bio
00:16:53 assay?
00:16:54 All of it. In other words, the bio assay is the way you study
00:17:00 blood vessel growth.
00:17:01 The blood vessel growth and you can control that somehow with
00:17:05 is there an understanding what kind of chemicals could control
00:17:08 the growth of a blood vessel?
00:17:09 Sure. Well, now there is, but then when I started, there
00:17:11 wasn’t and that that gets to your original question. So you
00:17:14 go through various steps. We did the first steps. We showed
00:17:17 that a such molecules existed and then we developed
00:17:20 techniques for studying them. And we even isolated fractions,
00:17:24 you know, groups of substances that would do it. But what
00:17:28 would happen over the next, we did that in 1976, we published
00:17:33 that what would happen over the next 28 years is other people
00:17:37 would follow in our footsteps. I mean, we tried to do some
00:17:39 stuff too, but ultimately to make a new drug takes billions
00:17:43 of dollars. So what happened was there were different growth
00:17:47 factors that people would isolate, sometimes using the
00:17:50 techniques that we developed. And then they would figure out
00:17:55 using some of those techniques, ways to stop those growth
00:17:58 factors and ways to stop the blood vessels from growing. That
00:18:02 like I say, it took 28 years, it took billions of dollars and
00:18:05 work by many companies like Genetec. But in 2004, 28 years
00:18:11 after we started, the first one of those Avastin got approved
00:18:15 by the FDA. And that’s become, you know, one of the top
00:18:20 biotech selling drugs in history. And it’s been approved
00:18:23 for all kinds of cancers and actually for many eye diseases
00:18:27 too, where you have abnormal blood vessel growth, macular.
00:18:30 So in general, one of the key ways you can alleviate, what’s
00:18:38 the hope in terms of tumors associated with cancerous
00:18:41 tumors? What can you help by being able to control the
00:18:46 growth of vessels?
00:18:47 So if you cut off the blood supply, you cut off the, it’s
00:18:52 kind of like a war almost, right? If the nutrition is going
00:18:56 to the tumor and you can cut it off, I mean, you starve the
00:19:01 tumor and it becomes very small, it may disappear or it’s going
00:19:05 to be much more amenable to other therapies because it is
00:19:08 tiny, you know, like, you know, chemotherapy or immunotherapy
00:19:12 is going to be, have a much easier time against a small
00:19:15 tumor than a big one.
00:19:16 Is that an obvious idea? I mean, it seems like a very clever
00:19:20 strategy in this war against cancer.
00:19:23 Well, you know, in retrospect, it’s an obvious idea, but when
00:19:27 Dr. Folkman, my boss first proposed it, it wasn’t, a lot of
00:19:31 people didn’t thought he was pretty crazy.
00:19:33 And so in what sense, if you can sort of linger on it, when
00:19:39 you’re thinking about these ideas at the time, were you
00:19:42 feeling you’re out in the dark?
00:19:43 So how much mystery is there about the whole thing?
00:19:46 How much just blind experimentation, if you can put
00:19:50 yourself in that mindset from years ago?
00:19:52 Yeah.
00:19:52 Well, there was, I mean, for me, actually, it wasn’t just
00:19:56 the idea.
00:19:56 It was that I didn’t know a lot of biology or biochemistry.
00:19:59 So I certainly felt I was in the dark, but I kept trying and
00:20:03 I kept trying to learn and I kept plugging.
00:20:06 But I mean, a lot of it was being in the dark.
00:20:08 So the human body is complicated, right?
00:20:11 We’ll establish this.
00:20:12 Quantum mechanics in physics is a theory that works incredibly
00:20:16 well, but we don’t really necessarily understand the underlying
00:20:19 nature of it.
00:20:20 So are drugs the same in that you’re ultimately trying to
00:20:25 show that the thing works to do something that you try to do,
00:20:29 but you don’t necessarily understand the fundamental
00:20:33 mechanisms by which it’s doing it?
00:20:35 It really varies.
00:20:36 I think sometimes people do know them because they’ve figured
00:20:40 out pathways and ways to interfere with them.
00:20:42 Other times it is shooting in the dark.
00:20:45 It really has varied.
00:20:46 Okay.
00:20:47 And sometimes people make serendipitous discoveries and
00:20:49 they don’t even realize what they did.
00:20:51 So what is the discovery process for a drug?
00:20:55 You said a bunch of people trying to work with this.
00:20:59 Is it a kind of a mix of serendipitous discovery and art,
00:21:08 or is there a systematic science to trying different chemical
00:21:12 reactions and how they affect whatever you’re trying to do,
00:21:16 like shrink blood vessels?
00:21:18 Yeah, I don’t think there’s a single way to go about
00:21:22 something in terms of characterizing the entire drug
00:21:25 discovery process.
00:21:26 If I look at the blood vessel one,
00:21:28 yeah, there the first step was to have the kinds of theories
00:21:34 that Dr. Folkman had.
00:21:35 The second step was to have the techniques where you could
00:21:38 study blood vessel growth for the first time and at least
00:21:40 quantitate or semi quantitate it.
00:21:44 Third step was to find substances that would stop blood
00:21:48 vessels from growing.
00:21:49 Fourth step was to maybe purify those substances.
00:21:54 There are many other steps too.
00:21:55 I mean, before you have an effective drug,
00:21:57 you have to show that it’s safe.
00:21:58 You have to show that it’s effective.
00:22:00 And you start with animals.
00:22:01 You ultimately go to patients.
00:22:03 And there are multiple kinds of clinical trials you have to do.
00:22:06 If you step back, is it amazing to you
00:22:08 that we descendants of great apes
00:22:11 are able to create drugs, chemicals that
00:22:18 are able to improve some aspects of our bodies?
00:22:22 Or is it quite natural that we’re
00:22:25 able to discover these kinds of things?
00:22:27 Well, at a high level, it is amazing.
00:22:29 I mean, evolution is amazing.
00:22:31 The way I look at your question, the fact
00:22:33 that we have evolved the way we’ve done,
00:22:36 I mean, it’s pretty remarkable.
00:22:38 So let’s talk about drug delivery.
00:22:41 What are the difficult problems in drug delivery?
00:22:43 What is drug delivery from starting
00:22:48 from your early seminal work in the field to today?
00:22:51 Well, drug delivery is getting a drug
00:22:55 to go where you want it, at the level you want it,
00:22:57 in a safe way.
00:22:59 Some of the big challenges, I mean, there are a lot.
00:23:02 I mean, I’d say one is, could you target the right cell?
00:23:06 Like, we talked about cancers or some way
00:23:08 to deliver a drug just to a cancer cell and no other cell.
00:23:11 Another challenge is to get drugs
00:23:14 across different barriers.
00:23:15 Like, could you ever give insulin orally?
00:23:17 Could you, or give it passively transdermally?
00:23:21 Can you get drugs across the blood brain barrier?
00:23:24 I mean, there are lots of big challenges.
00:23:26 Can you make smart drug delivery systems
00:23:29 that might respond to physiologic signals in the body?
00:23:32 Oh, interesting.
00:23:33 So smart, they have some kind of sense,
00:23:37 a chemical sensor, or is there something more
00:23:39 than a chemical sensor that’s able to respond
00:23:41 to something in the body?
00:23:43 Could be either one.
00:23:44 I mean, one example might be if you were diabetic,
00:23:48 if you got more glucose, could you get more insulin?
00:23:53 But that’s just an example.
00:23:57 Is there some way to control the actual mechanism
00:23:59 of delivery in response to what the body’s doing?
00:24:02 Yes, there is.
00:24:03 I mean, one of the things that we’ve done
00:24:05 is encapsulate what are called beta cells.
00:24:07 Those are insulin producing cells in a way
00:24:09 that they’re safe and protected.
00:24:11 And then what’ll happen is glucose will go in
00:24:15 and the cells will make insulin.
00:24:20 And so that’s an example.
00:24:23 So from an AI robotics perspective,
00:24:25 how close are these drug delivery systems
00:24:29 to something like a robot?
00:24:31 Or is it totally wrong to think about them
00:24:33 as intelligent agents?
00:24:35 And how much room is there to add that kind of intelligence
00:24:39 into these delivery systems, perhaps in the future?
00:24:42 Yeah, I think it depends on the particular delivery system.
00:24:45 Of course, one of the things people are concerned about
00:24:47 is cost, and if you add a lot of bells and whistles
00:24:49 to something, it’ll cost more.
00:24:51 But I mean, we, for example, have made
00:24:54 what I’ll call intelligent microchips
00:24:55 that can, where you can send a signal
00:24:58 and you’ll release drug in response to that signal.
00:25:01 And I think systems like that microchip someday
00:25:04 have the potential to do what you and I
00:25:06 were just talking about,
00:25:07 that there could be a signal like glucose
00:25:09 and it could have some instruction to say
00:25:11 when there’s more glucose, deliver more insulin.
00:25:14 So do you think it’s possible that there,
00:25:16 that could be robotic type systems roaming our body
00:25:19 sort of long term and be able to deliver
00:25:21 certain kinds of drugs in the future?
00:25:23 You see, do you see that kind of future?
00:25:26 Someday, I don’t think we’re very close to it yet,
00:25:29 but someday, you know that that’s nanotechnology
00:25:31 and that would mean even miniaturizing
00:25:33 some of the things that I just discussed.
00:25:35 And we’re certainly not at that point yet,
00:25:37 but someday I expect we will be.
00:25:40 So some of it is just the shrinking of the technology.
00:25:44 That’s a part of it, that’s one of the things.
00:25:47 In general, what role do you see AI sort of,
00:25:52 there’s a lot of work now with using data
00:25:55 to make intelligent, create systems
00:25:57 that make intelligent decisions.
00:25:59 Do you see any of that data driven kind of computing systems
00:26:04 having a role in any part of this,
00:26:09 into the delivery of drugs, the design of drugs
00:26:13 and any part of the chain?
00:26:15 I do, I think that AI can be useful
00:26:18 in a number of parts of the chain.
00:26:20 I mean, one, I think if you get a large amount
00:26:22 of information, you know, say you have some chemical data
00:26:26 because you’ve done high throughput screens
00:26:29 and let’s, I’ll just make this up,
00:26:30 but let’s say I have a, I’m trying to come up with a drug
00:26:33 to treat disease X, whatever that disease is
00:26:37 and I have a test for that and hopefully a fast test
00:26:43 and let’s say I test 10,000 chemical substances
00:26:47 and a couple work, most of them don’t work,
00:26:49 some maybe work a little, but if I had a,
00:26:52 with the right kind of artificial intelligence,
00:26:54 maybe you could look at the chemical structures
00:26:57 and look at what works and see
00:26:58 if there’s certain commonalities,
00:26:59 look at what doesn’t work and see what commonalities
00:27:02 there are and then maybe use that somehow
00:27:05 to predict the next generation of things
00:27:07 that you would test.
00:27:08 As a tangent, what are your thoughts
00:27:10 on our society’s relationship with pharmaceutical drugs?
00:27:14 Do we, and perhaps I apologize
00:27:17 if this is a philosophical broader question,
00:27:19 but do we over rely on them?
00:27:22 Do we improperly prescribe them?
00:27:24 In what ways is the system working well
00:27:26 and what way can it improve?
00:27:28 Well, I think pharmaceutical drugs are really important.
00:27:33 I mean, the life expectancy and life quality of people
00:27:37 over many, many years has increased tremendously
00:27:40 and I think that’s a really good thing.
00:27:42 I think one thing that would also be good
00:27:44 is if we could extend that more and more
00:27:45 to people in the developing world,
00:27:47 which is something that our lab has been doing
00:27:49 with the Gates Foundation or trying to do.
00:27:53 So I think ways in which it could improve,
00:27:55 I mean, if there was some way to reduce costs,
00:27:59 that’s certainly an issue people are concerned about.
00:28:01 If there was some way to help people in poor countries,
00:28:05 that would also be a good thing.
00:28:06 And then of course, we still need to make better drugs
00:28:10 for so many diseases.
00:28:12 I mean, cancer, diabetes.
00:28:14 I mean, there’s heart disease and rare diseases.
00:28:17 There are many, many situations where it’d be great
00:28:20 if we could do better and help more people.
00:28:22 Can we talk about another exciting space,
00:28:27 which is tissue engineering?
00:28:29 What is tissue engineering or regenerative medicine?
00:28:32 Yeah, so that tissue engineering or regenerative medicine
00:28:35 have to do with building an organ or tissue from scratch.
00:28:38 So someday maybe we can build a liver
00:28:43 or make new cartilage and also would enable you
00:28:47 to someday create organs on a chip,
00:28:49 which we and others are trying to do,
00:28:52 which might lead to better drug testing
00:28:54 and maybe less testing on animals or people.
00:28:57 Organs on a chip, that sounds fascinating.
00:29:01 So what are the various ways to generate tissue?
00:29:06 And how do, so is it, you know,
00:29:08 the one is of course from stem cells.
00:29:10 Is there other methods?
00:29:11 What are the different possible flavors here?
00:29:14 Yeah, well, I think, I mean, there’s multiple components.
00:29:17 One is having generally some type of scaffold.
00:29:19 That’s what Jay Vacanti and I started many, many years ago.
00:29:23 And then on that scaffold,
00:29:26 you might put different cell types,
00:29:28 which could be a cartilage cell, a bone cell,
00:29:30 could be a stem cell that might differentiate
00:29:32 into different things, could be more than one cell.
00:29:35 And the scaffold, sorry to interrupt,
00:29:37 is kind of like a canvas that’s a structure
00:29:39 that you can, on which the cells can grow?
00:29:43 I think that’s a good explanation what you just did.
00:29:44 I’ll have to use that, the canvas, that’s good.
00:29:47 Yeah, so I think that that’s fair.
00:29:49 You know, and the chip could be such a canvas.
00:29:52 Could be fibers that are made of plastics
00:29:55 that you’d put in the body someday.
00:29:57 And when you say chip, do you mean electronic chip?
00:29:59 Like a…
00:30:00 Not necessarily, it could be though.
00:30:02 But it doesn’t have to be, it could just be a structure
00:30:04 that’s not in vivo, so to speak,
00:30:08 that’s, you know, that’s outside the body.
00:30:10 So is there…
00:30:11 Canvas is not a bad word.
00:30:13 So is there a possibility to weave into this canvas
00:30:20 a computational component?
00:30:22 So if we talk about electronic chips,
00:30:23 some ability to sense, control,
00:30:28 some aspect of this growth process for the tissue.
00:30:31 I would say the answer to that is yes.
00:30:33 I think right now people are working mostly
00:30:36 on validating these kinds of chips for saying,
00:30:40 well, it does work as effectively,
00:30:43 or hopefully as just putting something in the body.
00:30:47 But I think someday what you suggested,
00:30:49 you certainly would be possible.
00:30:51 So what kind of tissues can we engineer today?
00:30:53 What would, yeah.
00:30:54 Yeah, well, so skin’s already been made
00:30:57 and approved by the FDA.
00:30:58 There are advanced clinical trials,
00:31:00 like what are called phase three trials,
00:31:03 that are at complete or near completion
00:31:05 for making new blood vessels.
00:31:08 One of my former students, Laura Nicholson,
00:31:10 led a lot of that.
00:31:13 Oh, that’s amazing.
00:31:14 So human skin can be grown.
00:31:16 That’s already approved in the entire, the FDA process.
00:31:20 So that means what,
00:31:23 so one, that means you can grow that tissue
00:31:27 and do various kinds of experiments
00:31:30 in terms of drugs and so on.
00:31:34 But what does that, does that mean
00:31:35 that some kind of healing and treatment
00:31:38 of different conditions for unhuman beings?
00:31:41 Yes, I mean, they’ve been approved now for,
00:31:43 I mean, different groups have made them,
00:31:45 different companies and different professors,
00:31:47 but they’ve been approved for burn victims
00:31:50 and for patients with diabetic skin ulcers.
00:31:53 That’s amazing.
00:31:54 Okay, so skin, what else?
00:31:59 Well, at different stages,
00:32:01 people are, like skin, blood vessels,
00:32:05 there’s clinical trials going now for helping patients
00:32:08 hear better, for patients that might be paralyzed,
00:32:12 for patients that have different eye problems.
00:32:15 I mean, and different groups have worked on
00:32:18 just about everything, new liver, new kidneys.
00:32:20 I mean, there’ve been all kinds of work done in this area.
00:32:24 Some of it’s early, but there’s certainly
00:32:26 a lot of activity.
00:32:27 What about neural tissue?
00:32:30 Yeah.
00:32:31 The nervous system and even the brain.
00:32:34 Well, there’ve been people out of working on that too.
00:32:36 We’ve done a little bit with that,
00:32:37 but there are people who’ve done a lot on neural stem cells
00:32:40 and I know Evan Snyder, who’s been one of our collaborators
00:32:43 on some of our spinal cord works done work like that
00:32:46 and there’ve been other people as well.
00:32:48 Is there challenges for the,
00:32:51 when it is part of the human body,
00:32:52 is there challenges to getting the body to accept
00:32:55 this new tissue that’s being generated?
00:32:58 How do you solve that kind of challenge?
00:33:00 There can be problems with accepting it.
00:33:02 I think maybe in particular,
00:33:04 you might mean rejection by the body.
00:33:07 So there are multiple ways that people are trying
00:33:09 to deal with that.
00:33:10 One way is, which was what we’ve done with Dan Anderson,
00:33:14 who was one of my former postdocs
00:33:16 and I mentioned this a little bit before for a pancreas,
00:33:19 is encapsulating the cells.
00:33:20 So immune cells or antibodies can’t get in and attack them.
00:33:26 So that’s a way to protect them.
00:33:28 Other strategies could be making the cells non immunogenic,
00:33:34 which might be done by different either techniques
00:33:36 which might mask them or using some gene editing approaches.
00:33:40 So there are different ways that people
00:33:42 are trying to do that.
00:33:43 And of course, if you use the patient’s own cells
00:33:45 or cells from a close relative, that might be another way.
00:33:50 It increases the likelihood that it’ll get accepted
00:33:52 if you use the patient’s own cells.
00:33:54 Yes.
00:33:55 And then finally, there’s immunosuppressive drugs,
00:33:57 which will suppress the immune response.
00:34:00 That’s right now what’s done, say, for a liver transplant.
00:34:03 The fact that this whole thing works is fascinating,
00:34:06 at least from my outside perspective.
00:34:09 Will we one day be able to regenerate any organ
00:34:13 or part of the human body?
00:34:15 Any of you?
00:34:16 I mean, it’s exciting to think about future possibilities
00:34:19 of tissue engineering.
00:34:22 Do you see some tissues more difficult than others?
00:34:25 What are the possibilities here?
00:34:27 Yeah, well, of course, I’m an optimist.
00:34:29 And I also feel the timeframe,
00:34:30 if we’re talking about someday,
00:34:32 someday could be hundreds of years.
00:34:33 But I think that, yes, someday,
00:34:36 I think we will be able to regenerate many things.
00:34:39 And there are different strategies that one might use.
00:34:41 One might use some cells themselves.
00:34:44 One might use some molecules
00:34:47 that might help regenerate the cells.
00:34:49 And so I think there are different possibilities.
00:34:51 What do you think that means for longevity?
00:34:54 If we look maybe not someday, but 10, 20 years out,
00:35:00 the possibilities of tissue engineering,
00:35:01 the possibilities of the research that you’re doing,
00:35:04 does it have a significant impact
00:35:06 on the longevity of human life?
00:35:10 I don’t know that we’ll see
00:35:11 a radical increase in longevity,
00:35:12 but I think that in certain areas,
00:35:15 we’ll see people live better lives
00:35:19 and maybe somewhat longer lives.
00:35:21 What’s the most beautiful scientific idea
00:35:25 in bioengineering that you’ve come across
00:35:28 in your years of research?
00:35:30 I apologize for the romantic question.
00:35:33 No, that’s an interesting question.
00:35:35 I certainly think what’s happening right now
00:35:37 with CRISPR is a beautiful idea.
00:35:39 That certainly wasn’t my idea.
00:35:42 I mean, but I think it’s very interesting here
00:35:45 what people have capitalized on
00:35:48 is that there’s a mechanism by which bacteria
00:35:52 are able to destroy viruses.
00:35:54 And that understanding that leads to machinery
00:35:58 to sort of cut and paste genes and fix a cell.
00:36:06 So that kind of, do you see a promise
00:36:09 for that kind of ability to copy and paste?
00:36:13 I mean, like we said, the human body is complicated.
00:36:16 Is that, that seems exceptionally difficult to do.
00:36:23 I think it is exceptionally difficult to do,
00:36:25 but that doesn’t mean that it won’t be done.
00:36:27 There’s a lot of companies and people trying to do it.
00:36:30 And I think in some areas it will be done.
00:36:32 Some of the ways that you might lower the bar
00:36:36 are not, are just taking,
00:36:39 like not necessarily doing it directly,
00:36:40 but you could take a cell that might be useful,
00:36:45 but you want to give it some cancer killing capabilities,
00:36:48 something like what’s called a CAR T cell.
00:36:50 And that might be a different way
00:36:52 of somehow making a CAR T cell and maybe making it better.
00:36:56 So there might be sort of easier things
00:36:58 and rather than just fixing the whole body.
00:37:01 So the way a lot of things have moved with medicine
00:37:04 over time is stepwise.
00:37:06 So I can see things that might be easier to do
00:37:10 than say, fix a brain.
00:37:11 That would be very hard to do,
00:37:13 but maybe someday that’ll happen too.
00:37:16 So in terms of stepwise, that’s an interesting notion.
00:37:19 Do you see that if you look at medicine or bioengineering,
00:37:25 do you see that there is these big leaps
00:37:29 that happen every decade or so, or some distant period,
00:37:33 or is it a lot of incremental work?
00:37:36 Not, I don’t mean to reduce its impact
00:37:39 by saying it’s incremental,
00:37:40 but is there sort of phase shifts in the science,
00:37:46 big leaps?
00:37:48 I think there’s both.
00:37:49 Every so often a new technique or a new technology comes out.
00:37:54 I mean, genetic engineering was an example.
00:37:56 I mentioned CRISPR.
00:37:58 I think every so often things happen
00:38:01 that make a big difference,
00:38:03 but still there’s to try to really make progress,
00:38:07 make a new drug, make a new device.
00:38:09 There’s a lot of things.
00:38:11 I don’t know if I’d call them incremental,
00:38:12 but there’s a lot, a lot of work that needs to be done.
00:38:15 Absolutely.
00:38:16 So you have over, numbers could be off,
00:38:20 but it’s a big amount.
00:38:22 You have over 1,100 current or pending patents
00:38:25 that have been licensed, sublicensed
00:38:27 to over 300 companies.
00:38:29 What’s your view, what in your view are the strengths
00:38:33 and what are the drawbacks of the patenting process?
00:38:36 Well, I think for the most part, there’s strengths.
00:38:39 I think that if you didn’t have patents,
00:38:42 especially in medicine,
00:38:43 you’d never get the funding that it takes
00:38:45 to make a new drug or a new device.
00:38:47 I mean, which according to Tufts,
00:38:49 to make a new drug costs over $2 billion right now.
00:38:52 And nobody would even come close to giving you that money,
00:38:55 any of that money, if it weren’t for the patent system,
00:39:00 because then anybody else could do it.
00:39:03 That then leads to the negative though.
00:39:08 Sometimes somebody does have a very successful drug
00:39:11 and you certainly wanna try to make it available
00:39:14 to everybody.
00:39:15 And so the patent system allowed it to happen
00:39:21 in the first place, but maybe it’ll impede it
00:39:23 after a little bit, or certainly to some people
00:39:26 or to some companies, once it is out there.
00:39:31 What’s the, on the point of the cost,
00:39:34 what would you say is the most expensive part
00:39:37 of the $2 billion of making a drug?
00:39:40 Human clinical trials.
00:39:42 That is by far the most expensive.
00:39:44 In terms of money or pain or both?
00:39:47 Well, money, but pain goes, it’s hard to know.
00:39:50 I mean, but usually proving things that are,
00:39:54 proving that something new is safe and effective in people
00:39:57 is almost always the biggest expense.
00:40:00 Could you linger on that for just a little longer
00:40:02 and describe what it takes to prove,
00:40:06 for people that don’t know, in general,
00:40:09 what it takes to prove that something is effective on humans?
00:40:12 Well, you’d have to take a particular disease,
00:40:17 but the process is you start out with,
00:40:20 usually you start out with cells,
00:40:21 then you’d go to animal models.
00:40:23 Usually you have to do a couple animal models.
00:40:25 And of course the animal models aren’t perfect for humans.
00:40:28 And then you have to do three sets of clinical trials
00:40:31 at a minimum, a phase one trial to show that it’s safe
00:40:34 in small number of patients, a phase two trial
00:40:36 to show that it’s effective in a small number of patients,
00:40:39 and a phase three trial to show that it’s safe and effective
00:40:42 in a large number of patients.
00:40:44 And that could end up being hundreds
00:40:46 or thousands of patients.
00:40:49 And they have to be really carefully controlled studies.
00:40:52 And you’d have to manufacture the drug,
00:40:55 you’d have to really watch those patients.
00:40:58 You have to be very concerned that it is gonna be safe.
00:41:03 And then you look and see, does it treat the disease better
00:41:07 than whatever the gold standard was before that?
00:41:10 Assuming there was one.
00:41:12 That’s a really interesting line.
00:41:14 Show that it’s safe first, and then that it’s effective.
00:41:17 First do no harm.
00:41:19 First do no harm, that’s right.
00:41:21 So how, again, if you can linger in a little bit,
00:41:26 how does the patenting process work?
00:41:29 Yeah, well, you do a certain amount of research,
00:41:32 though that’s not necessarily has to be the case.
00:41:35 But for us, usually it is.
00:41:36 Usually we do a certain amount of research
00:41:40 and make some findings.
00:41:41 And we had a hypothesis, let’s say we prove it,
00:41:46 or we make some discovery, we invent some technique.
00:41:49 And then we write something up, what’s called a disclosure.
00:41:52 We give it to MIT’s technology transfer office.
00:41:55 They then give it to some patent attorneys,
00:41:57 and they use that plus talking to us
00:42:00 and work on writing a patent.
00:42:03 And then you go back and forth with the USPTO,
00:42:07 that’s the United States Patent and Trademark Office.
00:42:09 And they may not allow it the first, second or third time,
00:42:14 but they will tell you why they don’t.
00:42:17 And you may adjust it,
00:42:18 and maybe you’ll eventually get it, and maybe you won’t.
00:42:21 So you’ve been part of launching 40 companies
00:42:24 together worth, again, numbers could be outdated,
00:42:28 but an estimated $23 billion.
00:42:33 You’ve described your thoughts
00:42:34 on a formula for startup success.
00:42:36 So perhaps you can describe that formula
00:42:38 and in general describe what does it take
00:42:41 to build a successful startup?
00:42:44 Well, I’d break that down into a couple of categories.
00:42:46 And I’m a scientist and certainly
00:42:48 from the science standpoint, I’ll go over that.
00:42:50 But I actually think that really the most important thing
00:42:54 is probably the business people that I work with.
00:42:57 And when I look back at the companies that have done well,
00:43:01 it’s been because we’ve had great business people.
00:43:03 And when they haven’t done as well,
00:43:05 we haven’t had as good business people.
00:43:06 But from a science standpoint,
00:43:08 I think about that we’ve made some kind of discovery
00:43:12 that is almost what I’d call a platform
00:43:15 that you could use it for different things.
00:43:17 And certainly the drug delivery system example
00:43:20 that I gave earlier is a good example of that.
00:43:22 You could use it for drug A, B, C, D, E and so forth.
00:43:27 And that I’d like to think that we’ve taken it far enough
00:43:30 so that we’ve written at least one really good paper
00:43:33 in a top journal, hopefully a number
00:43:36 that we’ve reduced it to practice and animal models
00:43:39 that we’ve filed patents, maybe had issued patents
00:43:45 that have what I’ll call very good and broad claims.
00:43:48 That’s sort of the key on a patent.
00:43:50 And then in our case, a lot of times when we’ve done it,
00:43:55 a lot of times it’s somebody in the lab
00:43:57 like a postdoc or graduate student
00:43:59 that spent a big part of their life doing it
00:44:01 and that they wanna work at that company
00:44:03 because they have this passion
00:44:04 that they wanna see something they did
00:44:06 make a difference in people’s lives.
00:44:09 Maybe you can mention the business component.
00:44:12 It’s funny to hear Grace had to say
00:44:15 that there’s value to business folks.
00:44:17 Oh yeah, well.
00:44:18 That’s not always said.
00:44:20 So what value, what business instinct is valuable
00:44:25 to make a startup successful, a company successful?
00:44:29 I think the business aspects are,
00:44:32 you have to be a good judge of people
00:44:35 so that you hire the right people.
00:44:37 You have to be strategic so you figure out
00:44:40 if you do have that platform
00:44:41 that could be used for all these different things.
00:44:44 And knowing that medical research is so expensive,
00:44:47 what thing are you gonna do first, second,
00:44:49 third, fourth and fifth?
00:44:51 I think you need to have a good,
00:44:53 what I’ll call FDA regulatory clinical trial strategy.
00:44:58 I think you have to be able to raise money incredibly.
00:45:01 So there are a lot of things.
00:45:02 You have to be good with people, good manager of people.
00:45:05 So the money and the people part I get,
00:45:08 but the stuff before in terms of deciding the A, B, C, D,
00:45:13 if you have a platform which drugs to first take a testing,
00:45:16 you see nevertheless scientists
00:45:18 as not being always too good at that process.
00:45:22 Well, I think they’re a part of the process,
00:45:24 but I’d say there’s probably, I’m gonna just make this up,
00:45:28 but maybe six or seven criteria that you wanna use
00:45:31 and it’s not just science.
00:45:33 I mean, the kinds of things that I would think about
00:45:35 is, is the market big or small?
00:45:37 Is the, are there good animal models for it
00:45:41 so that you could test it and it wouldn’t take 50 years?
00:45:45 Are the clinical trials that could be set up
00:45:48 ones that have clear end points
00:45:51 where you can make a judgment?
00:45:53 And another issue would be competition.
00:45:58 Are there other ways that some companies
00:46:00 out there are doing it?
00:46:01 Another issue would be reimbursement.
00:46:05 You know, can it get reimbursed?
00:46:07 So a lot of things that you have manufacturing issues
00:46:10 you’d wanna consider.
00:46:11 So I think there are really a lot of things
00:46:13 that go into whether you,
00:46:15 what you do first, second, third, or fourth.
00:46:19 So you lead one of the largest academic labs in the world
00:46:23 with over $10 million in annual grants
00:46:27 and over a hundred researchers,
00:46:28 probably over a thousand since the lab’s beginning.
00:46:31 Researchers can be individualistic and eccentric.
00:46:37 How do I put it nicely?
00:46:38 There you go, eccentric.
00:46:40 So what insights into research leadership can you give
00:46:43 having to run such a successful lab
00:46:45 with so much diverse talent?
00:46:49 Well, I don’t know that I’m any expert.
00:46:50 I think that what you do to me,
00:46:53 I mean, I just want,
00:46:54 I mean, this is gonna sound very simplistic,
00:46:56 but I just want people in the lab to be happy,
00:46:58 to be doing things that I hope
00:47:00 will make the world a better place,
00:47:02 to be working on science
00:47:04 that can make the world a better place.
00:47:06 And I guess my feeling is if we’re able to do that,
00:47:11 you know, it kind of runs itself.
00:47:13 So how do you make a researcher happy in general?
00:47:17 I think when people feel,
00:47:19 I mean, this is gonna sound like, again,
00:47:21 simplistic or maybe like motherhood and apple pie,
00:47:23 but I think if people feel they’re working on something
00:47:26 really important that can affect many other people’s lives
00:47:30 and they’re making some progress,
00:47:32 they’ll feel good about it
00:47:34 and they’ll feel good about themselves
00:47:35 and they’ll be happy.
00:47:37 But through brainstorming and so on,
00:47:39 what’s your role and how difficult is it as a group
00:47:43 in this collaboration to arrive at these big questions
00:47:49 that might have impact?
00:47:51 Well, the big questions come from many different ways.
00:47:54 Sometimes it’s trying to, things that I might think of
00:47:57 or somebody in the lab might think of,
00:47:59 which could be a new technique
00:48:00 or to understand something better.
00:48:02 But gee, we’ve had people like Bill Gates
00:48:05 and the Gates Foundation come to us
00:48:07 and Juvenile Diabetes Foundation come to us and say,
00:48:10 gee, could you help us on these things?
00:48:11 And I mean, that’s good too.
00:48:13 It doesn’t happen just one way.
00:48:16 And I mean, you’ve kind of mentioned it, happiness,
00:48:20 but is there something more,
00:48:24 how do you inspire a researcher
00:48:26 to do the best work of their life?
00:48:28 So you mentioned passion and passion is a kind of fire.
00:48:32 Do you see yourself having a role to keep that fire going,
00:48:35 to build it up, to inspire the researchers
00:48:39 through the pretty difficult process
00:48:42 of going from idea to big question, to big answer?
00:48:47 I think so.
00:48:48 I think I try to do that by talking to people
00:48:52 going over their ideas and their progress.
00:48:56 I try to do it as an individual.
00:49:00 Certainly when I talk about my own career,
00:49:01 I had my setbacks at different times
00:49:04 and people know that, that know me.
00:49:06 And you just try to keep pushing and so forth.
00:49:12 But yeah, I think I try to do that.
00:49:15 But yeah, I think I try to do that
00:49:17 as the one who leads the lab.
00:49:20 So you have this exceptionally successful lab
00:49:23 and one of the great institutions in the world, MIT.
00:49:29 And yet sort of, at least in my neck of the woods
00:49:32 in computer science and artificial intelligence,
00:49:36 a lot of the research is kind of,
00:49:40 a lot of the great researchers, not everyone,
00:49:43 but some are kind of going to industry.
00:49:46 A lot of the research is moving to industry.
00:49:49 What do you think about the future of science in general?
00:49:52 Is there drawbacks?
00:49:54 Is there strength to the academic environment
00:49:58 that you hope will persist?
00:49:59 How does it need to change?
00:50:02 What needs to stay the same?
00:50:04 What are your thoughts on this whole landscape
00:50:05 of science and its future?
00:50:08 Well, first I think going to industry is good,
00:50:10 but I think being in academia is good.
00:50:12 You know, I have lots of students who’ve done both
00:50:15 and they’ve had great careers doing both.
00:50:18 I think from an academic standpoint,
00:50:21 I mean, the biggest concern probably that people feel today,
00:50:24 you know, at a place like MIT
00:50:26 or other research heavy institutions is gonna be funding
00:50:30 and particular funding that’s not super directed,
00:50:34 you know, so that you can do basic research.
00:50:37 I think that’s probably the number one thing,
00:50:39 but you know, it would be great if we as a society
00:50:43 could come up with better ways to teach,
00:50:45 you know, so that people all over could learn better.
00:50:50 You know, so I think there are a number of things
00:50:51 that would be good to be able to do better.
00:50:55 So again, you’re very successful in terms of funding,
00:50:58 but do you still feel the pressure of that,
00:51:01 of having to seek funding?
00:51:04 Does it affect the science or is it,
00:51:07 or can you simply focus on doing the best work of your life
00:51:11 and the funding comes along with that?
00:51:14 I’d say the last 10 or 15 years,
00:51:16 we’ve done pretty well funding,
00:51:18 but I always worry about it.
00:51:19 You know, it’s like you’re still operating
00:51:23 on more soft money than hard.
00:51:25 And so I always worry about it,
00:51:27 but we’ve been fortunate that places have come to us
00:51:33 like the Gates Foundation and others,
00:51:34 Juvenile Diabetes Foundation, some companies,
00:51:37 and they’re willing to give us funding
00:51:39 and we’ve gotten government money as well.
00:51:42 We have a number of NIH grants and I’ve always had that
00:51:44 and that’s important to me too.
00:51:47 So I worry about it, but you know,
00:51:51 I just view that as a part of the process.
00:51:53 Now, if you put yourself in the shoes of a philanthropist,
00:51:57 like say I gave you $100 billion right now,
00:52:02 but you couldn’t spend it on your own research.
00:52:05 So how hard is it to decide which labs to invest in,
00:52:12 which ideas, which problems, which solutions?
00:52:16 You know, cause funding is so much,
00:52:19 such an important part of progression of science
00:52:22 in today’s society.
00:52:24 So if you put yourself in the shoes of a philanthropist,
00:52:26 how hard is that problem?
00:52:27 How would you go about solving it?
00:52:29 Sure, well, I think what I do, the first thing is different
00:52:32 philanthropists have different visions.
00:52:34 And I think the first thing is to form a concrete vision
00:52:37 of what you want.
00:52:38 Some people, I mean, I’ll just give you two examples
00:52:41 of people that I know.
00:52:44 David Koch was very interested in cancer research
00:52:47 and part of that was that he had prostate cancer.
00:52:51 And a number of people do that along those lines.
00:52:55 They’ve had somebody, they’ve either had cancer themselves
00:52:57 or somebody they loved had cancer
00:53:00 and they wanna put money into cancer research.
00:53:02 Bill Gates, on the other hand,
00:53:04 I think when he had got his fortune,
00:53:06 I mean, he thought about it and felt, well,
00:53:08 how could he have the greatest impact?
00:53:10 And he thought about, you know, helping people
00:53:12 in the developing world and medicines
00:53:15 and different things like that, like vaccines
00:53:18 that might be really helpful for people
00:53:20 in the developing world.
00:53:21 And so I think first you start out with that vision.
00:53:25 Once you start out with that vision, whatever vision it is,
00:53:29 then I think you try to ask the question,
00:53:33 who in the world does the best work if that was your goal?
00:53:38 I mean, but you really, I think have to have
00:53:40 a defined vision.
00:53:41 Vision first.
00:53:41 Yeah, and I think that’s what people do.
00:53:45 I mean, I have never seen anybody do it otherwise.
00:53:48 I mean, and that, by the way,
00:53:49 may not be the best thing overall.
00:53:53 I mean, I think it’s good that all those things happen,
00:53:55 but, you know, what you really want to do,
00:53:57 and I’ll make a contrast in a second,
00:54:00 in addition to funding important areas,
00:54:02 like what both of those people did, is to help young people.
00:54:07 And they may be at odds with each other
00:54:10 because a far more, a lab like ours,
00:54:13 which is, you know, I’m older, is, you know,
00:54:15 might be very good at addressing some of those kinds
00:54:18 of problems, but, you know, I’m not young.
00:54:20 I train a lot of people who are young,
00:54:22 but it’s not the same as helping somebody
00:54:24 who’s an assistant professor someplace.
00:54:26 So I think what’s, I think, been good about our thing,
00:54:30 our society, or things overall,
00:54:33 are that there are people who come at it
00:54:35 from different ways, and the combination,
00:54:37 the confluence of the government funding,
00:54:40 the certain foundations that fund things,
00:54:43 and other foundations that, you know,
00:54:46 want to see disease treated,
00:54:48 well, then they can go seek out people,
00:54:51 or they can put a request for proposals
00:54:53 and see who does the best.
00:54:54 You know, I’d say both David Koch and Bill Gates
00:54:58 did exactly that.
00:54:58 They sought out people, both of them, you know,
00:55:02 or their foundations that they were involved in,
00:55:04 sought out people like myself.
00:55:07 But they also had requests for proposals.
00:55:11 Now, you mentioned young people,
00:55:12 and that reminds me of something you said
00:55:14 in an interview of Written Somewhere,
00:55:17 that said some of your initial struggles
00:55:21 in terms of finding a faculty position, or so on,
00:55:28 that you didn’t quite, for people,
00:55:30 fit into a particular bucket, a particular.
00:55:33 Right.
00:55:35 Can you speak to that?
00:55:38 How, do you see limitations to the academic system
00:55:41 that it does have such buckets?
00:55:44 Is there, how can we allow for people
00:55:49 who are brilliant, but outside the disciplines
00:55:56 of the previous decade?
00:55:59 Yeah, well, I think that’s a great question.
00:56:01 I think that, I think the department heads
00:56:03 have to have a vision, you know, and some of them do.
00:56:07 Every so often, you know, there are institutes
00:56:11 or labs that do that.
00:56:13 I mean, at MIT, I think that’s done sometimes.
00:56:17 I know mechanical engineering department just had a search,
00:56:21 and they hired Gio Traverso, who is one of my,
00:56:25 he was a fellow with me, but he’s actually
00:56:28 a molecular biologist and a gastroenterologist.
00:56:32 And, you know, he’s one of the best in the world,
00:56:34 but he’s also done some great mechanical engineering
00:56:37 and designing some new pills and things like that.
00:56:39 And they picked him, and boy, I give them a lot of credit.
00:56:43 I mean, that’s vision, to pick somebody.
00:56:46 And I think, you know, they’ll be the richer four.
00:56:49 I think the Media Lab has certainly hired, you know,
00:56:52 people like Ed Boyden and others who have done,
00:56:55 you know, very different things.
00:56:56 And so I think that, you know, that’s part of the vision
00:57:00 of the leadership who do things like that.
00:57:03 Do you think one day, you’ve mentioned David Koch and cancer,
00:57:07 do you think one day we’ll cure cancer?
00:57:10 Yeah, I mean, of course, one day,
00:57:12 I don’t know how long that day will come.
00:57:14 Soon.
00:57:15 Yeah, soon, soon, no, but I think.
00:57:17 So you think it is a grand challenge,
00:57:19 it is a grand challenge,
00:57:20 it’s not just solvable within a few years.
00:57:22 No, I don’t think very many things
00:57:24 are solvable in a few years.
00:57:25 There’s some good ideas that people are working on,
00:57:28 but I mean, all cancers, that’s pretty tough.
00:57:32 If we do get the cure, what will the cure look like?
00:57:35 Do you think which mechanisms,
00:57:37 which disciplines will help us arrive at that cure
00:57:40 from all the amazing work you’ve done
00:57:42 that has touched on cancer?
00:57:44 No, I think it’ll be a combination
00:57:45 of biology and engineering.
00:57:46 I think it’ll be biology to understand
00:57:50 the right genetic mechanisms to solve this problem
00:57:54 and maybe the right immunological mechanisms
00:57:56 and engineering in the sense of producing the molecules,
00:58:00 developing the right delivery systems,
00:58:02 targeting it or whatever else needs to be done.
00:58:05 Well, that’s a beautiful vision for engineering.
00:58:08 So on a lighter topic, I’ve read that you love chocolate
00:58:11 and mentioned two places, Ben and Bill’s Chocolate Aquarium
00:58:16 and the chocolate cookies, the Soho Globs
00:58:20 from Rosie’s Bakery in Chestnut Hill.
00:58:22 I went to their website and I was trying
00:58:25 to finish a paper last night.
00:58:26 There’s a deadline today and yet I was wasting
00:58:30 way too much time at 3 a.m. instead of writing the paper,
00:58:34 staring at the Rosie Baker’s cookies,
00:58:36 which are just look incredible.
00:58:38 The Soho Globs just look incredible.
00:58:40 But for me, oatmeal white raisin cookies won my heart
00:58:44 just from the pictures.
00:58:46 Do you think one day we’ll be able to engineer
00:58:49 the perfect cookie with the help of chemistry
00:58:52 and maybe a bit of data driven artificial intelligence
00:58:55 or is cookies something that’s more art than engineering?
00:59:02 I think there’s some of both.
00:59:03 I think engineering will probably help someday.
00:59:06 What about chocolate?
00:59:08 Same thing, same thing.
00:59:09 You’d have to go to see some of David Edwards stuff.
00:59:12 He was one of my postdocs and he’s a professor at Harvard
00:59:15 but he also started Cafe Art Sciences
00:59:18 and it’s just a really cool restaurant around here.
00:59:22 But he also has companies that do ways
00:59:26 of looking at fragrances and trying to use engineering
00:59:30 in new ways and so I think that’s just an example.
00:59:34 But I expect someday that AI and engineering
00:59:38 will play a role in almost everything.
00:59:40 Including creating the perfect cookie.
00:59:42 Yes.
00:59:43 Well, I dream of that day as well.
00:59:45 So when you look back at your life,
00:59:47 having accomplished an incredible amount of positive impact
00:59:50 on the world through science and engineering,
00:59:53 what are you most proud of?
00:59:56 My students, I really feel when I look at that,
00:59:59 we’ve probably had close to 1,000 students
01:00:02 go through the lab and they’ve done incredibly well.
01:00:06 I think 18 are in the National Academy of Engineering,
01:00:09 16 in the National Academy of Medicine.
01:00:12 I mean, they’ve been CEOs of companies,
01:00:15 presidents of universities and they’ve done,
01:00:19 I think eight are faculty at MIT,
01:00:21 maybe about 12 at Harvard.
01:00:22 I mean, so it really makes you feel good
01:00:25 to think that the people, they’re not my children
01:00:28 but they’re close to my children in a way
01:00:31 and it makes you feel really good
01:00:32 to see them have such great lives
01:00:34 and them do so much good and be happy.
01:00:37 Well, I think that’s a perfect way to end it, Bob.
01:00:40 Thank you so much for talking to me.
01:00:41 My pleasure.
01:00:41 It was an honor.
01:00:42 Good questions.
01:00:43 Thank you.
01:00:44 Thanks for listening to this conversation with Bob Langer
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01:01:19 at Lex Friedman, spelled without the E, just F R I D M A N.
01:01:25 And now let me leave you with some words from Bill Bryson
01:01:28 in his book, A Short History of Nearly Everything.
01:01:31 If this book has a lesson,
01:01:33 it is that we’re awfully lucky to be here.
01:01:36 And by we, I mean every living thing.
01:01:39 To attain any kind of life in this universe of ours
01:01:42 appears to be quite an achievement.
01:01:44 As humans, we’re doubly lucky, of course.
01:01:47 We enjoy not only the privilege of existence,
01:01:50 but also the singular ability to appreciate it
01:01:53 and even in a multitude of ways to make it better.
01:01:57 It is talent we have only barely begun to grasp.
01:02:01 Thank you for listening and hope to see you next time.