Hacking the genome with Crispr

So, shout out to Janine. So a little bit about my background. So my name is Kathy. Once again, I'm a biotech and healthcare entrepreneur. I've had a pretty unusual journey.

I first started my scientific journey when I was really young, at 14 years old. I started working at university labs. I published my first paper when I was 16 years old. And then when I was 18, I became the youngest founder of a biotech company that was VC-backed. So that was my first company, Renomics.

And then I dropped out of University of Toronto to be part of the Thiel Fellowship, which is when you get $100,000 to drop out of school for two years. And then afterwards, I started a company called LockBio, which is sort of like an online digital health platform where our clients sell prescription medications, telehealth consultations, etc. And most recently, I joined Cold Spring Harbor Labs as part of their board of directors. Cold Spring Harbor Labs is probably one of the most prestigious labs in the world where they discovered DNA, and eight Nobel laureates live there currently. So that's kind of the work I do between healthcare and biotech.

My first company was in the genomic space, and I'm also working on a gene editing project now, which is something that's really interesting, and I'll get into it afterwards. And I also want to give a shout out to Leo here, who I met on this trip. Leo has helped me with setting up the experiments and also finding plans, et cetera, and just being very helpful in general. So give everybody a clap for Leo. So let's start with the genomics industry.

I want to talk a little bit about Moore's Law. So this is a Moore's Law graph about semiconductors. We see that the energy efficiency of computers has doubled every 1.5 years over the last 60 years, and that kind of follows this trend of what makes an innovative technology be very efficient and scalable. This Moore's Law also applies to the cost of the human genome for sequencing.

And so as you can see here, earlier in this millennium, And so as you can see here, earlier in this millennium, one sequence human genome used to cost $100 million to do. Now it costs less than $1,000. So what this represents is that there's a massive opportunity to better read our DNA, and not just our DNA as humans, but also the DNA of animals and plants. And there's a lot that we can do with that data, whether it's reading it better for diagnostics and prevention of diseases, or we can also now edit them, which is now writing our own DNA or writing the DNA of organisms. And one of the things that we're going to do today and tomorrow is we're going to gene edit a real organism.

It's a plant, it's not gonna be anything crazy, but of course if there's interest we can always scale it up to animals and other cool things in the future. So this is another example of the applications of what happens when you can gene sequence really cheaply. So this is an example of using the BRCA gene, the detection of the BRCA gene to prevent and diagnose the early onset or preventing breast cancer and ovarian cancer in women. So if you have a mutation in BRCA1 and BRCA2 that's known to cause disease, a.k.

a. pathogenic, then you're able to prevent it much sooner so that's one of the applications of genetic testing another application maybe some of you guys have heard of this is embryo gene testing so that means you can actually test the genes of your embryo to make sure that they're not going to be carrying diseases and then of course there are always some very I don't know, controversial but also exciting use cases where it can test for features that you want to see in a future kid. And of course, you can get into all sorts of realities where you can edit and change the genomes of the future generations or future animals that would exist in the ecosystem. So this is another visual example of genetics being used in a natural way. So this is like the GFP protein.

This is naturally observable and seen in jellyfish. And it's a bioluminescence that you can actually use CRISPR to put into the genomes of other animals and make them glow-in-the-dark to make them have the same protein, the GFP protein, and characteristics of the jellyfish. So here you can see that you can do it in fish, flies, worms, plants as well. You can actually buy some glow-in-the-dark plants and fish. There's a company called Glowfish, G-L-O-fish, that just makes GFP fish, and they actually make tens of millions of dollars a year just by selling GFP fish, which is actually not hard to make.

We actually have some really cool experiment kits here that some of you might be able to do later in the month, that puts the GFP protein into E. coli, so bacteria, and you can make the bacteria glow in the dark because you're putting the gene from a jellyfish into the bacteria. That's going to be a little harder than the plant one, but we're going to start with the plant one, see how people feel, and then we can do some more fun and complicated stuff like that. But those are the cool, visible, easy applications of gene editing, but it can really go anywhere from here. You know, if you can just imagine, you can take the genes that encode for, let's say the horn on a narwhal or rhino, it can take those genes and put it on a horse and it can actually make a unicorn.

And that's how it would work. You know, we can make any reality happen because we now understand the genome much better than before and we can also have the ability to rewrite the genome by inserting pieces of the genetic code from other species into other species where it doesn't really belong, but, you know, we'll see what happens. That's part of the project I'm working on now, which I'll talk to you guys about in a bit. A little bit more about the genomics industry. So we just talked about the technology, some simple applications, some more, you know, serious applications, and some fun applications.

But where we are as an industry is pretty early. I think this is one of the biggest challenges in the genomics space. You know, we're taking a very innovative technology and we're applying a very antiquated playbook to that technology by pushing it into, you know, drug discovery. Like, we're trying to make gene therapies where, you know, we have not yet found a proper and safe way to deliver it for a lot of these gene therapies. And, you know, we're doing a lot of testing for genes that, you know, there's a lot of VUSs, variants of unknown significance.

So there's a lot of data problems. There's a lot of issues with kind of putting the new technology in an existing playbook and just kind of forcing it to happen. That's why insurance doesn't cover, like healthcare insurance in the U.S. doesn't cover a lot of the genetic tests anymore.

They cover BRCA1 and 2, but not a lot of the other genes. So it just prevents the growth of a really impressive technology. What I'm hoping here is, what I'm hoping will happen in this session, but overall in a group like this, is for everybody to feel like gene editing is something that they can have an intuition about and actually have ideas about and then feel like they can actually do something about it. Like I don't think it should be something that's locked up in a lab with you know PhDs and academia and grants and pharmaceutical companies all the time. I think this is now a technology that should be seen as something that belongs to the people because we're all made out of biology and biology surrounding all of us.

And I think the opportunities are huge. I think it's an over $1 trillion opportunity if we're able to really reimagine reality and the ecosystems around us, redesign how forests, agriculture, animals behave, even humans, whether it's disease prevention or new medicines, new types of animals. Those are all things that can happen once we really have a good grasp of this technology. And there's gonna be so many creative uses of this, even, you know, for example, luxury pets, you know, who doesn't want a unicorn or, what's another one, jackalope, you know, those are really cool mythical animals that never existed until we can actually now create them for the first time as humans. But it's not easy building in bio.

I think one of the reasons why, you know, when I was in the Teal Fellowship, you know, Vitalik, you know, built Ethereum and people built cool, you know, OYO rooms. Those are all software applications or even a little bit of hardware. But no one really took off in the biotech space because it's just so hard to enter the space as a newcomer, as a young person, as someone with a lot of creative ideas because you have to get lab equipment, you have to have access to sterile facilities. A lot of times you have to have a PhD or above to be able to lead a lab with a research focus that you find interesting. And of course, there's a lot of mundane structures like the funding, publishing, other capital incentives that prevent real innovation.

But I think that's all about to change. As you guys are seeing here, we can actually do a gene editing experiment in the middle of Thailand randomly. You know, we don't have to be confined to our computers just coding applications all day. We can actually be doing hands-on experiments and changing physical realities. And this is where network states or pop-up cities, I use it interchangeably, but Janine always corrects me, so I don't know what the right term is.

Yeah, so this is where I think it's really interesting. What does biology look like in a network state or in a pop-up city? How can those two ideas really merge? I think we're going to see a very small example with a simple gene editing experiment, but what can we really escalate that to, and how do we scale it up to really interesting experiments that will benefit all of humans, all of the humans that are part of the experiments, network states, or just around the world. And one thing to really notice here is I think that gene editing in biology is an especially interesting area to focus on because it's the centralizable.

In the past with deep tech in general, it's something that's been very centralized. If you were to build a nuclear plant, nuclear weapons back in the day, you would have to have a very centralized facility. Now really anyone can have a lab, anyone can get access to CRISPR, anybody can get access to cells, DNA, order DNA online. My first company was making variant libraries for pharma companies, synthetic biology companies, basically selling DNA. So you can really buy this stuff online.

You can really buy all the materials you would need and just start gene editing stuff. So that's why it's really decentralized and quite interesting. Biology typically had the characteristic of high technical risk and low