Founder of IndieBio
What I want to do is talk to you about something really interesting to me in my career arc, that's led me to the adventure capital side of the world.
I also want to teach you to be always asking the bigger questions about what design can do, and about designing science itself. Just a quick background, I did work for a decade at IDEO, where I learned really deeply about the design process, and I think one of the biggest things I found there was that as designers, you design something and then you give it to the client, who would take it and come out with it looking completely different, which sucks. After a while, though, I actually learned that it's not that they suck, it's that they have constraints that we didn't consider as designers.
One of the things that I always was thinking about was: how do you find those other constraints? That led me to understanding how you design a business, alongside designing the product.
Of course, once you start doing that, you're one step away from actually doing a startup, which is what I did next.
I built with my wife a company called Starters, which is a fitness app to help people get started on their road to fitness, and that was an amazing experience that helped me to see how fast you could have an idea, execute it, get it into the marketplace, and get thousands of people in lots of different countries to tell you how helpful that was in their lives. That got me empowered to start thinking about how else to scale design.
I left IDEO to join an adventure capital fund called SOSV, where I found early stage investing to be extremely similar to designing. You are working with small teams that don't have to take your opinion. They are working on hard problems that are building products and businesses against a timetable, which is the burn rate. That was a natural fit for me, and I had a great time.
The question was, what's the focus?
I have a background in genetic engineering as well, so I found the time was right for trying something around science.
I'm partially talking to you about humanity's looming crisis, which deals with the world population over time. There's been a huge explosion in the population through the period of a few hundred years. When you extrapolate the population out, that will double again another two generations.
That brings up a really big point, which is: How are you going to deal with double the number of people on the planet, and the same amount of resources? We're already seeing a growing gap between the rich and poor. I think it's going to be really hard to understand what the world will look like in two generations of more scarcity. So there is a looming crisis out there, and maybe we don't have to deal with it. But, I have two young kids now, and they will certainly have to deal with it. The point is, biology is accelerating.
It's accelerating faster than Moore's Law, and in doing so, we're able to understand, or can control, the fundamental force of life, which is evolution. Biology is a technology unlike any other that we've had so far. It's a technology that can actually help with scarcity problems because we can do things around efficiency. We can do much more with fewer resources. I'll explain that a little bit more. So, what does this have to do with designers?
Well, design is a tool kit that scientists can use to go faster, and I think that's one of the biggest things that I've found in what I've been doing for the past couple of years, in investing in biotech startups. There is this wall between academia, which is discovery based, and industry, which is application based. Traditionally, you get the academia professors who pull out their discovery and tell a graduate student to go out into the industry and make that happen.
Then you get this degree of separation between the inventor of the technology, and the implementer of that technology, and things don't always work. With design, we could empower and we are empowering, technical founders to build companies themselves. They are not one degree separate or two degrees separate from the core technology, but actually able to build it on their own.
So, how do we actually design science to do so?
Science is a process to understand nature at its base. This is the scientific method. It follows what we all know, right? Make an observation. Think of a question. Create a hypothesis. Build something to test the hypothesis, or do some research to test the hypothesis, and develop a theory and then recycle it. It is a 10 to 20 year discovery cycle, it builds on the research of others, and we are doing this for the understanding of the world around us. I've been talking about design process and explaining it to clients for a decade, and by the end of my design-focused career, I started drawing it like this. If you boil down all the circles, all the ways it's ever been described, I see this simply as: You learn something, and create something, and you keep doing that over and over again. That's all it is. You could slap other things into it, but really you are just creating and learning. And so, design and science are actually two sides of the same coin. They're doing the same thing. You just have different tool sets, and somewhat different goals. Discovery versus application. Really, though, you're doing the same thing.
So for me, I found a really nice translator between what scientists are doing to build products, and what designers are doing to build products. There are certain things that scientists just don't have in a tool set that they learn in their PCs and post-docs, which is talking to people, testing certain assumptions, super rapid iteration, and understanding human friction, because humans aren't necessarily always part of the problem, or the equation in scientific inquiry. So here is all the theory. It all is true, but how does it actually work in practice? Luckily, I've been able to build a laboratory for this, a thinking called indy-bio. It's an early stage seed accelerator. We fund companies for a quarter million dollars. We give them a full lab. They have four months to de-risk their business. I sent this to UCSF institute last week, and it's wide open. What do you mean four months? How do you do anything in four months? Well, I think the interesting thing is it's reframing what is possible and how you do it.
So, we've funded a bunch of companies all over the map of the biotech space. Just for you guys, I thought it would be cool to extract four principles of design for science.
I'll give a couple of examples of what I'm talking about. First is: Focus on the problem, not the solution. This seems pretty obvious, but it's not. Here's a good example. Everyone in the world is trying to make an artificial kidney right now. Every scientist in regenerative medicine is trying to make artificial kidneys. It's an extremely big problem.
Right now, everyone is thinking: This is a kidney, and this is the function of all the cells, so let's take cells and rebuild the kidney from scratch. We found Martez, the CEO of Kidney, who is a materials science guy, and he approached the problem very differently. He saw it as this: People that have kidney failure need to go to dialysis every day. If we can remove that need, then they have a free life, just like everyone else. They may not have a kidney, but they otherwise would be exactly the same. So he, from a material science point of view, created a device that is implantable in the body, that is in essence a tiny dialysis machine. He reframed the problem for himself, and had a vastly different solution than every other lab in the world working on artificial kidneys. The first implantation of that device was put in a pig. It was demonstrating that it produced urea. That was done within four months, based on prior work, and was a big milestone for the company. Geltor is another good example for understanding your customer. For every designer here, this seems obvious. However, it's actually not so obvious all the time who your customer is, or what is the actual problem or friction that that customer is facing. Geltor is a company that makes collagen in bacteria.
With collagen, normally you have to melt down horse noses, and hooves, and all the cartilaginous parts of animals. That gives you Jell-O, and all the lovely things. These guys can say, "Okay, well we could take the collagen protein, right?". In the piece of DNA that codes for that, you could stick into ecoli bacteria, and have it spit out tons of collagen, without ever having to harm an animal, or even grow it up and feed it, and all of those things that you need to do for putting the cost into that.
They went out and talked to their customers, and what they learned was that it's not the collagen that they needed to replace.
Collagen is good, but there are issues. For instance, it is in gel caps, so there's a problem if vegetarians are eating those. The world's biggest gel cap maker is in India, and they were the first ones to call Geltor, wondering how soon they could get the gelatin delivered. What they're doing is taking the sequence of proteins, and replacing a few amino acids here and there, to give you different functional properties of the collagen.
So, it's shinier or glossier for one application, or has a lower melting point for another. By going out and talking to the bakers, and all these people, they were able to diversify their product line off of what seemed like one single product. Another one is Product Directed Discovery. This one is another obvious one, but for scientists you're used to discovery. Why does it work? Well, sometimes you don't need necessarily to know why, you need to just make sure that it does work. Strunga is a company that we invested in, that is making a very rapid test for foodborne pathogens. Taking what normally requires three days to culture, and turning it into three hours.
They create an example of a team with fantastic science in the lab, showing that it's working all the way down to one cell per cubic centimeter. We wonder where it's going to be used. Well, it's been used in a factory, where some dude is swabbing a side of a beef in a slaughterhouse, with blood everywhere. And they want to know what the product is. How is someone actually going to use this? So they went and said they needed the swab. That little red swab is a good example. How does it work in terms of using the reagents and everything like that? So, they swab it, and they're like, "Oh wow, the foam holds onto the bacteria, it doesn't let it go." So now they're doing all this research on different foams on swabs. It goes to show you. You have to find all your constraints, your constraints aren't just the science in the laboratory. So, a design approach really helped them get to a product that was viable, much quicker on a lower cost. Then finally, finding friction with business models. None of this matters unless you can make money doing so, otherwise you're out of business. Here's a company called Mendel. They use artificial intelligence to match human clinical trials for cancer immunotherapies, and other therapies, to patients' medical records. They're using an AI and an LP to read all of the entire medical record and match it to a clinical trial, which is a very hard task. Who's going to pay for that?
How does that business actually work? So, one of the big things for them was talking to enough users and customers and everyone to understand what that business model in the end looks like.
So now, they can provide the business for free, and have pharma pay for the biomarkers that they are going to discover in getting all this genomic and outcome data in one place, which is very hard to do. Those two things are normally separated by a wall, and through their service they are able to bring it together. So, that turned a company that was a pass, into: Wow, okay, that can actually change the way we go about looking for data. So, we've had a lot of great results in doing this experiment. I think the next experiment is to figure out how to scale what we're doing. So, over the next 20 years, we're going to see fields blow up based on the advances of biology. Cellular agriculture is a big one.
There is a company called Memphis Meats. They're making animal muscle tissue in vats without ever having to grow an animal. That's their actual chicken, deep fried southern chicken, which was just tasted by the Wall Street Journal, who had a big article about them yesterday. With gene augmentation, we're talking again about gene therapy. This will absolutely change and challenge a lot of the things we talk about every day. What does it mean not just to change genetic diseases that are hereditary, but choices I could make, like changing my eye color, or things like that? Well, as we understand the genetics of things, we'll be able to make those types of decisions, and then the question is: should we?
N= One Healthcare. Like snowflakes, no two tumors are identical, no two diseases are identical. No two people are identical. So, right now we do large scale clinical trials because we're looking for solutions that match most people. If you're an edge case, that is unfortunate. In the long run, we're going to have: you aren't the edge case, you are the only case. That is going to require a redefinition of the FDA clinical trial process. Consciousness and Machine UX. We're starting big frontiers understanding consciousness. This is a company called Conic that we funded, that's using human neurons that are grown in a matrix, and then grafted to a microchip to do simple computation, to sense the molecules.
It flew a drone towards TNT gradients as a demonstration. Finally, there's all this talk of going to Mars and the moon. How are we going to actually do something like this?
Well, it's going to have to happen in biology. How do you mine the side of a mountain? Well, we're working on finding companies and companies are being built around bio remediation. This is being able to put bacteria on a hillside that leech the metal ions out of that hill, and then collecting it. There's got to be new ways of transporting our technologies and building them into life, rather than necessarily taking hard, big pieces of machinery and things like that.
So, the future is rather interesting. We live in interesting times. I think the next two generations are going to really be living in deeply interesting times. So, thanks for listening.