Latest / Get Real with Jim Weiss / Your Cells Are Technology with Futurist Andrew Hessel

Transcript

Your Cells Are Technology with Futurist Andrew Hessel · Get Real with Jim Weiss

0:00
Speaker 1: Just about everything inspired me, but obviously talking about the
0:04
Speaker 1: individualized cancer treatment I think is the most critical for
0:07
Speaker 1: me personally. We've actually went down that road when Otter
0:11
Speaker 1: had her cancer and we were exploring it, and I've
0:14
Speaker 1: worked in the space of cartes and cell therapies that
0:19
Speaker 1: are really more one to one versus one drug hits
0:23
Speaker 1: all approaches. There are some that are great, like some
0:27
Speaker 1: of the PD one cancer immunotherapies have had a positive impact.
0:32
Speaker 1: But I think at the end of the day, this
0:34
Speaker 1: idea of individual sequencing that we can do ourselves that
0:40
Speaker 1: can help you engineer if you get any disease, really
0:44
Speaker 1: but engineer a treatment to attack that disease. I mean,
0:48
Speaker 1: that seems to be the future, and the big issue
0:51
Speaker 1: is it's scalable. It sounds like we're not far from that.
0:55
Speaker 1: And the reason I believe it is the taking off
0:59
Speaker 1: of the GLP one space, and now I think we're
1:03
Speaker 1: going to see it in hormones. People are taking more
1:07
Speaker 1: control and responsibility for their own health and realizing, okay,
1:12
Speaker 1: I've got to sequence, and you know, I've got to
1:15
Speaker 1: know what is happening. And I do think we're going
1:18
Speaker 1: to move in a direction that is very not self diagnosis,
1:22
Speaker 1: but I would say better informed health planning for your
1:27
Speaker 1: whole life. That's been our theme here, and I think
1:30
Speaker 1: it was nice to hear reassurance that those technologies could
1:34
Speaker 1: become reality because you always hear how they're not cost
1:37
Speaker 1: effective and they'll never be scalable and they'll take billions
1:40
Speaker 1: to do it. Well, what better way to spend billions.
1:44
Speaker 1: I think people should listen to this episode mainly, I
1:47
Speaker 1: think to reduce some of their fears in and around
1:52
Speaker 1: the use of AI in medicine and in healthcare and
1:56
Speaker 1: tech in general, right, because I think tech was always
1:59
Speaker 1: interesting in the health and science areas, but it's really
2:03
Speaker 1: going to accelerate things and expand our ability to do
2:07
Speaker 1: more versus contract that we have technologies that can help
2:13
Speaker 1: us overcome a lot of obstacles. And I think it's
2:15
Speaker 1: just the half glass full version. A lot of people
2:18
Speaker 1: are pessimistic about what the world would be like for
2:21
Speaker 1: our kids and their kids, you know, my grandkids, you know,
2:25
Speaker 1: and all that, and it's like, oh, that sounds like
2:27
Speaker 1: it's going to be really freaking cool obviously if it's
2:30
Speaker 1: applied the right way. Hey Andrew, thanks for coming on.
2:35
Speaker 2: Hey, it's my pleasure.
2:36
Speaker 1: Man. How did you get into this line of work?
2:39
Speaker 1: Has it gone as you expected? Oh?
2:42
Speaker 2: No, I've had no plans. There's been very few expectations.
2:45
Speaker 2: I was just someone who was always interested in how
2:49
Speaker 2: things work, always like I remember distinctly asking my parents
2:55
Speaker 2: for those books at Christmas time how things work, and
2:57
Speaker 2: I just go through them cover to cover. Most machines
3:01
Speaker 2: back then were pretty simple. I was born in the
3:03
Speaker 2: nineteen sixties and in my teen years, as I'm going
3:06
Speaker 2: through high school, I was working with everything mechanical, electrical,
3:13
Speaker 2: starting to get into the first PCs. But I realized
3:17
Speaker 2: the one thing that nobody really knows how it works
3:21
Speaker 2: is biology, and that's where I decided i'd focus. And
3:24
Speaker 2: when I switched to essentially bio one on one in
3:27
Speaker 2: the whole program in university, going through life sciences, most
3:31
Speaker 2: of my peers were people that were just going into
3:35
Speaker 2: so they could go into medicine because you needed a
3:37
Speaker 2: couple of years of introductory biology, whereas I was completely
3:41
Speaker 2: focused on single celled organisms, the basic machinery of biology
3:46
Speaker 2: of the cell, and wanted to know how the cell
3:48
Speaker 2: works from a fundamental level. So that's shaped most of
3:51
Speaker 2: my career as well as drawing analogies to the electronic
3:57
Speaker 2: world to the computational world, because it turns out that
4:00
Speaker 2: cells and computers very different mediums, but they share a
4:04
Speaker 2: lot of the same architectures.
4:06
Speaker 1: And the worlds are colliding. I mean, I remember I
4:09
Speaker 1: started my biotech career at Genentech in nineteen ninety two
4:13
Speaker 1: and Art Lovinson was the head of R and D,
4:15
Speaker 1: and you know, I remember him being very focused on
4:19
Speaker 1: computers and technology and data in ways that you know,
4:25
Speaker 1: I hadn't really appreciated fully, and how they put all
4:29
Speaker 1: that together to design, you know, really great clinical trials.
4:33
Speaker 1: Obviously they became incredibly successful. You basically said, the age
4:38
Speaker 1: of programming life has arrived. What does that entail like?
4:42
Speaker 1: It sounds a little scary, but maybe not, you know,
4:47
Speaker 1: you want to talk about that.
4:48
Speaker 2: Yeah, I'm happy to so. Our career paths are probably
4:52
Speaker 2: similar in some ways because I joined Amjin and Genetech's
4:56
Speaker 2: probably main competitor in nineteen ninety five, and I came
5:01
Speaker 2: in because I recognized that we were entering a new
5:05
Speaker 2: age in genomics. The Human Genome Project was five years
5:10
Speaker 2: and I had seen new types of sequencers on the
5:15
Speaker 2: bench they hadn't even been It was still several years
5:17
Speaker 2: before commercialization that were game changing. I recognized that I
5:22
Speaker 2: really needed it was time to move into life science,
5:25
Speaker 2: and I was brought in because I was one of
5:27
Speaker 2: the first people kind of working in bioinformatics. I was
5:31
Speaker 2: using computers every day to analyze geneticode, build databases, process information.
5:37
Speaker 2: That just wasn't a common skill in the folks in
5:42
Speaker 2: life science at the time, So it was a really
5:44
Speaker 2: good fit for me. That being said, going back to
5:47
Speaker 2: programming life, I saw very clearly from the earliest days
5:50
Speaker 2: that the cell was a processor. It wasn't like a
5:53
Speaker 2: computer processor in that a computer processor processes bits of information.
5:58
Speaker 2: This was process us seeing molecular molecules. But if you
6:03
Speaker 2: drilled down, it had an operating system that was written
6:08
Speaker 2: in DNA. And of course the whole human Genome project
6:11
Speaker 2: was to understand our operating system. But because I came
6:16
Speaker 2: from the world of microbiology, I was super interested in
6:19
Speaker 2: understanding the microbial operating system. As the genome project was
6:23
Speaker 2: going on, we were getting more and more data. We
6:26
Speaker 2: were starting to see how the code was put together.
6:29
Speaker 2: And after the genome project was completed and the number
6:33
Speaker 2: of bacteria had been sequenced, it was time to move
6:36
Speaker 2: away from reading the genome and start thinking about how
6:39
Speaker 2: do I program it? How do I start writing?
6:42
Speaker 1: Is there a biodiction? I mean, can we separate some
6:45
Speaker 1: of these areas as bioeconomy and biosecurity and biodefense and biotechnology.
6:51
Speaker 1: How should we be thinking about it with AI, which
6:55
Speaker 1: we're obviously going to get into in this age of AI,
6:59
Speaker 1: How would you define where we are now?
7:02
Speaker 2: Because I've always worked at the intersection of computers and theology.
7:07
Speaker 2: For me, it's more of an evolution, but it's still
7:10
Speaker 2: very early days. For example, in twenty twenty four, the
7:14
Speaker 2: Nobel Prizes were awarded to researchers that we're using AI
7:18
Speaker 2: tools for interpreting the structure of proteins. That was Demis
7:22
Speaker 2: Acidys and John Jumper at Google deep Mind, and David
7:26
Speaker 2: Baker got the other half of that Nobel for designing proteins.
7:30
Speaker 2: But proteins are the smallest components in cells. You can
7:33
Speaker 2: think of as basically the biological equivalent of the transistors
7:37
Speaker 2: or other components in a computer, and so we're really
7:40
Speaker 2: going bottom up. But those tools are now intelligent. Just
7:45
Speaker 2: in the last five or six months, we've seen the
7:48
Speaker 2: first AI designed viral genomes, and we can build AI
7:53
Speaker 2: tools to design, for example, bacterium, but we can't easily
7:59
Speaker 2: build and tests that yet. So we've kind of got
8:01
Speaker 2: more computational power on the design side. Then we have
8:06
Speaker 2: automation and technology to do the compile and boot up,
8:10
Speaker 2: if that makes any sense. But these two fields are
8:13
Speaker 2: completely AI is going to take over biology and allow
8:18
Speaker 2: us just to start to program biology by clearly defining
8:24
Speaker 2: our intentions. Think of it as vibe coding for the biology.
8:28
Speaker 1: Should everyone listening to this be freaked out by that?
8:31
Speaker 1: Or how do you think about it? Because some people
8:34
Speaker 1: might say, oh, yeah, you know the machines are going
8:36
Speaker 1: to create that's where this is going to go the
8:39
Speaker 1: wrong direction. But I guess we are probably similar minded,
8:43
Speaker 1: you know, in that now it'll facilitate, it'll help us
8:47
Speaker 1: maybe get to some real big answers faster. But I'm
8:51
Speaker 1: not that fearful of it, of the unknown. But how
8:53
Speaker 1: would you help people understand it, what the role will be.
8:57
Speaker 2: Every technology has a good and a bad side. Every
9:01
Speaker 2: technology is dual use. You know, a fok can pick
9:05
Speaker 2: up your food, it can poke out an eye. So
9:07
Speaker 2: the technology itself is agnostic, it's how we use it.
9:11
Speaker 2: Most people, well, you know, ninety nine point nine percent
9:15
Speaker 2: of people are going to use it in a positive way,
9:18
Speaker 2: or in a way that is economically positive. Let's put
9:22
Speaker 2: it that way. They're going to try and do something
9:24
Speaker 2: productive that earns the money, that helps their family, that
9:28
Speaker 2: solves a problem. They're going to use it in a
9:30
Speaker 2: productive way. And they will always be people that will
9:33
Speaker 2: use it maliciously. They'll find some weak point, they'll scam somebody,
9:37
Speaker 2: they'll target something, or they want to build a weapon
9:40
Speaker 2: specifically not for defense, but for offense. You can't blame
9:44
Speaker 2: the technology in that. You can only look at the
9:46
Speaker 2: people and how they're using it. There is the potential
9:49
Speaker 2: for accidents. Some people might be trying to do something
9:52
Speaker 2: good and go oops, though some of those oops can
9:55
Speaker 2: be quite dangerous. My big fear in biology personally, and
9:59
Speaker 2: then people have different is that someone will use these
10:02
Speaker 2: tools maliciously to create a pandemic classifvirus.
10:05
Speaker 1: You know, I guess the real question around that is,
10:10
Speaker 1: for all the advances that have been made, why aren't
10:14
Speaker 1: we closer to cures or answers in some areas? You know,
10:19
Speaker 1: you'd think this combination of computers plus biology would have
10:24
Speaker 1: us at the point where things would go fast. We'd
10:28
Speaker 1: have answers. Why don't we have them all yet?
10:32
Speaker 2: I think we just need to be a little patient.
10:34
Speaker 2: First of all, we started genomics kind of by saying, oh,
10:38
Speaker 2: let's go sequence the human genome, which is the most
10:42
Speaker 2: complex genome on the planet, and you think about it,
10:45
Speaker 2: and so we kind of started at the top, and
10:48
Speaker 2: now we're working down and applying the knowledge that we
10:52
Speaker 2: got from sequencing and continuing to analyze. Human biology is
10:57
Speaker 2: very slow to translate to humanity because we have rules
11:02
Speaker 2: and regulations about what we can do to people and
11:05
Speaker 2: what companies can do to people. So that's why cures
11:07
Speaker 2: are slow. But when it comes to the technology for
11:11
Speaker 2: being able to program biology, that is growing exponentially. Again,
11:17
Speaker 2: the stuff that Ajin or Genentech was doing thirty years
11:20
Speaker 2: ago is available to grade school kids today. Yeah, and
11:25
Speaker 2: there it might think of it as toy biology or
11:28
Speaker 2: playful biology or lab based biology, but these tools are
11:31
Speaker 2: extremely powerful. Remember, it takes ten years to get a
11:34
Speaker 2: new drug through the drug development process. It's extremely expensive,
11:40
Speaker 2: and that limits the number of things you can do
11:43
Speaker 2: but we are seeing drugs that have been computationally designed
11:46
Speaker 2: going through that process. And just in the last couple
11:49
Speaker 2: of weeks, one of the companies that I've been tracking
11:52
Speaker 2: for years that does design of drugs using these AI
11:56
Speaker 2: based computational systems, called in Silico Medicine, just went public
12:01
Speaker 2: in Hong Kong and was hugely oversubscribed. And you know,
12:05
Speaker 2: it is one of the first generation of new drug companies.
12:09
Speaker 2: That's kind of AI first, none of the other drug
12:12
Speaker 2: companies or AI first. But that's changing.
12:15
Speaker 1: And why not, Like I guess they didn't adopt it
12:19
Speaker 1: or are they going to have to catch up to it,
12:21
Speaker 1: because some folks have said to me, you know, run
12:24
Speaker 1: these companies, we don't use AI at all purposefully.
12:29
Speaker 2: The entire AI can work at every single facet of
12:33
Speaker 2: drug development. This takes me back to about a year ago.
12:35
Speaker 2: I had a contract with a major pharma talking about
12:39
Speaker 2: how AI could be used in their drug development process
12:42
Speaker 2: in clinical trials. And the short version of that presentation
12:47
Speaker 2: and the research I had done for it was it
12:50
Speaker 2: basically sped up the report generation. They really weren't using
12:54
Speaker 2: it effectively in any other aspect of clinical trials. AI
12:59
Speaker 2: can be us at the very start of the drug
13:02
Speaker 2: development process and support it with every step of the
13:06
Speaker 2: clinical trial and research process.
13:08
Speaker 1: So AI first.
13:10
Speaker 2: Companies that are starting to emerge will have a huge
13:13
Speaker 2: advantage over the classical drug development paradigm. And I'm starting
13:17
Speaker 2: to see that in cancer. We can go into that
13:20
Speaker 2: if you like, but there's a reason for them.
13:23
Speaker 1: Yeah, I do want to go into it. Yes, I'm
13:25
Speaker 1: certainly invested in those areas. Then it matters to me personally,
13:30
Speaker 1: what are you seeing now on the cancer front.
13:33
Speaker 2: So my argument with cancer has always been we've been
13:36
Speaker 2: going about it all wrong, and that's because no two
13:40
Speaker 2: cancers are identical. Thirty years ago we called it breast cancer,
13:43
Speaker 2: prostate cancer. That's just calling it by tissue of origin,
13:46
Speaker 2: which is determined by pathologists looking at the cell types.
13:51
Speaker 2: Now that we can sequence cells and really inspect their
13:55
Speaker 2: code and how their code is operating what we call expression,
13:59
Speaker 2: we can deeply, molecularly analyze the cancer and what the
14:03
Speaker 2: first thing you find out is no two cancers are
14:05
Speaker 2: the same. Meanwhile, the drug development process is geared to
14:09
Speaker 2: making one size fits all medicine. It's a complete mismatch
14:12
Speaker 2: between the problem and the tools we have to solve it,
14:16
Speaker 2: and that's why cancer hasn't really been cured. You can't
14:21
Speaker 2: you can't do a one size fits all cure for
14:23
Speaker 2: something that is individualized. But the most exciting thing I've
14:27
Speaker 2: seen in the last few years is there's been groups
14:29
Speaker 2: now that are taking the entire drug development process for cancer,
14:33
Speaker 2: starting with diagnostics of the cancer cell and making it individualized,
14:38
Speaker 2: starting with one person's cancer, deeply analyzing it and then
14:42
Speaker 2: using that to develop custom therapeutics and vaccines, so both
14:47
Speaker 2: passive you know, training your body to recognize the cancer,
14:50
Speaker 2: as well as actively targeting and eliminating the cancer and
14:54
Speaker 2: building that entire pipeline for the single individual. And in fact,
14:58
Speaker 2: it's becoming cost effective to do that because some of
15:02
Speaker 2: the most expensive modern medicines one size fits all or
15:07
Speaker 2: slightly personalized around key targets and cancer, are getting up
15:10
Speaker 2: to the multimillions of dollars. But this entire individualized process
15:15
Speaker 2: is already at about the same price, and it gets
15:18
Speaker 2: cheaper because most of these processes are digital. Everything digital
15:23
Speaker 2: gets faster, better, cheaper. The main accelerant is that now
15:27
Speaker 2: you're not doing phase clinical trials to reduce risk. You
15:30
Speaker 2: could basically have approval to work with a particular patient
15:34
Speaker 2: before you start.
15:35
Speaker 1: So cells are living computers and DNA is a programming language. Well,
15:39
Speaker 1: everything sounds like we're going in this direction in healthcare.
15:43
Speaker 1: Become engineerable. Can we engineer at all?
15:47
Speaker 2: Yeah? I think we start knocking off diseases faster and faster. Again, cancer,
15:53
Speaker 2: I think will become a managed disease you can't ever
15:57
Speaker 2: eliminate because cells are going to corrupt and start to
16:00
Speaker 2: all the time. I think infections with bacteria again. People
16:04
Speaker 2: have worried about antibiotic resistance. I think we're in the
16:07
Speaker 2: golden age of antibiotics. We don't need to just use
16:11
Speaker 2: a few chemicals anymore. We have so many new programmable
16:15
Speaker 2: moieties to chase after a particular bacterium. They're clonal, so
16:19
Speaker 2: much easier to kill than a cancer cell, which will
16:22
Speaker 2: have a spectrum of degradation inside a particular individual. We're
16:27
Speaker 2: also starting to see this end of one approach emerge
16:30
Speaker 2: with rare diseases and children where there's just been no
16:33
Speaker 2: treatment at all. But now through advanced diagnostic technologies, we
16:37
Speaker 2: can get a deep understanding of a particular problem pretty
16:41
Speaker 2: much at birth. This is really fun and it just
16:44
Speaker 2: keeps going on from there. Our genomes are three billion
16:47
Speaker 2: bits of code. How long will it take us to
16:50
Speaker 2: be able to write eukaryotic genomes like our own at
16:54
Speaker 2: the outside. I think it'll take twenty years. I think
16:57
Speaker 2: it could happen much faster than that.
17:00
Speaker 1: So you got to like get there, you know, you
17:02
Speaker 1: gotta get calent. If we can engineer DNA to write
17:05
Speaker 1: the book of life, should we be doing this?
17:07
Speaker 2: I think absolutely yes. Like I've never seen prohibition work
17:12
Speaker 2: in any area, you know, from alcohol to nuclear technologies.
17:17
Speaker 2: I think we just have to use it wisely and productively.
17:20
Speaker 2: Life is the most powerful technology we have. Like growing
17:25
Speaker 2: something is logical manufacturing right like it self assembles, And
17:30
Speaker 2: if you can do it just by writing the program, wow,
17:34
Speaker 2: that's huge. So I believe that biotechnology is combined with
17:38
Speaker 2: AI technologies, is a superpower and we're just learning how
17:42
Speaker 2: to unlock that. And yes, there are real risks, but
17:46
Speaker 2: there are huge opportunities in every aspect of our lives
17:50
Speaker 2: and for taking better care of our planet because we've
17:53
Speaker 2: been extremely successful as a species, but we've been using
17:57
Speaker 2: pretty crude technologies to generate that success, and we know
18:01
Speaker 2: that they're not sustainable. It's changing our atmosphere. We're using
18:04
Speaker 2: too much of this and too much of that. We
18:06
Speaker 2: collect all these waste products that can't be broken down yet. Yeah,
18:11
Speaker 2: by programming, biology can fix all that and take us
18:14
Speaker 2: to a cleaner, sustainable, infinitely recyclable world. And I think
18:18
Speaker 2: if you can get there in your thinking, we can
18:21
Speaker 2: go and create it.
18:22
Speaker 1: So you co founded it way back in twenty sixteen.
18:26
Speaker 1: Genome project, right GP, Right, a community that is writing
18:30
Speaker 1: genomes from scratch? Is that still going? Is that still rolling?
18:34
Speaker 1: And what the fuck is it? Exactly?
18:37
Speaker 2: So? Remember I'm old, So I remember when the Human
18:41
Speaker 2: Genome Project was launched. Right when the Human Genome Project
18:44
Speaker 2: was launched in nineteen ninety, it had taken six years
18:48
Speaker 2: of planning, convincing Congress to release the money, and you know,
18:53
Speaker 2: Jim Watson was at the head of it like it
18:55
Speaker 2: was a big deal, and that was just to read
18:57
Speaker 2: our genome. The thing that I recall most about that launch,
19:01
Speaker 2: working in bacterial genomics was we hadn't sequenced to bacterium yet,
19:06
Speaker 2: the smallest cellular life. We tend to be very human centric,
19:11
Speaker 2: So after the Human Genome Project was completed, I expected
19:15
Speaker 2: us to take that energy. It was the biggest science
19:18
Speaker 2: project the world had ever done, scientists had ever done.
19:21
Speaker 2: It was kind of the large Hadron Collider of biology.
19:26
Speaker 2: I expected that energy to stay cohesive and move from
19:30
Speaker 2: reading to writing, let's start programming biology.
19:33
Speaker 1: Now.
19:33
Speaker 2: That didn't happen. What ended up happening was the field
19:36
Speaker 2: split into omics, proteomics, metabolomics, glycomics. Like a thousand omics
19:42
Speaker 2: blossomed on that foundation of reading the human genome, and
19:46
Speaker 2: by twenty ten, seven years after the close of the project,
19:51
Speaker 2: there was still no effort to talk about let's build
19:55
Speaker 2: a foundation for synthesis and programming, even though the field
19:59
Speaker 2: of synthe biology was kind of bubbling away under the radar.
20:03
Speaker 2: And so I wrote an essay for the Huffington Post
20:06
Speaker 2: at the time saying, you know, asking the question, is
20:09
Speaker 2: it time for another genome project, this time around writing
20:13
Speaker 2: at least that's locked into the history books. But it
20:16
Speaker 2: really didn't catch on, and by twenty fifteen I was
20:19
Speaker 2: getting so frustrated. I proposed that we create a new
20:23
Speaker 2: human genome project, the Human Genome Project.
20:26
Speaker 1: Right.
20:27
Speaker 2: That got us some traction, some funding to launch, and
20:30
Speaker 2: it went out the door in twenty sixteen, with the
20:32
Speaker 2: bank was a top one hundred paper of twenty sixteen,
20:35
Speaker 2: and we had a lot of energy around that. What
20:37
Speaker 2: we didn't have is a big funder that would come
20:39
Speaker 2: in and write a billion dollar check. And to my chagrin,
20:44
Speaker 2: the board decided to drop the human part of the
20:47
Speaker 2: Human Genome Project Right, which totally made media attention nosedive
20:53
Speaker 2: and made it impossible to find a big funder. So
20:56
Speaker 2: short version is since COVID where we went virtual. Since then,
21:00
Speaker 2: we've kind of parked it. I'm the chairman. I maintain everything.
21:03
Speaker 2: It's all there.
21:04
Speaker 1: It's all parked.
21:05
Speaker 2: And what's emerging now with AI, with increased ability to
21:10
Speaker 2: program with better synthesis and assembly tools and a UK
21:14
Speaker 2: effort that has emerged called sin HD Synthetic Human Genome
21:19
Speaker 2: to build a human chromosome, It's time to reactivate that genome.
21:23
Speaker 1: Project right aims to engineer cancer resistance, viral immunity, transplantable organs.
21:29
Speaker 1: Which breakthrough. Do you think is closest to reality that
21:33
Speaker 1: you could see come through? Is it the cancer one?
21:36
Speaker 2: We don't need to write a whole human genome to
21:39
Speaker 2: cure cancer. You just need to build essentially bioweapons for
21:43
Speaker 2: cancer cells. And that's typically going to be small things
21:47
Speaker 2: that are going to be bioavailable. I think the thing
21:49
Speaker 2: that is really going to cause the Human Genome project
21:54
Speaker 2: right to take off is building human cell cultures that
21:59
Speaker 2: are resis distant to infection, because we use human cell
22:03
Speaker 2: cultures a lot to make products or do research, but
22:07
Speaker 2: it's really hard to grow human cells in a dish
22:11
Speaker 2: and stop them from being infected from just the viruses
22:14
Speaker 2: that circulate around us. But for me, it's the compiling technology,
22:19
Speaker 2: the synthesis and assembly.
22:20
Speaker 1: Just as we.
22:21
Speaker 2: Start to put more effort into writing a human genome,
22:24
Speaker 2: the synthesis and assembly technologies will improve, and that will
22:28
Speaker 2: make it easier to start programming bacteria, starting to program
22:33
Speaker 2: single celled organisms like Yees et cetera, et cetera. So
22:36
Speaker 2: I think just the core technology is really the most
22:39
Speaker 2: exciting short term thing to come out of this, as
22:42
Speaker 2: well as the AI design tools.
22:44
Speaker 1: Are you talking to Kennedy and doctor Oz and some
22:48
Speaker 1: of these guys about this yet or have you been
22:51
Speaker 1: asked to?
22:52
Speaker 2: Will you? Oh, it's definitely reaching them. I haven't gone
22:55
Speaker 2: to health in Human services that should be fairly obvious,
22:58
Speaker 2: but yeah, I go and try and message this to
23:01
Speaker 2: as much as I can and get the word out
23:03
Speaker 2: to people so that they can start figuring it out
23:05
Speaker 2: for themselves and putting the resources into these technologies. I'd
23:09
Speaker 2: love to see the US have the leadership in global biosecurity.
23:13
Speaker 1: So you've advised the FBI and the United Nations on
23:16
Speaker 1: these issues. What's keeping you up at night?
23:20
Speaker 2: For me personally, it's viruses, And that's because viruses. Look,
23:24
Speaker 2: there's dangerous proteins and venoms and toxins, et cetera, but
23:28
Speaker 2: those don't self replicate, so you know, you'd have to
23:31
Speaker 2: have a manufacturing plant and a dispersal system, but viruses
23:35
Speaker 2: just go from host to host. And we know that
23:38
Speaker 2: a flu or a cold can spread globally in just
23:40
Speaker 2: a few weeks. So viruses right now, for me are
23:45
Speaker 2: the biggest threat because and I was much more optimistic
23:48
Speaker 2: pre COVID. I was like, Yeah, let's yeh. Viruses of
23:52
Speaker 2: a lot of really beneficial characteristics as well that we
23:55
Speaker 2: use for vaccines and gene therapies. So I was very
23:59
Speaker 2: pro virus. I still am, but clearly through COVID and
24:04
Speaker 2: post COVID, the threats are much better understood and the
24:09
Speaker 2: lack of tools for monitoring encountering viral infections has been demonstrated,
24:14
Speaker 2: so we really need to work on it.
24:16
Speaker 1: They may be the biggest risk, but we can mitigate
24:19
Speaker 1: that risk.
24:20
Speaker 2: I think so. By and again, at every level of
24:22
Speaker 2: the architecture, you look for people who are malicious. You
24:25
Speaker 2: build in constraints in the design tools that flag for
24:28
Speaker 2: anomalous or malicious behavior. You definitely have the checkpoints at
24:33
Speaker 2: synthesis and assembly. You have checkpoints in the testing and
24:37
Speaker 2: refining processes in the automated labs. And then you still
24:41
Speaker 2: need sensors everywhere in the world, which we should have,
24:44
Speaker 2: you know, in the same way that we track weather
24:46
Speaker 2: and we track the launches of nuclear missiles, we should
24:50
Speaker 2: have biosensors that are cheap and everywhere. That's something I'd
24:53
Speaker 2: really like to see. And for me, that's just a
24:56
Speaker 2: I call it the universal swab. You know, like right now,
24:59
Speaker 2: people get sick, and you know, it happens all the time,
25:02
Speaker 2: whether it's a cold or a flu or rspee. And
25:04
Speaker 2: today there's no universal swab, but a sequencer, a cheap
25:08
Speaker 2: automated DNA sequencer, say the size of a phone would
25:12
Speaker 2: be amazing. You just swab stick it in and it'll
25:15
Speaker 2: tell you every virus or microbe on that swab. That
25:19
Speaker 2: to me is a technology that should exist now, it'll
25:25
Speaker 2: be in every medicine cabinet beside our thermometer, you know.
25:28
Speaker 2: So that would be really cool, and I think we
25:30
Speaker 2: can get there if we just put a little effort
25:33
Speaker 2: into it.
25:33
Speaker 1: So before we go to the fun questions, your team
25:36
Speaker 1: at Autodesk synthesized the virus, and did I understand the
25:40
Speaker 1: Museum of Modern Art acquired it as the first engineered
25:44
Speaker 1: organism and their collection. How did a synthetic virus end
25:48
Speaker 1: up in an art museum? Is it art or science
25:51
Speaker 1: or both?
25:51
Speaker 3: What?
25:52
Speaker 1: And why?
25:53
Speaker 2: Yeah? So at Autodesk, Autodesk makes computer aided design tools.
25:59
Speaker 2: At the time when I was working with them, they
26:01
Speaker 2: were also very interested in three D printing, and I said,
26:05
Speaker 2: well that's great, but you know, a cell is kind
26:07
Speaker 2: of the three D printer that today's three D printers
26:11
Speaker 2: will eventually morph into their multi material they can make
26:14
Speaker 2: more three D printers anyway, So we were playing at
26:17
Speaker 2: that intersection and I said, look, I want to three
26:20
Speaker 2: D print biology, so can we do it? We had
26:23
Speaker 2: design software to build a virus. What we needed was
26:28
Speaker 2: the compiler, and it turned out around that time, this
26:30
Speaker 2: was twenty fourteen, some of the DNA synthesis companies said
26:35
Speaker 2: that they could start making viral sized genomes complete, like
26:39
Speaker 2: just send them the order, they'd send me back the
26:41
Speaker 2: genome as a special project. It was still more than
26:45
Speaker 2: what they were typically offering to researchers. Short version is,
26:49
Speaker 2: we took a genome that had already been synthesized in
26:52
Speaker 2: two thousand and three by Craigvenor. It's a viral genome
26:55
Speaker 2: that only infects bacteria. It's absolutely safe for humans. You
26:59
Speaker 2: can think of it as it was almost an antibiotic.
27:01
Speaker 2: It had already been made synthetically. But the Craig Venture spurup.
27:06
Speaker 2: He's an eminent genetic scientist. His partner was ham Smith,
27:10
Speaker 2: who just died late last year but already had a
27:13
Speaker 2: Nobel Prize. It was ham Smith and Craig and the
27:16
Speaker 2: rest of their team at the J. Craig Venture Institute
27:19
Speaker 2: that synthesized this genome back in two thousand and three,
27:22
Speaker 2: and they said it took them two weeks to do it.
27:25
Speaker 2: They didn't put any costs. They published the paper. So
27:27
Speaker 2: I said, let's do that here at Autodesk, So we
27:31
Speaker 2: got a researcher that had studied that virus. They downloaded
27:35
Speaker 2: the virus genome from GenBank, the public database of genomes.
27:39
Speaker 2: He corrected the errors in the genome in that public file,
27:44
Speaker 2: and then we sent it to all these DNA synthesis
27:46
Speaker 2: companies and said just make it. You received back little
27:49
Speaker 2: tubes of DNA code, and then we put that into E.
27:54
Speaker 2: Coli bacteria and we showed that yes, some of these
27:57
Speaker 2: genomes were viable, and we took pictures of what they
28:01
Speaker 2: call a plaque assay. It's a lawn on a petrit dish.
28:04
Speaker 2: It's a growth plate. It's a lawn of E. Coli
28:06
Speaker 2: that gets dead spots wherever the virus booted up and
28:09
Speaker 2: killed the cells. So it's kind of like if you
28:11
Speaker 2: overfertilize your lawn in places it kills off the grass.
28:15
Speaker 2: So it's kind of like that. It's called a plaque assay.
28:17
Speaker 2: So we took those photos. It hit the news, which
28:20
Speaker 2: was kind of hilarious. Anyway, the curator at the Museum
28:23
Speaker 2: of Modern Art reached out to us and said, we'd
28:26
Speaker 2: love to have this organism as part of our collection,
28:29
Speaker 2: so we packaged everything up. We didn't send the virus.
28:32
Speaker 2: We sent the code, we sent the pictures, we sent
28:35
Speaker 2: the process, we sent the story, and it became part
28:38
Speaker 2: of the collection. So, as far as I know, it's
28:40
Speaker 2: the first synthetic organism ever in the Museum of Modern.
28:44
Speaker 1: Art in New York. Well, wow, it's like, you know,
28:47
Speaker 1: a new art movement.
28:49
Speaker 2: It won't be the last.
28:50
Speaker 1: It's the new cubism right. Anyway, we always like to
28:54
Speaker 1: end with a few fun questions. What a great conversation.
28:57
Speaker 1: We could go obviously on for hours, but there'll be
29:00
Speaker 1: more to come. It says nothing to do. Well, maybe
29:03
Speaker 1: it does with all the things you've been talking about.
29:06
Speaker 1: What's the best vacation you've ever taken?
29:09
Speaker 2: Oh, my god, the best vacation that. No one has
29:12
Speaker 2: ever asked me that. By the way, I've never been
29:15
Speaker 2: a big vacation guy because my work and my life
29:18
Speaker 2: aren't separated. I keep authors hours or podcaster hours.
29:21
Speaker 1: You see genomes everywhere, Yeah, I I do.
29:25
Speaker 2: Every time I look at something living, I just look
29:27
Speaker 2: at it like code.
29:28
Speaker 1: Oh my god, I must drive you crazy.
29:30
Speaker 2: No, not really, It's just the headspace I live in.
29:33
Speaker 2: But my favorite vacations are beach vacations. I love going
29:36
Speaker 2: and playing in water. I love boogie boarding, I love
29:40
Speaker 2: just laying in the sun and reading a book. Those
29:42
Speaker 2: are the best, it is true rest. I love being
29:45
Speaker 2: by the ocean. I love the sound of waves. I
29:47
Speaker 2: could do that pretty much full time.
29:49
Speaker 1: So what album is the soundtrack of your life? If
29:53
Speaker 1: there was one album and you can't say Genesis, well.
29:57
Speaker 2: You know, I actually have to say, it's Peter Gabriel's
30:00
Speaker 2: Secret World, Secret World Live. I saw that concert live.
30:04
Speaker 2: I love that album. I've probably listened to it a
30:06
Speaker 2: thousand times, and it is there's something that's rewired in
30:12
Speaker 2: my brain that if I play that album, I will
30:15
Speaker 2: fall asleep. I've heard it so many times I know
30:17
Speaker 2: every note. It just completely lulls me into relaxation and sleep.
30:22
Speaker 1: Well, I'm going to use that instead of ambient. That
30:24
Speaker 1: sounds way better.
30:26
Speaker 2: Just listen to it a thousand times.
30:28
Speaker 1: Yeah, yeah, I'll try that. What's something you want to
30:31
Speaker 1: get real honest about? Which you know we're a get
30:34
Speaker 1: real podcast. Is there something you want to get real
30:37
Speaker 1: honest about with us? Yeah?
30:39
Speaker 2: So this is what I've been working on. I am
30:42
Speaker 2: absolutely confident that the programming of life is taking off,
30:46
Speaker 2: it's off the runway.
30:47
Speaker 1: It is going.
30:48
Speaker 2: It's just going to keep going faster, better, cheaper. I
30:51
Speaker 2: love that. But what I've been thinking about now more
30:55
Speaker 2: and more is the other end of the spectrum about death.
30:58
Speaker 2: Right now, I'm thinking about how do we have more
31:00
Speaker 2: life cycles. I know that we're finite. Anything biological is finite.
31:06
Speaker 2: But I've been watching all this interest and investment in
31:09
Speaker 2: health and longevity, which is great. Like that's such a
31:13
Speaker 2: different mindset than when I was a kid.
31:15
Speaker 1: Totally.
31:15
Speaker 2: I don't think we're doing it right yet, Like this
31:18
Speaker 2: should just be baked into the health system at a
31:20
Speaker 2: very low level. We should be completely scanned and monitored periodically,
31:26
Speaker 2: you know, by our doctor's head to toe. That being said,
31:29
Speaker 2: we are going to die. But I am fascinated by
31:32
Speaker 2: the idea of backing up people today that just a
31:35
Speaker 2: blood sample properly preserved and give you the option for
31:40
Speaker 2: a completely new life cycle through human cloning, which is
31:43
Speaker 2: not available yet. But we've been doing the same thing
31:46
Speaker 2: with animals. It's all merging together with de extinction Colossal,
31:51
Speaker 2: the company that has been de extincting wooly mammoth and
31:54
Speaker 2: dire wolf, and says they're going to do the Dodo
31:56
Speaker 2: and others. That's cloning and editing technologies. They just acquired
32:01
Speaker 2: yage in Pets, which is the largest pet cloning and
32:05
Speaker 2: agricultural animal cloning service in the world. They do horses
32:09
Speaker 2: and other animals as well, so that now it's all
32:12
Speaker 2: become one big cloning company and editing. That is huge
32:16
Speaker 2: because now I'm starting to see the path that one
32:20
Speaker 2: day will do the same thing for humans will become
32:22
Speaker 2: comfortable enough with this technology that just a blood sample
32:26
Speaker 2: properly stored will give you the option to having a
32:30
Speaker 2: twin brother twenty fifty one hundred years from now one
32:33
Speaker 2: thousand years man, you could have GM version one, two, three, four,
32:37
Speaker 2: five in perpetuity.
32:38
Speaker 1: Oh wow, I hear you on all this and it's
32:42
Speaker 1: fascinating and probably its own podcast. Kay, what do you
32:45
Speaker 1: think I'm rivit is? I know this has been yeh,
32:48
Speaker 1: one of your areas that you're most interested in.
32:50
Speaker 3: I also find it fascinating that you're what scares you
32:53
Speaker 3: most or keep you up at night from a biosecurity standpoint,
32:55
Speaker 3: as viruses. I was thinking you'd say something about warfare
32:59
Speaker 3: orical weapons, but really it's what changed in COVID how
33:03
Speaker 3: we see the power, the deadly power of viruses, which
33:06
Speaker 3: is striking to me.
33:08
Speaker 2: Yeah, you know, when I was younger, nuclear weapons were
33:11
Speaker 2: a big thing that you know, that's pretty horrific, and
33:14
Speaker 2: of course if it actually escalated into global thermonuclear war,
33:18
Speaker 2: that would be pretty bad. But those are superpowers. We
33:21
Speaker 2: have no control over those things except for who we
33:24
Speaker 2: vote for in some ways. But a virus engineered with
33:28
Speaker 2: the right characteristics, the long enough latency where it didn't
33:31
Speaker 2: show any would say asymptomatic, with the right effects disability
33:36
Speaker 2: or death, it spread globally in just a few weeks
33:40
Speaker 2: and affect billions of people, and you wouldn't even know
33:43
Speaker 2: it until it kind of happened, because we don't have
33:46
Speaker 2: the tools and technologies to track just the viruses circulating
33:49
Speaker 2: around us today, even in public spaces. So that to
33:53
Speaker 2: me is the big risk factor today, potentially as many
33:56
Speaker 2: casualties as nuclear war. But with technology jeez, that are
34:00
Speaker 2: available today by small groups, that to me is the
34:04
Speaker 2: big risk factor. Personally, I just worry. I've made it
34:08
Speaker 2: now to my sixties without major problems, but I know
34:10
Speaker 2: that we're going to see more decline and eventual of death,
34:13
Speaker 2: So I would love to see more and more effort
34:17
Speaker 2: go into health earlier in life.
34:20
Speaker 1: Yeah, it's changing. Look, that's what this whole podcast is about.
34:23
Speaker 1: Early often prevent the event, and that's the key. So thanks.
34:28
Speaker 1: I hope this inspires some of my audience to go
34:31
Speaker 1: faster and do better. And I really appreciate you spending
34:37
Speaker 1: this hour with us.
34:38
Speaker 2: Thank you, yes, thank you, you really appreciate it.
34:43
Speaker 1: Hey, everyone, thanks for joining me on the Get Real podcast.
34:46
Speaker 1: You know, I hope you feel a little healthier hanging
34:48
Speaker 1: out with me.
34:49
Speaker 4: You know, it's going to be a lot of fun.
34:52
Speaker 4: Passing this along to others. Please subscribe below, Please share.
34:56
Speaker 4: I'm excited not just to talk about healthcare a lot
35:00
Speaker 4: of other fun topics. It's about making healthy. Talk about
35:04
Speaker 4: healthcare is not a lecture.
35:07
Speaker 1: This is supposed to be fun and look forward to
35:09
Speaker 1: spending more time with you in the future.