Ep 11: Network Effects In TechBio (NFX Masterclass)

SPEAKER_1 (0:00)

You're listening to episode 11 on Network Effects and TechBio, which is the final episode from the Network Effects Masterclass, here on the NFX Podcast. Biology is the most advanced technology on Earth, and in this episode, general partner Omri Drory explains how Network Effects are helping TechBio companies cure diseases, fight climate change, and tackle some of the biggest issues facing humanity today. If you enjoyed the audio version of the NFX Masterclass on Network Effects, be sure to share with other founders and friends, and watch the videos for the full experience at nfx.com/masterclass.

Omri Amirav-Drory (0:32)

Hello, my name is Omri. I'm a general partner at NFX. My background is very scientific. I'm one of the initial scientists founders. I did my PhD in Tel Aviv University, studying hardcore biochemistry. I got the Fullbright Fellowship, went to Stanford for my postdoc. I started a company called Genome Compiler that NFX invested in, one of the initial TechBio companies. Ran it for five and a half years until we got acquired by Twist Biosciences, a platform company creating synthetic DNA. I was a head of corporate development for Twist for two and a half years until they IPO'd. Then I left to start a small fund called TechBio, a $10 million pre-sid fund. And then NFX had invested in my company, invested in my fund. We did Mammoth Biosciences together when I was at Twist, invited me to join them. Initially as a venture partner for Fund 2, but now a general partner for Fund 3 At NFX Bio, we like to say biology is the most advanced technology on earth. Sometimes it reminds me like an alien spaceship that crashed landed on earth, and we're trying to figure out how this gizmo work. It's pretty amazing technology. But there is one technology that is even more advanced in biology, and it's very human. It's entrepreneurship. Because entrepreneurs can imagine the world that it should be, and then are just annoyed that the world today is not as the world that they imagine, and just using their passion and their grit, they can reap a hole in the universe and drug all of us, kicking and screaming to the new universe they imagine. And they are going and trying to solve some of the biggest problems that we have. So our companies are trying to cure diseases, are trying to solve climate change, are trying to produce renewable chemicals and materials. So our civilization will not be dependent on fossil fuels, but will be more sustainable. So that gives you just extra motivation and just joy of finding, supporting, just helping companies grow in this space.

For the past hours, you've been hearing a lot about network effects. So let's take network effects into bio. At NFX, we love to support scientist founders. And Marmouth is a great example for a company where all three founders were scientists. They are obviously brilliant, right? But one way we can help them is to level up their thinking around business and defensibility. All our platform companies are, you know, they have the vertical platform, but they also have the products. So we have the platform and the products build on top of the platform. So Marmouth platform technology is based on novel CRISPR system that you can use to detect any DNA or RNA sequence. And other system that they discover, small cas system, you can use to cure any genetic disease. The great thing about the company is they have unlimited amount of indication and product they can create using that platform. So they can partner some of those indications or they can develop some of those indications. And the more product they create, the more data they have, the easier it is to create new partnership with other pharma companies, and the bigger the ecosystem becomes. So, I met Trevor at Stanford when I was still working at Swiss Biosciences, and I got really excited about what he was trying to achieve. So, I introduced him to my partners at NFX, and he and his co-founders were one of the initial accelerator groups. Then later on, when the paper came out of the Jennifer Donders lab, where they used CRISPR for diagnostic, the ability to detect any DNA or RNA sequence, I got extremely excited and I told Trevor, hey, this is a better IP, this is a better technology to solve the problem you're trying to solve. And he was lucky enough to be able to get the IP out of Jennifer's lab. And later on, two of Jennifer's star students, Lucas and Janice, discovered more system and wanted to start a company. So, we brought all of them together and started Mammoth Biosciences to tackle not just the diagnostic part, but also the therapeutic side. Unlike software where it's very easy to copy Facebook, but it's very hard to copy 5 billion users, in biology it starts with basic science, research, and IP. You need to own the IP, the freedom to operate, in the area you're trying to develop. That's how you start. Once you have that, the more products you develop, the more data you have, the easier it is for you to develop new products. You already learned about the platform network effect. It's more toward the middle of the map, which makes it stronger than others. So we help the founders to realize the power of network effects and how they naturally fit in. So in Mammoth's case, they are developing their own diagnostic and their own drugs, but they also as a platform collaborating with many different companies to help them build on top of the platforms, either diagnostic or therapeutics. And again, because the platform is so wide and you can create so many different therapeutics and so many different diagnostic, one company cannot do it all. That's a power of the platform and especially Mammoth platform. You can collaborate and get a lot of upfront revenues from collaborating with companies for specific products, and then you can use this revenue and all the platform and all the robotics and people and capabilities that you are building in house to develop your own products and go all the way to the market. Traditionally, in bio, a lot of the traditional pharma plays are finding one small molecule that can go after one indication. And it's very binary. It's either work or it doesn't work. You just flip a car to see if it works or doesn't work. The transition from biotech to TechBio, where again, biology is getting digitized, where because it's digital, you can use machine learning automation to make sense of the data and moving from people pipetting in the lab to high throughput automation, allow you to speed the cycle of design, build, test, learn and create products faster. It means that one company with a platform technology, like Moderna and the RNA technology or Mammoth and the CRISPR technology, can create a huge amount of products by themselves and collaborate with many other companies to create many different products for them. And traditionally, you couldn't do that.