SRNG Soaring Eagle Acquisition Corporation

Filed by Soaring Eagle Acquisition Corp. pursuant to

Rule 425 under the Securities Act of 1933

and deemed filed pursuant to Rule 14a-12

under the Securities Exchange Act of 1934

Subject Company: Ginkgo Bioworks, Inc.

Commission File No.: 333-256121

Ginkgo Bioworks, Inc.

Investor Day

June 24, 2021

Introduction / Safe Harbor — Anna Marie

Anna Marie Wagner:

On the call today, we will be making forward-looking statements, which involve risks and uncertainties. We refer you to the Form S-4 that was filed by Soaring Eagle with the Securities and Exchange Commission for further information regarding these risks and uncertainties. We will also be referring today to certain non-GAAP financial measures, including foundry billable revenue net, present value and adjusted EBITDA, that we use in measuring our financial performance. A reconciliation of these non-GAAP measures to their nearest comparable GAAP measures are available and can also be found in our Form S-4.

Anna Marie Wagner:

Welcome to our first Investor Day. My name is Anna Marie Wagner, and I’m the Senior Vice President of Corporate Development at Ginkgo, and I lead our Investor Relations function. We’re looking forward to being able to host you all in person soon, but in the meantime, we’re happy to be able to meet you where you are.

Anna Marie Wagner:

If you’ve been following Ginkgo over the past couple of years, you’ve probably spent a lot of time listening to Jason and I talk about the company. And so today, we wanted to take a step back and introduce you to the broader team, so you have the opportunity to hear directly from our technical and commercial leaders, as well as from our customers. If you’re newer to the story, I’d also recommend you watch our investor presentation from May 11th. It’s posted on our website, and it’s a great primer to the platform and the business model. Today, we’re going to dive a bit deeper, and I hope that by the end of this session, you’ll really feel like you know who we are and you have a better sense of what we really do here.

Anna Marie Wagner:

We’re going to start the day with a conversation with our founders. Somehow after 20 years, they are all still friends and happily working together, and as I’ve gotten to know them, I’ve been really impressed by their totally unique and complementary superpowers that they’ve each developed. Then we’re going to head inside and introduce you to the platform. Barry’s going to take everyone through the foundry and introduce you to some of our automation, software and IT leaders, who help make our scale possible. We’d love to show you the foundry in person though. So if you find yourself in Boston, definitely shoot us a note. Then to complete the review of the platform, you’ll meet Patrick Boyle, our Head of Codebase, who will help you understand what biological codebase actually is and how we leverage it to support our customers. You’ll also meet Claire Laporte, our Head of Intellectual Property, who helps not only protect our platform and the IP we’ve created, but also works to ensure our customers have strong IP so they can successfully commercialize their products.

Anna Marie Wagner:

Once you’ve gotten an introduction to the platform, we’ll introduce you to some of our customers across industries and from small startups to large corporations. You’ll meet Jennifer Wipf, our Head of Commercial for Cell Engineering and Ena Cratsenburg, our Chief Business Officer, who together help identify and structure new collaborations and ensure customer success., We’ll also highlight how we’ve enabled new companies to start on the platform, helping bring together the capital, strategic partnerships, and of course, access to our platform that accelerates innovation. You’ll meet the leaders of Motif, Allonnia and the newest company building on our platform in the personal care space, who are building businesses in remarkably different end markets, but have leveraged Ginkgo’s platform since day one.

Anna Marie Wagner:

We hope that by now you’re excited about the potential for biological innovation in the world, but alongside that potential is an imperative to treat biology with care. We’ll feature two segments that help illustrate how we think about this imperative. First, we look at the need for a global biosecurity infrastructure and how Ginkgo thinks about the role of biosecurity in building our business. We’ll also have a conversation about the role of ESG at Ginkgo and in investing more broadly.

Anna Marie Wagner:

To wrap up our prepared remarks. I’m going to sit down with our CFO, Mark Dmytruk to get a financial update and talk about some of the most common questions that I get from investors on our business model, our projections and valuation. We’ll end with a live Q&A, where our team will be available to answer questions submitted on the Open Exchange streaming platform, as well as via Twitter @ginkgo. With that, I’m excited to be able to introduce you to my friends and my colleagues here at Ginkgo. We’ll get started with a conversation with our founders.

A Conversation with Our Founders

Jason Kelly:

I’m super excited about this part of investor day. One of the really kind of secret superpowers of Ginkgo is that we have a five person founding team that’s been working together for 20 years and actually still likes each other. So I thought I would give you all a chance to meet the other founders here at Ginkgo. We would just kind of do a little bit of a wrap session, I guess. So maybe I’ll kick it off so Austin, Reshma you joined Tom’s lab, when was that?

Austin Che:

I joined first in 2001.

Reshma Shetty:

Yeah and I joined the year after in 2002.

Jason Kelly:

So this is at MIT, 2001. How did it happen? What drew you to Tom in the first place? And had you done biology before you met Tom?

Austin Che:

I did not, but Tom’s background also inspired me. Right? He had built a bio lab in the computer science building and had taught himself biology and his vision of programming cells as kind of the next iteration from programming computers really inspired me to learn and get into biology.

Jason Kelly:

Yeah so, Tom, how did that happen exactly? It’s a bit of a strange leap, I would say.

Tom Knight:

Well, so in around 1990 or so I decided that the end of the interesting things happening in computer science was pretty much upon us. I was just kind of looking around and what’s the next interesting thing to do. And we were-

Reshma Shetty:

Because computing was over in 1990, to be fair.

Tom Knight:

Computers yeah. So, I was looking around for the next thing to do. Looking at what was going to be the next technology that was going to be important and sort of looking at how we could make semiconductors and the next generation of electronics with the precision that would be required to work at that scale. And it looked to me like it was going to be chemistry and more specifically it looked like it was going to be biochemistry. So that was a major motivator.

Jason Kelly:

As in biology was going to build the chips.

Tom Knight:

Yeah, that’s right. So they founded-

Jason Kelly:

Was it called synthetic biology at that point?

Tom Knight:

No, we called it cellular computing.

Jason Kelly:

I see. Okay. When did it start getting called synthetic biology?

Tom Knight:

Probably 2003 or so I’m guessing somewhere around there.

Jason Kelly:

When was the synbio war? When did you arrive on the scene?

Reshma Shetty:

I showed up at MIT in the fall of 2002. And I think you maybe had just sort of figured out the name of synthetic biology is an analogy to synthetic chemistry. So the idea is like you use chemistry to synthesize things. We’re going to use biology to make things. And so that’s why.

Barry Canton:

The unique thing that came out of that MIT synthetic biology working group, arguably, was the idea of focusing on the underlying tools and technologies and trying to convert it into a more, like, mature engineering discipline as Tom had seen happen in computers.

Tom Knight:

Yeah. Not just the tools, but also I think a very important aspect of it was the idea of standardization. The idea that you could reuse components that you could design them once and use them many times.

Jason Kelly:

And what today we call our code base. Yeah. Yeah. Then back then was this concept of, “Hey, we had standard parts in other engineering fields from screw threads to computer functions. Why can’t we have them in biology?” Well Barry, your CTO, you head up our technology platform development today. If you look back, what do we have right, what do we have wrong? Right, does it feel like a straight line from MIT to that biology working group to Ginkgo today.

Barry Canton:

Oh absolutely. We nailed it all perfectly.

Jason Kelly:

That’s so laughable.

Barry Canton:

Yeah. Next question.

Barry Canton:

No, that’s really interesting to think about. I mean, I think some general themes have remained really true and we have followed through on those. I’m thinking about approaching the technology from an engineering standpoint has been true. I think bringing to bear the learnings and technologies from other disciplines, whether it be computer science or operations research or whatever else, electrical engineering, I think we have done a good job of bringing all of those themes and concepts into the way that we do our work. Leveraging robotics, leveraging software wherever possible. And you can’t take a tour of the Ginkgo foundries without seeing all that.

Jason Kelly:

That’s a lot of robots. Yeah.

Barry Canton:

There are a lot of robots. I think there were certainly things where we haven’t gotten as far as we would like, and nor has the field arguably. I think it was a helpful way to think about it. I guess more of a meta point there is that it’s probably good for us to be careful about when we use analogies versus when we just are direct about the beauty and complexity of biology as its own thing, rather than trying to fit biology into prior engineering disciplines.

Jason Kelly:

Speaking of sort of the beauty and wonder of biology, right. What got you into it? How did you start with it?

Reshma Shetty:

Well, biology itself, I fell in love with working in a lab at the University of Utah. So Toto Olivera is a professor and he studies these venomous cone snails.

Jason Kelly:

Venomous cone snails. Okay.

Barry Canton:

Beautiful, beautiful.

Reshma Shetty:

They’re amazing. I’ll nerd out for a second. So they’re these little marine snails that live in coral reefs all around the world. And some of them basically spear fish. So they literally have a harpoon that they can spear a fish with and inject it with neurotoxins to paralyze it. Others catch fish with nets.

Jason Kelly:

The purpose of this meeting is to get the public excited about programming biology.

Reshma Shetty:

Well these neurotoxins have now been used as pain relief and other sort of therapeutic drugs and then as amazing tools for neuroscience. But anyways, I just thought these snails were super cool and that is how I fell in love with biology. And then when I met Tom, I realized that we could actually program biology and take the next step. And so that was my journey. Well, Tom, you should talk about iGEM because that was probably the other biggest community building exercise.

Jason Kelly:

What does iGEM stand for?

Tom Knight:

International Genetically Engineered Machine Competition. The teams compete to do something cool, an experimental system that they build over the summer and demonstrate. Come together in November typically or October end of October and sort of impress one another about how wonderful-

Jason Kelly:

So who owns the winning project from the first year?

Tom Knight:

I actually don’t remember.

Jason Kelly:

I do remember cause I was in that competition.

Tom Knight:

This competition idea really worked, I can tell.

Jason Kelly:

It was IT Austin and they had... It was kind of cool. You put down bacteria on a plate, they grew into a lawn and then you would shine light on it. And the ones where the light hits would change color, and so they made the first bacterial Polaroid. It was cool.

Reshma Shetty:

I was a judge at that competition. They deserved to win.

Jason Kelly:

How many teams were in it last year?

Tom Knight:

Oh, I don’t know, 350, something like that. From all around the world.

Jason Kelly:

Yeah, and that’s thousands of students.

Tom Knight:

Huge participation from China and Europe. Maybe even South America.

Jason Kelly:

Yeah. And what I love about it is you go and you tour around and I mean, everybody is so fired up about what they can do in biology. And the beauty of the iGEM teams to me is they have no idea what will or won’t work. And so they try all this stuff and oh surprise some of these things that everybody else would have told them won’t actually do work.

Tom Knight:

Yeah. I think one of the things is they’re early enough in their education that they don’t realize how hard some of these problems really are. And so they’re willing to try things that you and I wouldn’t have.

Jason Kelly:

This feels like us in 2007. All right. That’s what I would say, right. It’s like you just don’t know any better and then you’re like, “Well, at least like if I go off on this journey with people I enjoy being with, it’s not going to be a miserable life, so let’s give it a fricking swing.” And I don’t know that there’s much more to it than that, right.

Tom Knight:

That’s right.

Reshma Shetty:

Naivety is your friend I think.

Jason Kelly:

It’s your friend. Big time. I couldn’t agree more.

Barry Canton:

And lo Ginkgo was born.

Jason Kelly:

Yeah well I feel like that’s the reality. I mean, I guess, yeah. What’d you think when we came in your office, Tom, to tell you about Ginkgo? Do you remember that?

Reshma Shetty:

I mean unnamed company. [crosstalk 00:09:12]. We came into your office and said, “We’re thinking about starting a company.”

Tom Knight:

Yeah, well I think my first reaction was, “Can I join you?”

Barry Canton:

I think an important part of the logic was that academia is great for doing, hopefully blue sky, high-risk research and what we believed at the time was that what synthetic biology needed was engineering, industrialization and things that could better be done in, arguably in a commercial context than an academic context where it’s about publishing papers. And so I think, at least for me looking back, I think that was an important part of the logic about why taking what was essentially the same mission and moving it from an academic context into a commercial context would allow us to do something cool, right.

Jason Kelly:

I felt like that’s always been true about Ginkgo. It’s been sort of a mission, there was a larger mission and goal for it. It wasn’t like, “Oh, I just want to build a company and flip it.” Or anything like that. Very clearly from day one that wasn’t the case with us. And I think the team that’s joined around us as a result reflects that, right. You’re basically buying into, now 500 zealots that want to make biology easier to engineer and are going to keep pushing that for the long run. And I think it starts all the way back at that point in time.

Tom Knight:

I think we’ve always had sort of a long-term point of view. I think, quite a bit longer than a typical company in this space.

Reshma Shetty:

I think by being a mission driven company, we were optimizing on our mission above anything else. Right. And I think that’s what lets you tolerate a lot of pain in the early years. Right. But I mean, so we would do all sorts of crazy things, apply for every grant under the sun just to try to keep things afloat before we sort of really saw traction. And yeah, I think we signed our first few commercial contracts in like 2014. And that’s sort of what led us to then have the confidence to join YC and take off from there.

Jason Kelly:

I think it helped to set the bit of what it means to be a fast growing tech company. I think we have a solid mission fit. I think we had Tom’s long term vision that said, “Look, if we build into this and follow these technology paths, there’s a big thing waiting for you.” And so then if that’s true, you should just grow like a tech company. Right. And that’s what we learned at YC. Right. It was like, if you lean into it and you bet on scale and you have a business that benefits from scale it’ll pay off. So just keep betting.

Barry Canton:

Yeah. It’s interesting. Because I can’t remember when that sort of economy of scale and build scale idea kind of really took hold. Would you date it back to 2014 to YC?

Jason Kelly:

Yeah, because I kind of think that’s when we started seeing the... Well, I don’t know what year it was probably two years later that Tom picked up on the fact that the output of the facility had been tripling in the last couple of years and our costs had been halving. And we started to say like, “Oh, we should own that metric and actually meet it internally.” That was all around that same time.

Barry Canton:

It was around 2017. Definitely not earlier than that, because we had about three years of that sort of [inaudible 00:12:24] progress under our belts. And it started around 2015.

Tom Knight:

One of the things that I think was different about the company also was the idea that we should be building a computer platform for the technology really from day one.

Jason Kelly:

Yeah. There was this realization somewhere along the line that what we needed to do for people is the whole project. We’re going to program a cell for you like we program a computer and what you’re going to get at the end of the day, is like the finished cell. And that suddenly meant we had to do all these things. Once we landed on that business model as being the right business model, the amount of technology and infrastructure that had to be under one roof was daunting. I think our first principal’s view was this is the right product to put out the door if you want to meet the mission of make it easier to engineer biology. Well sell people a programmed cell. Right. And so that felt great. And it just meant we had to build technology for 10 years, right. But-

Barry Canton:

And the other thing that it kind of mandated was that we would have to work on a lot of those projects at the same time. If that was going to be our product well we would need to have a bunch of them. And I think that therein lies the core of the horizontal platform idea. And then what that pushes you to do is to ask, okay, how can I work on diverse projects at the same time? And what does the platform have to look like to do that?

Jason Kelly:

This is the game we’re playing, right? This is how I see it. And I just think it’s new to biotech. Right. I think one of the things about Ginkgos, we’re a little outside the mold of biotech. We’ve taken a lot of lessons from Tom and [Semis 00:13:59], we’ve taken lessons from business models and app store economics and things like that. And we’ll see.

Reshma Shetty:

Well, I think amongst the founding team and the way I describe it to people is like on paper, the four of us, not Tom, but the rest of us sort of look identical. I feel like you could literally swap out our resumes for each other and you wouldn’t know the difference.

Jason Kelly:

That’s accurate, yeah.

Reshma Shetty:

And so I think what’s happened with the founding team is that we’ve essentially speciated over the years. Right? We all started as the same, like, common ancestor. And then it speciated into our own niches in the company. And I think that was pretty key to us sticking together for almost 20 years now.

Jason Kelly:

I feel like we benefit also because the vision is very tight. In other words, it’s a lot easier for us to kind of push in our directions without getting off the rails, in part because all the way back to Tom, it’s been a tight mission for so long. And then having folks then who have that history, going back to the foundation of the field, then managing the company. That is such an unfair advantage.

Reshma Shetty:

But I also think that the trust that we’ve built up over time and that speciation into specialized roles has also extended to the entire leadership team of Ginkgo, right? We operate in a way where we are very comfortable sort of trusting each other, pushing power and responsibility down in the organization. And I feel like we’ve sort of tried to bake that into the culture. And so in the leadership team, it was very natural to bring in other folks and trust them with large amounts of responsibility to make decisions for Ginkgo. Because that’s how we operate with each other. And so it was sort of an additional natural extension of that.

Jason Kelly:

Yeah, well and as the platform scales up, I think it’s just more and more true, right. It’s one of the things I’m excited about, as we’re taking the company public and the company’s getting bigger is just more folks invested in the success of the organization across the whole team. I do think we’re laying the groundwork for that culture and I’m really excited about it. So Austin, you spent a lot of time engaging with other startups in the ecosystem around Ginkgo. How do you think about it? How do you think about what’s sort of coming behind us and how do we engage with them in a healthy way?

Austin Che:

Some of this I think comes back to kind of our painful start, right? Many, many years of scrounging for resources and trying to get started. And, I think our vision of making biology easier to engineer is, how do we not have other startups go through the same pain? And so having gone through that ourselves, we understand sort of what those companies need and how we could provide those services to those companies. And I think it’d be extremely rewarding if we can get to the point where we’re companies are being created because Ginkgo exists. If we are enabling new companies, I think that that would be a dream for me. Yeah.

Jason Kelly:

So it’s been kind of a weird year for biology. A weird year and a half with COVID. And I think there’s suddenly this awareness that biology is powerful stuff, which has maybe been obvious to us. But I think again, people take biology for granted. I haven’t noticed it as much. And so here we’re opening it up. We’re going to make biology as easy to program as it is to program computers. And we’re going to open that platform up so that kids can do it, use it someday. How do we do it? How do we do it safely and responsibly?

Reshma Shetty:

I think this is actually a topic that we’ve thought about even since the very beginning. I mean, if you think back to our days at MIT, we had a lot of conversations about biosecurity, bio-safety. How do we create a community around this technology that ensures that it uses the technology overwhelmingly for constructive purposes? I actually credit Drew a lot for seeding a lot of these conversations, both with us and with the community at large. Right.

Barry Canton:

Bringing in a lot of non-engineers, non-scientists, yeah.

Jason Kelly:

Social science.

Reshma Shetty:

Yeah. We had anthropologists, artists, designers, social scientists-

Barry Canton:

Policy people.

Reshma Shetty:

... policy folks and so I think that’s always been baked into even the origins of the field. And I give Drew a lot of credit for that, but I think now at Ginkgo, as we’re faced with like, “Hey, we have this incredibly powerful platform, we’re potentially going to open it up to start ups, to a broader set of folks, maybe ultimately to kids,” then how do we continue to ensure that it’s used for good, right. And so I think baking in a cultural value, both inside the company and caring how our platform is used is super important because these are not easy questions. Right, part of the reason why I think that that’s how we frame it. Right. We care how our platform is used is we’re not actually saying we have all the answers, we just care what the answers are.

Jason Kelly:

Yeah. And what I’m excited about at Ginkgo is a culture of establishing that across the whole team. Right, because then you end up with ultimately thousands of people caring how the platform is used. Their diverse backgrounds, their ability to sort of help us see what’s coming.

Reshma Shetty:

It needs to be a diverse community. Right. I think we’ve learned from every other technology that if you have just a narrow slice of society, who’s developing and using the technology, then that biases it to only benefit that narrow slice, right? You need a diverse team of people who are building and using the technology. If you actually want to see around all the possible corners and all the way things can go wrong.

Jason Kelly:

And who feel like they own the place so that they make wise choices about what to do with it at the balance of growth and impact. Yeah. 100%. Well I’ll ask sort of, I’d say the number one question I get from investors, which is whether in our lifetimes we will see dinosaurs back. So I’m going to ask for just a thumbs up or thumbs down from each of you on this question right now at the same time.

Barry Canton:

Wait, wait, wait, are we giving a thumbs up that it’s going to happen or that it’s a good idea.

Jason Kelly:

That it will happen. Thumbs up is that we will see that in our lifetime.

Tom Knight:

Something that looks like a dinosaur or literally.

Jason Kelly:

Yeah, it can look like Tom doesn’t need... Yeah, we’re not trying to get too technical here. I’m not trying to get back to-

Barry Canton:

And what about birds? Where are we on birds?

Jason Kelly:

I understand that birds are dinosaurs but everyone knows what they mean when we say dinosaur, it means something to you.

Austin Che:

And breathes fire, is that that-

Jason Kelly:

No, that’s dragons. Also want that. That would be a second one separately. Those haven’t existed.

Barry Canton:

So you want like a green, scaly looking thing that didn’t actually exist, or?

Jason Kelly:

Yeah, I mean, it could have stupid feathers but that needs to be big and it needs to be... People need to-

Barry Canton:

Like a Brontosaurus. You want a Brontosaurus.

Jason Kelly:

Okay, yeah, a Brontosaurus.

Tom Knight:

Do we have to be scared of it?

Jason Kelly:

Yes.

Tom Knight:

Okay.

Jason Kelly:

Big enough that you’re scared. You wouldn’t want to be in a room with it alone. All right.

Barry Canton:

So what is the thumbs up?

Jason Kelly:

Thumbs up means that we’re going to have them. That yes, they’ll happen.

Tom Knight:

In how long?

Jason Kelly:

In our lifetimes.

Tom Knight:

Oh, I don’t know.

Jason Kelly:

Austin’s lifetime. All right. All right, here we go.

Austin Che:

This should be a question of if we’re going to extend our life.

Jason Kelly:

Okay. Don’t go down that route. This is not Silicon Valley all right, we’re in Boston. All right. 1, 2, 3. Yes. All right. Well, the last 20 years have been an absolute pleasure to build this with you. Excited for the next 20 or infinity with Austin. Thanks for the time guys. Thank you.

Overview — Ginkgo 101

Jason Kelly:

I’m super excited for our first investor day here at Ginkgo. I’m going to have a little bit of time with you up here at the front, before we dive into a whole bunch of different elements of the company. I thought I’d use just a moment to give you a little bit of the architecture of Ginkgo and highlight some of the key questions that I frequently get from investors that I think are worth highlighting upfront. The core idea behind Ginkgo is that you can program a cell like you program a computer because it runs on digital code in the form of DNA, right? It’s A, T, Cs and Gs, not zeros and ones, but you can read that code with DNA sequencing and write it with DNA synthesis. If you can read and write code and you have a machine that’ll run it, you can program it.

Jason Kelly:

We’ve known that, you’ve got to hear it, just a fun conversation with me and my co-founders. Yeah, this is an idea that goes back 20 years ago to when we met at MIT and what we’ve had to figure out in the intervening years are both how to build the technology to do that in a way that drives scale and value into the business. Then what’s the right business model? How do you commercialize this idea of compiling and debugging genetic code? All right, so let me drill in a little bit. On the technology side, the number one thing to understand that’s different between computer programming and cell programming is that cell programming is a physical process. In other words, when I compiled DNA code, I literally have to build a molecule like A, T, C.

Jason Kelly:

Those are chemicals. I do polymer synthesis to build that piece of DNA and install it physically into a cell. Well, as a result, we need physical facilities to compile code. It’s not just virtual, like on a computer. You’ll get a tour of our foundry from our platform leads, and you’ll see 200,000 square feet of physical infrastructure, robotics, and automation, and the key business implication of that infrastructure is it improves with scale just like Ford or Intel. The more of it you do, the cheaper it gets. That’s one of the key competitive moats around the business is as our platform gets bigger, we can offer something more valuable to our customers. Then you also hear about it on the data side. As we do more cell engineering, we learn more. You’ll hear from our head of code base about that, how we build up that data asset that also makes us offer a better product year over year to customers.

Jason Kelly:

That is the source of value at Ginkgo, simple as that. Compounding technical scale, how do you harvest that value? We actually spent a lot of time thinking about what is the right business model for this? One of the obvious ones would be, well, hey, use that platform, go make your own products, right? You have this great platform, why don’t you go become a therapeutics company or something like that? A lot of money in the therapeutics industry. One of the things we realized was that would be a mistake because once you pick a narrow window of the products, you end up building a smaller, less general platform. It’s not as good as if you serve everybody and work on everybody’s products. Then importantly, we decided our customers are a lot better at launching products in these markets than we would ever be.

Jason Kelly:

So just in the last three or four months, we’ve done announced deals with Biogen, one of the largest therapeutic biotech companies, with Corteva, one of the largest ag biotech companies, and with one of the largest flavor and fragrance companies in the world. In addition to new deals with startups in the cosmetics

industry and other new small companies, pioneering applications for cell programming, we will never be as good at launching a therapeutic as Biogen or an ag product as Corteva or we have our long historical relationship with Bayer. They are the product developers. What Ginkgo does is we basically provide a common horizontal platform to program cells and take that work off their plate, so they don’t have to have their own scientists doing it by hand at the lab bench. Instead, our robotics and automation, and our data assets are available to them.

Jason Kelly:

Okay, so that sounds good. Good value to the customer improves with scale. How do you make money? The key big, big value capture for Ginkgo is in taking a piece of the value of those products. Think, like, app store ecosystem, right? The big mobile phone companies spend a lot of investment, making a great ecosystem for you to be able to launch an app and make a whole bunch of money as a product developer in their app ecosystem. They take a piece of that pie. Exactly the same business model we have here. We’re going to take a piece either through a royalty on the sale of that drug or that fragrance, or in lieu of a royalty, if you’re a smaller company, we can take equity in the company. That value, that is the long-term value of Ginkgo.

Jason Kelly:

One of the key questions we get is, “How do you think about getting your value to $15 billion? How do you think about just finding the valuation of the company? How is it ultimately going to be worth many, many more multiples on that value in the future?” The answer is the market for cell programs is going to dwarf the market for computer programs. These are the physical goods. Food, building materials, medicines, all of the physical things in our lives ultimately are biotech products and they just don’t know it yet. Getting a small piece of that pie will ultimately really drive the overwhelming majority of the value here at Ginkgo. We do get paid also. We have foundry revenues. People pay us as we do the work for them, but ultimately, the long-term value is actually in that sort of app value capture long-term value share. That’s a key thing for investors in the company to really understand. That’s the kind of investors we’re looking for are people that understand that long-term opportunity for Ginkgo in that area.

Jason Kelly:

Then finally, I’ll mention we’ve been doing more and more work in the area of bio-security. This is something that’s actually really important to me, as our platform gets better and we make it as easy to program cells as it is to program computers. Doing that safely and responsibly requires bio-security. Just like we need cybersecurity for computers, you’re going to need biosecurity for cell programming. What’s fortunate for Ginkgo is it’s actually turning into quite a nice business that’s growing quickly. You’ll hear it from that team as well today. Really excited to welcome you here to the investor day and enjoy the show.

Ginkgo’s Platform: Foundry:

Anna Marie Wagner:

So one of the questions that I get most frequently from investors, once they feel like they understand a little bit about cell programming and what that’s going to do for the world is, “Okay, but what is it that Ginkgo actually does in the foundry? What is the work that you do?” And we figured the best way to help explain that was to just show you directly, to walk you through the foundry. We’d obviously love to have you in Boston in person to walk through, but in the meantime I’m going to ask Barry to take you through a video tour of the foundry and introduce you to some of our leaders across software and automation who helped make what we do in the foundry possible.

Anna Marie Wagner:

He’s also going to introduce you to Patrick Boyle, who’s our head of code base, which incorporates all of the biological data and parts and strands that we use in conjunction with our foundry to enable projects for our customers across the entire cell programming landscape. Barry, take it away.

Barry Canton:

So you’ve already heard a lot today about the foundry, but you may well be wondering what do we mean when we talk about our foundry?

Barry Canton:

Well, first of all, the foundry is one of the key pillars of our platform that we’ve been building at Ginkgo over the last 13 years. And I’m really excited to be able to show you some more of the detail about that today. Ordinarily, I’d love to be bringing you on a physical tour of our foundries and showing off the people, the technologies, the instruments, the robots that we’ve been developing over the past number of years, but today I hope to still be able to bring you inside the foundry as best as we can and expose you to all those incredible technologies.

Barry Canton:

You’re also going to get to hear from some of my wonderful colleagues. You’re going to hear from Kristen Tran, who is our head of automation. You’re going to hear from Jamie Cho, who is our head of software. And you’re also going to hear from Dave Treff, who is our head of DevOps and IT. You’re going to hear about how all those different disciplines and technologies come together to power the Ginkgo foundry.

Barry Canton:

One of the first questions that we always get from folks is, what is our foundry and what do we do in there? That’s a very reasonable question because foundries and this concept of programming biology is foreign to almost everybody who hasn’t been doing it for 20 years like the team at Ginkgo. So I’m going to start there and let’s talk a little bit about, well, what actually happens in our foundry and what is the overall process of programming biology.

Barry Canton:

For us, it typically starts with an interaction with a potential partner or a customer where we jointly develop the concept of a cell program that will help that customer make a new product or a better version of an existing product. Through those conversations, we’ll develop a specification for the cell program that we’re going to build with them.

Barry Canton:

Once we’ve reached that agreed-upon specification, the work is turned over to our cell designers who will refine and develop the concept and the specification of how we’re going to make that cell program. And they’ll continue to develop that using code base from our collection, as well as nature’s code base, the cells and genetic assets that are out in nature. Our designers will bring those different pieces of code base together to develop a detailed design. We put all of our best learning accumulated over many cell programs into those early designs. Once we have those detailed designs that are specified at the level of DNA sequences, all in a computational manner, those designs are handed over to our DNA synthesis and our build teams. Their task is to take those conceptual and computational designs and turn them into reality in the lab.

Barry Canton:

So that starts typically with DNA synthesis, where we print out the new DNA sequences that our cell designers have come up with. Once we have those new DNA sequences, our build teams will take those DNA sequences, put them into the genomes of cells that we want to work with. We will finally, at this stage of the process, use sequencing technology, DNA reading, in order to make sure that we’ve made all of the right modifications to the DNA inside the cells that we’re working with. Now, we have a real life cell in the lab that is the physical instantiation of our designer’s concept.

Barry Canton:

Now the next question is, how does that cell perform? To answer that question, we hand those newly programmed cells over to our test teams who bring together a wide array of different capabilities that we use in order to understand how those new cell prototypes that we’ve been building perform. Do they meet the customer’s specifications? Do they nearly meet the customer’s specifications? Do we still have a lot of work to do? So those test teams use technologies like mass spectrometry, liquid chromatography, high throughput screening, next generation sequencing in order to understand what’s happening inside the cells that we’ve built and to measure the performance of those cells.

Barry Canton:

Typically, we will find that some of those prototype cells perform really well and some perform so-so and some don’t perform well at all. All of that information, across many different designs, will integrate together and use it to come up with a new round of designs. And then we will iterate through that process of designing, building cells, testing how they perform until we meet the customer’s specifications. And a lot of the technology in our foundry is oriented towards making that process as efficient as possible and investing in the tools and technologies that allow that process to happen faster and with a higher probability of success than has been possible previously.

Barry Canton:

So when you see inside our foundries and when we’re able to bring you physically to our site at Ginkgo, what you’re going to see is, first off, what looks kind of like a lab, but also a little bit different from a normal lab. That’s because, for our foundry to be efficient, what we’ve had to do is start with a conventional lab and then bring a lot of concepts in from manufacturing, from operations research, in order to build scalable, high throughput, automated processes that allow us to more quickly and effectively program sells for our partners.

Barry Canton:

So what you will see in our foundry is not the typical row after row of benches with a scientist working at each bench. You will see some of that in our foundries, but what you will see more and more of is sophisticated instrumentation, robotics, liquid-handling instruments, and a wide array of sophisticated and complex machinery and instrumentation that we use to amplify and multiply what our scientists are able to do in our foundry.

Barry Canton:

We bring the best in robotic and software automation together with the unique skills and insights that humans have in order to be able to program cells more effectively, higher probability of success than would ordinarily be possible. So what you will hear in the labs, what you’ll hear in our foundries is you’ll hear relatively loud hum of equipment of robotic arms, of instruments moving liquids back and forth. You’ll hear that hum of activity that is largely consisting of robots and instruments scaling up and powering the work of our foundries.

Barry Canton:

It’s essential to our foundry that we be able to run many, many designs or prototypes through every step of that process in order to minimize the overall timeline of a project or a cell program to develop a cell that meets the customer’s specifications.

Barry Canton:

So not only do we want to be able to look at thousands or tens of thousands of prototypes for every cell program, we also want to be able to work on many cell programs at the same time. Today, we work on tens of cell programs in the Ginkgo foundry at any point in time. In the future, we want to be able to work on hundreds of cell programs at any given time.

Barry Canton:

So when you put all of that together, you find you have a complex multi-step process of designing, building and testing cells. We want to be able to do that process at scale with tens of thousands of prototypes within each program and we want to be able to do many programs at the same time. The result of that is that scale, logistics, operations, the throughput of our foundries becomes really, really important. Those robotic and software automation, paired with what humans can do, means that overall our foundry can do way, way more work and way, way more cell programs than would be possible by people alone.

Barry Canton:

So this really leads in nicely for you to hear from Kristen Tran, our head of automation, who’ll tell you about all of the incredible robotic automation that we use throughout the Ginkgo foundries.

Kristen Tran:

At Ginkgo, we try to automate as much as we can. We start with small scale automation, really accessible stations for scientists and engineers to walk up to, really easy for them to start using. Once we actually start scaling up, we can actually start stringing these operations together seamlessly on an integrated work cell, which really allows us to really take off on that scale. It really allows the scientists’ output to increase 10X, 100X, 1000X, and really that’s our goal. We want to maximize that. We want to automate as much as we can and really whatever they’re going to let us do, we’ll try it.

Kristen Tran:

Instead of having a scientist go from station to station, we have this centralized robotic arm, that’s going to handle all of the samples and it’s also going to record everything. And it’s going to produce that valuable data that we need for our cell programs and for our code base.

Kristen Tran:

What my team and I do as automation engineers, we like to look at the physical activities people are doing in the lab. We’re engineering cells, and that requires a lot of precise handling of samples. What my team does is we take these activities in the lab that scientists are manually doing, such as pipetting, and we actually make a custom integration, so we integrate these in a work cell. With that custom integration, not only can we really control the timing and the precision of the activities, but we can actually track everything within our software so that all of the data can be collected and all of that can be reused for future engineering projects.

Kristen Tran:

For automation, in addition to automating manual processes that scientists would normally do with a bench, we can actually go beyond human capability and miniaturize certain reagents and certain reactions. So an example of this is with our acoustic liquid handler that can actually dispense nanoliter droplets of liquid.

Kristen Tran:

With one of our core processes, we were actually able to miniaturize reaction 50X. In addition to that, it increases the speed and the output. So our scientists are able to produce hundreds to 1000X more output that they can trust and that they’re able to go back to and reflect and really iterate on their process and on their design.

Kristen Tran:

I think there is a misconception that we’re trying to replace the activities that certain people do in the lab, but the way that we look at it is we really want to augment the ability of a scientist. We want to increase their ability to perform experiments in the lab. We want to give them the peace of mind that it’s going to be done faithfully, that it’s going to be done with high precision and high quality. And with these different scales of automation, they can actually increase their output and create more valuable data for them to iterate on their process.

Kristen Tran:

Something that’s really special about Bioworks 5 is in addition to the large scale that it provides, there’s actually all of this really interesting new technology where we’re able to sense the success of each operation. So you can tell whether or not an operation failed, was successful and record it.

Kristen Tran:

We use different types of sensing technology, including acoustics, light scattering sensing, light proximity sensors and pinhole cameras. And what’s really great is we implemented this in Bioworks 5, in our latest facility, but we can actually take that technology and apply it to all the different scales of work that we do throughout the foundry. So all of this technology that we’re developing in Bioworks 5, we always have an eye on like, “Well, where else can we leverage this? What else can we automate? Where else is this going to be valuable for us?” Really that’s how we develop our automation. We are always thinking about it in like, what are these new tools and how can they be even more helpful to Ginkgo and to our scientists?

Kristen Tran:

A lot of resources went into building Bioworks 5, but something that’s really unique about the automation at Ginkgo is that we have our own custom integration and software integration. So we work really closely with our colleagues in digital technologies, we have a great relationship, and what we do is we try to think how can we leverage all of that technology that’s already out there and make it really useful for Ginkgo and leverage it in a flexible way to apply to multiple programs?

Kristen Tran:

Our infrastructure, through custom automation and custom software, can actually be applied throughout the foundry. It can be applied for different cell programs, it can be applied for different organisms, and it’s kind of amazing the diversity of scientific processes that can be performed on the same set of infrastructure. I think we’re only really able to do that because we have this in-house development team, both on the automation side and on the software side, as well as the DevOps side. We all work together really collaboratively to make sure that that integration is as seamless as possible and we’re constantly thinking about how can we scale? How can we be more efficient? We always have to pair that with flexibility, which is always quite the challenge, but it’s a really fun challenge.

Kristen Tran:

All of our engineers at Ginkgo are really interested in being the ones that solve that problem and it’s been pretty amazing to see what the teams are capable of. We get to work really collaboratively with our engineering partners to create new technology, to create new capabilities on existing robotics. And in addition to that, sometimes we even have custom partnerships where we’re able to create something truly unique for Ginkgo. Bioworks 5 is a really prime example of this where we leverage existing high throughput manufacturing technology, but we’re able to apply it to the synthetic biology space.

Barry Canton:

The process of designing DNA, which must seem like a very abstract concept, really involves using computers to go from ideas down to detailed DNA sequences that can be thousands or tens of thousands of letters of DNA long. Because those DNA sequences are very long and because we’d like to be able to design many of them at the same time, we’ve built a suite of design tools, computational design tools, that our designers can use in order to come up with the best possible DNA designs for every cell program they’re working on.

Barry Canton:

When you see our designers working, what they’re really doing is interacting with software tools, many of which are proprietary, that allow them to stitch different pieces of DNA together, computationally, in a quick and efficient way, almost as easily as you can drag and drop objects in a software package. But those objects are actually DNA sequences that we are subsequently going to print out.

Barry Canton:

So once we’ve done that computational design process, which really looks almost like an architect or an engineer interacting with computer-aided design, then we move over into the lab.

Barry Canton:

DNA printing, again, that’s a very abstract concept. Well, does it look like a desktop printer that you might have at home or what does it look like? Well, it’s a lab operation, but it uses increasingly advanced sophisticated technology in order to make the operation of printing DNA as cost-effective and reliable as possible. So we work with partners such as Twist Bioscience to use their proprietary technology for printing out, literally using inkjet printer technology, to place individual DNA bases together in the right sequence so that we get the new DNA sequence that corresponds to what our designers have developed in our computer aided design tools. So DNA printing really looks like a very, very complicated printer.

Barry Canton:

Thereafter, once we have short-printed DNA sequences of say 100 bases long, we next need to stitch those 100-base sequences together into a thousand or a 10,000-base sequence of DNA that encodes a gene for a protein or a set of genes for a metabolic pathway. And that operation, stitching those short pieces of DNA together, is again, a lab operation. It looks like a lot of liquid handling, it looks like a lot of moving small volumes of liquid from one source to a destination and mixing lots of different liquids together, and so that’s a process where we rely very heavily on liquid handling automation to scale the amount of DNA molecules that we can build at the same time for many cell programs.

Barry Canton:

Once we put that DNA into the cells, and that process, again, really just looks like a liquid handling process, we take a little tube of the cells, we take a little tube of DNA, we mix some of the DNA into the cells, we treat them with some heat and some chemicals and that helps the cells take up the DNA inside them and integrate the new DNA into the genome of the cells. Once we have that operation done, we then grow the cells. So we start with a tiny tube with just a handful of cells in it that have the new DNA and we allow those cells to grow so that we have millions or billions of copies of that newly programmed cell. Those cells grow in either small bioreactors that look like miniaturized versions of fermentation systems at a brewery, or it happens in plates that have hundreds of individual wells in them so that we can grow many different populations of cells or many different prototype cells at the same time.

Barry Canton:

Once we have those cells grown up, we have lots and lots of cells, then the next step is often to sequence them, so DNA reading. That’s the process by which we read all the DNA that’s in the cell and make sure that we’ve put the right DNA into the cell. That’s an operation that happens on very sophisticated instruments. The machine streams data to our proprietary databases and our data lake here at Ginkgo, and that data contains all the DNA sequences that are found in those cells. That’s, again, a computational or a digital process.

Barry Canton:

Once we know that those DNA sequences are right, then we move on to measuring the performance of those cells. What that looks like is taking the cells, observing them via instrumentation that can say, looking at the levels of particular molecules or identifying particular molecules that are being made by those cells. And really allow us to look inside the metabolism of the cell or the behavior of the cell so that we can understand how its performance matches up to what we expect.

Barry Canton:

So when you see our testing operations in our foundry, what you’ll generally see are collections of instruments that are 24/7 taking small samples from a culture of cells and chemically analyzing those samples to understand what’s in there so that we can understand how those cells are performing.

Barry Canton:

You’ll see in the Ginkgo foundries, there is an enormous amount of work happening across many different cell programs at the same time. All of those physical operations, all that work that’s happening is very hard to track unless you have really good software tools to manage the operations of the foundry and also to collect all of the data and metadata that is being produced across all of those operations and bring all of that data into a location, like a database, and into a format that our scientists can analyze what’s happening and decide what to do next.

Barry Canton:

We’ve invested an enormous amount of energy and time over the last 12 years building proprietary software tools that are completely critical to the operation of our foundry so that we can operate at a scale that would be hard to operate it otherwise and at a level of quality and sophistication that would be impossible without dedicated software tools that were built specifically for our operation. And who better to tell you about that than our head of software, Jamie Cho?

Jamie Cho:

The software we build is uniquely tailored to Ginkgo’s foundry’s needs. Our software team has a lot of the same traditional skills that you see on other software teams, they know how to program in Python, and Ruby, Rails and react and all of those skills. But what’s really special about our team is we are all passionate about biology. In fact, our mission is to make delightful software that makes biology easier to engineer.

Jamie Cho:

Ginkgo’s unique focus on engineering biology at scale means that we have to build a software platform that can handle that level of scale. We have powerful workflow systems that allow us to generate and execute really complex laboratory workflows for actually manipulating that DNA and transforming it into organisms. This is a seamless process that the software enables. And likewise, we have built a platform so that it can actually pull data automatically from instruments and analyze that data, feeding it back to the beginning of the design build test ferment cycle.

Jamie Cho:

So our laboratory workflow software actually keeps track of everything that’s happening inside the lab. And a lot of these workflows are automated such that when instruments are processing the data and actually return the data, we’re able to analyze it automatically and refer it back to the originating samples that generated that data, and this all happens seamlessly.

Jamie Cho:

Integration of all of those different components is really important when you’re dealing with data sets as massive as the data sets that we’re generating every day. This degree of integration really enables us to keep track of what’s going on and then feed that information back into the current design build test ferment loop. But what’s even more exciting is because we can keep track of all of this stuff, we can also apply it to future programs and get a head start on those, and this is what we call code base.

Barry Canton:

Not only have we had to build a huge amount of infrastructure in our labs, in our foundries, with equipment and people and processes, the same applies to data. We’re generating a huge, massive amount of data across our operations every day. That data is being managed by our software, our proprietary software, but it’s really all built on a layer of digital infrastructure that was built specifically for our foundry. You’re going to hear today from Dave Treff, who’s our head of DevOps and IT, about that digital data infrastructure that we’ve been building,

Dave Treff:

Usually companies that are big build big but inflexible, slow-to-change infrastructure. Small companies will build smaller and flexible, much more flexible, much more changeable infrastructure. At Ginkgo, we build big and fast and very changeable. I have to change stuff constantly.

Dave Treff:

One of the things that we do is everything that we buy, for example let’s say we’re buying some network equipment, we look at each piece of network equipment that’s in the whole network or any computers that are in the foundry or anywhere, and we look at it and go, “Okay, we’re going to buy this today. Can we

make it go faster next year or can we upgrade it so that it has more capacity for more data?” Primarily, it’s Knight’s Law. If I was asked to do a three-year plan, for example, we do 4X every year, so it’s 4X this year, it’s 16X next year, it’s 64X year after that. So I have to have 64 times, or I have to plan for anyway, 64 times the amount of network, the amount of compute and the amount of storage that’s available. I’ve never worked anywhere like that. This is not normal.

Dave Treff:

Well, it’s really fun. I will tell you that. This is the most fun job I’ve ever had in my life. And if you look at me, I’ve had a few jobs.

Dave Treff:

What we do is we just stay ahead of the scientists. We buy bigger pipes, we buy bigger equipment, all of our software we make and we have to make it because it doesn’t exist. And the way we design our networks is obviously for things like resilience and I mentioned upgradability and flexibility and blah, blah, blah, but we also have... There’s probably, I don’t know, maybe a dozen different types of data that come out of these machines. We have to handle all of them and we have to get it to the software that we write, which is all bespoke, and then we have to shuttle that around and we’ve got to store it and we’ve got to make it so that Patrick and his folks can find it because that’s the code base.

Dave Treff:

We have built a custom network with lots and lots of security controls in them that go all the way down to the bit level, so there’s security on the wire, there’s security on the software, there’s security in all the network switches. But one of the other things about that is that’s really hard to do. You can’t just do that. You can go out and buy it, but do you trust it? No, you really want to do it yourself. So what we did is we hired a couple of ex-military three-letter agency people who have a lot of stories they can’t tell us, and they have been designing and helping us build our network and all of our processes to be secure. And what that does is obviously it gives us a lot of peace of mind. Other companies outsource all that stuff. We want to keep it in-house.

Barry Canton:

So the output of our foundry is a new cell, a programmed cell that does what our partner and our customer needs it to do, but that may not be all that they need. So sometimes our final product is the program cell, and we are able to hand that off to our partner for commercialization and production. Sometimes that cell needs to operate in a manufacturing process that we can help develop, perhaps in conjunction with our partner or perhaps we do the work to develop that manufacturing process.

Barry Canton:

Sometimes what our customer or our partner really needs is just a final product. They need a compound, they need a molecule, they need a protein that they can use for perhaps their application testing or to go directly into sales channels. In those cases, Ginkgo’s product is the cell, the process and whatever that cell is intended to make. We can help the partners close the gap from the newly programmed cell that we’ve developed for them to their final product. We have those capabilities across our foundry and across our locations.

Barry Canton:

So a core premise of our foundry is that most cell programming projects follow a conceptually similar workflow. We’ve already talked about it, designing cells, building them and testing their performance and iterating through that loop. That insight means that we can build a general purpose foundry that runs that

general workflow for many cell programs at the same time. Why is that helpful? Well, it’s helpful for one very important reason, because by running many cell programs at the same time we unlock economies of scale. We are able to make sure that our foundries are at a higher level of utilization, each individual piece of equipment is at a higher level of utilization, so that we can make better use of fixed costs or capital investments and amortize those expenses across many cell programs and many operations.

Barry Canton:

By working on many cell programs at the same time, we’re also increasing our learning about how to do this process better. We’re increasing the number of code base assets that we have available to us that we can then use to make subsequent cell programs easier, as you’ll hear later from Patrick Boyle. By working on many cell programs at the same time, we are able to reduce the individual costs of any given cell program. By doing so, we can increase the probability of success of those programs, we can reduce the cost of those programs and that’s value that we can offer to our partners.

Barry Canton:

So by working on many cell programs at the same time in our foundries, we unlock economies of scale, which makes the overall process better. By doing so, we then get to work on more cell programs at the same time. There’s a virtuous cycle there where more cell programs translate into greater economies of scale and better value for our partners.

Barry Canton:

So you can really think of the Ginkgo foundry as being a combination somewhere in between a lab and a factory. That’s why we don’t call them labs, we call them foundries because we wanted to differentiate them from a conventional lab.

Barry Canton:

But why foundry? Well, we’re using the term foundry that was popularized in the semiconductor industry where a foundry is really a chip fabrication facility that relies on very sophisticated equipment, very complex processes in order to be able to make an incredible product, a semiconductor chip. We thought that was a great inspiration for what a cell programming lab of the future could look like with investment. So that’s why we call them foundries.

Barry Canton:

One other reason why we like to make or draw the connection to the semiconductor industry is because we’ve been greatly inspired by Moore’s Law. The observation that over more than 30 years of development in the semiconductor industry, the complexity or the sophistication of semiconductor chips doubled roughly 18 months. And it did so by virtue of investments in the foundational tools and technologies of making semiconductor chips.

Barry Canton:

Our belief, the premise of Ginkgo, is that with investment in tools and technologies, we can see a similar compounding improvement in the technology and what we are able to deliver to our partners, as was observed with Moore’s law in the semiconductor industry.

Barry Canton:

You may think [crosstalk 00:33:19] that speculation, well, we believe that we are seeing that trend happen. We can empirically track the operations of our foundry, we can track how much work we’re doing, we can track how much it costs us to do that work and we can observe trends in how that amount of work and that cost of work is changing over time.

Barry Canton:

What we’re incredibly excited about is that over the course of the last five or six years, we’ve been able to see an exponential improvement in the amount of work that we do and an exponential reduction in the cost of that work on a per unit basis. That concept of exponentially increasing output from our foundry and exponentially decreasing cost to do the work we call Knight’s Law. It’s a nod to Moore’s Law that you’ve heard about. It’s also a nod to my co-founder, Tom. Knight’s Law at Ginkgo is really the result of an enormous number of people’s hard work over many years. And if we want to give recognition to one person who helped inspire so much of that work, we couldn’t come up with anyone more perfect than Tom.

Barry Canton:

So the reason that we’re able to maintain Knight’s Law and the reason that we expect that we’re going to be able to maintain Knight’s Law for many years to come is because we’re constantly evolving the technology and the tools and the operations of our foundry. We bring in new technologies that allow us to reduce variable costs. We bring in new processes that are more efficient, that save steps that can operate at higher throughput.

Barry Canton:

One particular example of that I want to highlight is advances in being able to combine many prototypes together in a single well or a single tube. So instead of needing to dedicate one tube per prototype, in which scenario our scale is limited by how many tubes we can push through the foundry every day, by combining many prototypes inside a single tube, and we can, in some cases, combine hundreds of thousands or millions of individual prototypes in a single tube, that really unlocks incredible new levels of scale and throughput through our foundry. We call that one multiplexing. That’s just one of the kinds of technologies that we’re, on an ongoing basis, introducing into our foundry. So what that means is what we’ve been showing you today is the Ginkgo foundry of 2021. We really look forward to seeing you again soon when we’ll be able to show you some of the new technologies and operations that we’re bringing into our foundry and are helping to drive our ability to program cells.

Christian Henry:

So I’ve been really fortunate to be part of the Ginkgo journey for nearly five years and in that time, I’ve seen one foundry go to now just recently opening the fifth foundry in the company at a scale that just quite frankly blows my mind.

Christian Henry:

What the team’s really been able to do is take all of the best of the life science technologies that are out there today and put them together in such a way to create an unprecedented scale. And you can see it as you walk through the different foundries, from the first foundry to now the most recent, highly automated fifth foundry.

Christian Henry:

When I sit and walk around the foundry and talk to people, I just get blown away every time because I think about the implications of what this could be and how this can change all different kinds of markets and create all kinds of different opportunities for people everywhere.

Ginkgo’s Platform: Codebase

Patrick Boyle:

The term that we borrowed from the software world. So you may have heard people talking about what we do at Ginkgo as programming DNA. So we have DNA sequencing, which is the ability to read DNA, DNA synthesis, which is the ability to write DNA, put those two things together and effectively you’re writing code. Codebase in the software world is really a way of thinking about what are the things that we’ve learned over the course of writing software programs that can be repurposed and reused for writing new programs? So a programmer today working on a new application would say, “Let me check out a library or a module from this codebase to build a new application.” They’re not writing every new application from scratch. There are lots of tools available to make that easier.

Patrick Boyle:

And what we’re trying to do at Ginkgo is basically build up all the experience that we have from doing all these programs and saying, “What are the biological programs from previous work that we’ve done and make them available to our programmers to use in subsequent projects so that we’re not starting each new project from square one, but can start on a basis of reusable biological assets or codebase that we can put into new programs?” The really cool thing about biological codebase is that it starts with nature. So unlike every other engineering or programming discipline, biology has actually been designing new things for four plus billion years. So the idea is we can actually start by looking into nature, to look at genetic programs that have been produced via evolution as our starting point. But one of the interesting things about biology is that there is a lot of digital information stored all around us.

Patrick Boyle:

There’s much more biological information out there than you may be aware of. So for example, you may know that you have a trillion cells in your body. On top of those trillion cells you also have a trillion bacteria living in your body. So think about just the density of information that’s encoded in all of those organisms. Another example for this is soil. You may think of soil as just dirt. Soil to us is an interesting place to look for new genetic programs. So to give you an example, we had a project that involved chemistry in the soil where we decided to sequence some soil to find new genetic activities. Take 50 milliliters, so that’s about a shot glass worth of soil, run that through a sequencer and what you find, and what we found is you identify 30 gigabases of new DNA information.

Patrick Boyle:

So base pair is about a bit, that’s 30 billion bits of new information. All those bits represent potential new genetic programs that we can use in different contexts. Multiply that times the rest of the world and you can understand that 4 billion years of evolution has created a lot of biological diversity and therefore, genetic programs that have been invented by biology that can then be identified and developed here at Ginkgo to build the next genetic program. Every time we do some sequencing like that, we’re looking for new genetic functions, we test those in our foundry and as we characterize those functions in the foundry, we record that digitally so that we can go back and reuse those genetic parts later. Codebase at Ginkgo really benefits from and exists because of the foundry. Effectively, you can think of the foundry as a way to do scalable experiments.

Patrick Boyle:

So really the scale that we have in the foundry allows us to collect so much information. It wouldn’t have made sense to try to record information in this way until we had this method using the foundry to systematically create thousands of data points for every project. Today, we’ve done more than 10 million strain tests. So that information can be used to make sure that we’re progressively making better decisions when we’re designing new projects. Today at Ginkgo, we have certain programs that have looked at 30000-

40,000 genes. We’re taking more shots on goal, iterating through more designs so that we can more rapidly engineer a working and functional organism for that customer. So that’s what the foundry can do. Codebase is important because we want to take all that information that we’re learning from that one project and apply it to the next one.

Patrick Boyle:

So you can think about, as we grow foundry capacity year over year, I want more and more of that capacity to be pointed at brand new things, like doing projects that we’ve never done before, working in enzymatic pathways that we’ve never worked in before, because the codebase knowledge that we’re building up means that we don’t have to repeat some of those same experiments that we’ve done previously. And the cool thing about biology is that given that biology all evolved from a common ancestor, a lot of biochemistry is shared across a huge diversity of products that are made by it by nature. So that means we’re progressively learning more and more about what nature can do. So each new project we’ll borrow more from our preexisting codebase, that’s like characterized genetic parts and programs that we’ve done before, which frees up even more foundry capacity for all the new stuff we’re doing.

Patrick Boyle:

So it’s a virtuous cycle where we grow foundry scale, collect more data and can make better use of that foundry scale on the basis of the data that we’ve already collected in our codebase. Another way to think about codebase is how many different sequences do we sift through when we’re looking for a new genetic function. Today, we have a database that includes about 3.4 billion sequences collected from the broader world. These are sequences that have been collected by all of the biological community and provided on public databases. And then we have another 400 million sequences that we’ve collected over the years that are proprietary to Ginkgo. And that gives you almost 4 billion sequences to play with. But again, what I find exciting about that is sequencing, as you may know, is getting cheaper and cheaper and more scalable each year. So the cost of sequencing has fallen a million fold over the last 20 years.

Patrick Boyle:

So ultimately what that means is in terms of looking for new genetic sequences and new genetic code, we’re really just getting started and those hundreds of millions of sequences that we have today represent a small sliver of the sequences that we’ll be using a few years from now to identify new gene functions. In many ways, codebase is a literal parts library. We have genetic sequences that we have in our databases that correspond to actual DNA sitting in a freezer that an engineer can put to use in a new project. The data about those parts, the performance data is what helps us make good decisions there. But ultimately what’s cool about codebase is that it is physical, it is a genetic sequence that can be repurposed, it is organisms that we’ve used across a large number of programs.

Patrick Boyle:

And that ability to identify new genetic parts out in nature and then put them to work in our foundries is one of the things that I’m really excited about because as our foundries grow, so does our ability to identify new genetic functions and learn from nature. And ultimately what we’re trying to do as engineers is making sure that we’re learning from the 4 billion years of genetic experimentation that have already happened to us. That’s a tremendous resource that you just don’t have in other engineering disciplines. We actually can learn so much from what nature has already done for us and we finally have the tools to do that. How does codebase benefit our customers? So we have two different types of customers. Many of them actually are cell programmers in their own right.

Patrick Boyle:

So they’ve been engineering biology for many years, they have deep expertise in their organisms, in their programs, but again, they’ve been very focused on a certain set of products. So what codebase offers is saying, “Here are all the genetic parts that we’ve looked at over the course of doing dozens of different programs, probably working on organisms and market verticals and applications that have nothing to do with what this customer is working on. And yet, because biology is really cool we often find functions that can be repurposed for those customers.”

Patrick Boyle:

So they’re automatically benefiting from the dozens of programs that we have performed on day one. The other type of customer that we work with these are product companies. They’re really focused on developing, compelling new products with biology. So they’re interested in formulation, generating new materials, basically trying to get products to consumers.

Patrick Boyle:

What codebase offers them is they don’t need to build out deep expertise in terms of what genetic design to use when trying to overexpress a new gene in a new system. They can work with us and we can say, “Your product resembles another project that we’ve done before. Therefore, we can start with this host organism that produces precursors for your project or we can start with this host organism that’s very talented at producing protein. Here are genetic approaches that have worked before, we can apply that to your particular program.” And ultimately, for those customers it means they spend much more of their time thinking about how to make their products, rather than trying to think about the organism that makes their products, which is really our job. How does Ginkgo as a horizontal platform differ from the traditional way of engineering organisms?

Patrick Boyle:

Many of our predecessors in this space would have focused on a very narrow set of products to produce. So imagine that you’re starting a new biological product company today. If you didn’t know that Ginkgo existed, what you would probably do is you’d go out and you’d hire 20 PhDs, they’d all work at the bench, they’d be very smart, come up with good ideas, a lot of person hours of work would go into engineering a small number of engineered organisms. If you’re lucky, you’ll end up with a product at the end of that. At Ginkgo what we’re doing is instead you have a five-person team because they’re making use of the foundry to do most of their work, they’re starting from a point where they can, say, start with a existing protein expression strand that we’ve already developed, so a lot of the initial work you would do just to get started has already been done.

Patrick Boyle:

And then the know-how and approaches you’d use to leverage the foundry to look at thousands of new prototypes to rapidly optimize your strain, those are lessons learned that we’ve incorporated across dozens of projects. So ultimately what we offer to customers who are trying to start new programs, create new biological products is that they don’t have to assemble those 20 PhDs, they don’t have to build all of that institutional knowledge that will only live on in a single product. They can benefit from the institutional knowledge that we’ve collected across dozens of programs. So one way that we’re thinking about codebase is how do we actually package codebase that’s more understandable both for our cell programmers, but also for our customers? One organizing principle that’s been really useful in software are what are called SDKs, that stands for software development kits.

Patrick Boyle:

And SDK will give you the tools to program in that language. It’ll give you some example libraries, some codebase that you can use to build higher order programs and also give you documentation. So you put those things together and a new programmer can get up to work quickly working in a new programming language. So we’re trying this out at Ginkgo, I’m calling them CDKs or cell development kits, but effectively what a CDK is for Ginkgo is taking an inexperienced organism that we’ve used across a number of different programs. So we know that it has robust performance, we know it grows well in a fermentor, works well and our automation and our foundry, so the robots can work with it. And importantly, we also have tools. So our foundry tools can be applied to that organism. Combine that with documentation, you basically have a platform that enables us to help our cell programmers get up and running quickly with a new program.

Patrick Boyle:

So for example, with the Dutch DNA organisms that we’re bringing over, these are filamentous fungi. What we’re doing is we’re building a fungal CDK, which will basically take those organisms, make sure that we have foundry tools to do all the things that we can do in the foundry with these organisms and use that to build out a number of different programs, focusing on protein expression and enzyme expression. And ultimately what that does is it creates not only the playbook for executing these types of programs, but it also builds out the tools and documentation. So again, leveraging hard [inaudible 00:12:13] lessons from software to say, “Let’s make sure that these projects are repeatable and that we never make the same mistake twice on a program.” And CDKs are just one organizing principle for that. What’s exciting about codebase is that we’re just getting started.

Patrick Boyle:

We’ve accumulated more than 10 million strain tests since we’ve opened our foundries. And each of those strain tests generates data that helps us inform how we should use our foundries better. But ultimately, you’ve probably heard of Knight’s Law, and that means that year over year our ability to generate data continues to grow. So really we’re just learning how to, how to collect and catalog that data in better and better ways. That’s really where we start to see the benefits of these dramatically falling cost curves in DNA sequencing and synthesis. It’s not just about reading and writing code, but learning from that code. And if we’re able to learn at the same rates that we’ve been able to improve the underlying technology, biology is going to get a lot easier to engineer over the next few years.

Claire Laporte:

My name’s Claire Laporte. And you’ve just heard about foundry and codebase from some of the other folks here. And I’m here to tell you about what that means from an intellectual property standpoint, how we protect it and what it means for our customers. Well, I came to Ginkgo in 2018, after 28 years at a law firm. I was doing patent trial work and I also advised little companies that were getting ready to go public or get acquired, deal with their intellectual property problems. So I came to Ginkgo to develop a strategy for the IP of this rapidly growing company, and to figure out how to fit IP into the unique situation of Ginkgo. Ginkgo is like a giant invention factory where literally hundreds of brilliant ideas are made every single day. So the question is, what do you do to protect all of that?

Claire Laporte:

You can’t patent hundreds of new things a day, that would take an administrative empire, which is certainly not an efficient way to run a company. So we protect most of our intellectual property with trade secrets. So maybe I should just back up and talk about the difference between patents and trade secrets for a moment. Patents are very important for a lot of biotechnology companies especially. They’re a government granted, limited monopoly that lasts for about 20 years after you apply for the patent. But to get the patent, you have to make a lot of disclosures, explain your whole invention and then when your patent expires, that knowledge is dedicated to the public. Whereas a trade secret is something that is intellectual property because nobody knows it and you never disclose it. So they never expire, but they don’t add to public knowledge. But the amount of work that is required to get a patent is very, very expensive.

Claire Laporte:

So as a matter of sheer volume, because of the massive number of inventions made at Ginkgo every day, we are focused mainly on trade secrets, but we also have between 50 and 60 patent families and many other starter patents essentially, that have not yet matured into families, but will at some point. Just to step back and explain what that means, a patent family is essentially like a seed. You make one disclosure of what your invention is, and then you can use that to obtain patents all over the world, in China, in Europe, in Japan, in India, in the United States. So each one of those patent families essentially represents a group of related patents. So from the patent families that we have so far, we have over 200 issued patents and also a very large number of patents that are pending and are still undergoing examination in national patent offices all over the world.

Claire Laporte:

We have a bunch of them that are very much at a starter stage, what are called provisionals and those will mature to be patent families at some point as well. When Ginkgo makes a new invention, a lot of times what that means is that design engineers or protein engineers will come up with designs for literally thousands of possible proteins or enzymes, biological parts and pieces that can perform a particular task. And they’ll use all their knowledge about biology, our codebase, to come up with that large set of candidates which then through our foundry we’re able to screen and figure out which ones actually work. So when you have the opportunity to try that many things, when you have that many shots on goal, you score a lot of goals. So what that means is that in any particular campaign where we’re trying to find one of those important things that is going to make a product for one of our customers, we might have something like 50-100 hits that come out of our process.

Claire Laporte:

So then the question is, well, most patents relate to one hit, how do you cover 50-200 hits in a single patent? So what we’re starting to do is actually make patenting a part of the services that we perform for our customers. We’re going to own those patents, but they’re going to get a limited, exclusive license to a very broad patent that covers an entire headset and actually provides them with a much broader scope in their market than they would get if they had done this themselves and had found one sequence that worked. The synthetic biology industry has been plagued by not fully thinking through the consequences of agreements and contractual commitments that it made. So there’ve been problems where people have committed their platform, essentially exclusively to one particular customer in a field. And of course, what that means is that if that customer doesn’t do very well, the technology can lie fallow and it also really limits the ability of the company that is supplying the technology to be able to work with others and to generally advance the science that is going to make biology easier to engineer.

Claire Laporte:

So I’ve worked pretty hard to try to develop a transaction structure that allows every customer that we have to benefit from all the previous work that we’ve done while still also retaining some of that benefit for our future projects. In general, we give, as I mentioned earlier, a limited exclusive license to our customers over patented IP, but we provide a non-exclusive license to unpatented IP, and also to the background, to all that other stuff that we invented before we ever encountered that customer. When a company comes to us and is interested in making a particular kind of project, the expectation will be that we’ll get into that kind of contract where you essentially give away the store and you say, “Okay, I’m not going to work in that area anymore. You’re going to get exclusivity to all the stuff that we invent.”

Claire Laporte:

So sometimes I think they’re a little disappointed when they learn that we don’t give that kind of exclusivity. But I think that eventually our customers come to realize that our platform is what it is and gives them the power that it gives them because of the fact that we haven’t provided that kind of exclusivity. I worked on a project recently where we had done something in the animal feed industry, and we were able to take some of those learnings and use them for plasma DNA production, which is really super important right now in the global pandemic that we’re facing. So I think that our customers are increasing in sophistication to understand that we really are trying to hit that sweet spot, where we do provide them with a real advantage for having invested with us. But we also are keeping our platform moving and growing and continuing to improve so that we can keep making biology easier to engineer.

Shyam Sankar:

I see a deep parallel between the heterodox and transformative approach that many companies, including Palantir are taking and transforming information technology. I see that same parallel with what Ginkgo is doing with the foundry, with biology, manufacturing, and so much more, everything physical in the world. Another aspect of Ginkgo that I find incredibly exciting is the compounding opportunity of the codebase. It’s not just data for data’s sake, but data that gives you true decision advantage and builds a moat around the business by building and advancing fundamental understanding of the science.

Cell Programming — Commercial Review

Anna Marie Wagner:

So now that you hopefully have a little bit of a better taste for what it is that we actually do, we want to help you understand what that does for our customers. I’m going to introduce you here now to Jennifer Wipf, who’s our head of cell engineering commercial, and Ena Cratsenburg, our chief business officer. We’re going to introduce you to a number of our customers and help explain how we think about building real partnerships with our customers and enabling their programs to succeed. Jen, Ena, take it away.

Jen Wipf:

Hi, I’m Jennifer Wipf, head of commercial here at Ginkgo Bioworks.

Ena Cratsenburg:

I’m Ena Cratsenburg. I’m the chief business officer at Ginkgo.

Jen Wipf:

We just took you on a tour of our foundry and you learned about our massive data and codebase. We want to talk to you about our customers, how we work with them, and give you a little bit of insight into what a cell program looks like.

Ena Cratsenburg:

As you’ve just heard, our mission is to make biology easier to engineer. And what that means is that we are relentless in the pursuit of building a world-class cell engineering program to enable our customers to develop very innovative products and solutions. Our customers are amazing innovators who have great ideas of how to use biology to solve world-class problems.

Jen Wipf:

At Ginkgo, cell programming can take on many different forms. It could be improving an ingredient for fermentation, inventing a novel therapeutic, creating bio-derived chemicals that replace products that are currently made with petroleum.

Ena Cratsenburg:

We do stuff like enzyme work that would go into baking and brewing. We’re working on solutions for bioremediation. So, the list goes on and on. There are many things we can do with cell programming.

Jen Wipf:

Many of the partners that we work with have their own R&D teams.

Ena Cratsenburg:

That’s right.

Jen Wipf:

Especially in pharma.

Ena Cratsenburg:

Yeah.

Jen Wipf:

Why would they come work with Ginkgo?

Ena Cratsenburg:

I think what’s really interesting is to see how Ginkgo actually compliments our customers’ R&D efforts. With sophisticated customers, like many of our pharma partners, they have an extensive R&D organization. They do their drug discovery and development really, really well. But what we do and what we offer is really an extension of that capability. We have a cell programming platform that is extensive, that has a lot of experts who know how to do cell programming. That really plugs into what they’re doing in terms of developing new therapeutics or looking for ways to improve the manufacturing process.

Ena Cratsenburg:

As we’ve seen with some of the latest news, we are working with pharma partners on improving mRNA production. We’re working with pharma partners on gene therapy, and the list goes on. There’s just a lot more we can do there that we’re really excited about.

Ena Cratsenburg:

We recently announced a deal with Biogen where we’re working with them to develop a next gen AAV-producing vectors. What’s exciting to us about that is gene therapy has a lot of promise to address a lot of unmet medical needs, cure a lot of diseases, but manufacturing has been a challenge. It’s difficult to manufacture gene therapies for diseases that have high dosage needs or for diseases with large patient populations. So what we’re doing with Biogen is to figure out how to use our high-throughput, automated foundry, along with our ability to come up with all sorts of different constructs and designs, and really go through rapidly this design test cycle to allow us to figure out the optimal constructs that would give us the highest producing, most efficient AAV production platform.

Jen Wipf:

Tell me about the types of customers that we have.

Ena Cratsenburg:

We have customers of all different sizes that span across many different markets. We’ve just talked about some of our pharma customers. But as you’ve indicated earlier, our cell programs are really broad and diverse. So we have customers that are working in different markets, whether it’s consumer products, in industrial chemicals, in bioremediation, baking and brewing. But we also have customers across many different sizes. We have Fortune 500 customers. We also have emerging new startups and a bunch of customers in between.

Ena Cratsenburg:

Once we enter into a collaboration with our customers and we put together a technical development plan, what happens?

Jen Wipf:

First, we assign a dedicated program team. These are experts in how to use the foundry and how to leverage codebase. But it’s not just that program team that works with our customers, they’re the orchestrators of the technical development plan. They leverage the massive scale of our foundry and codebase to execute on that plan. They are able to tap into the 200,000 square feet of foundry space that folks saw earlier, and the massive amounts of data that provide a starting point, a head start really, on how we can move the project forward.

Ena Cratsenburg:

And on top of that, the experts, all the experience that we have accrued from the years of working on different cell programs. It’s amazing to see that our customers who are working on a specific program can access this massive infrastructure, consisting not only of hardware, our foundry, software, the codebase, but also the expertise of people who can actually execute the program well.

Jen Wipf:

That’s right, Ena. Our teams are able to leverage experts throughout the foundry to run through design, build, test, ferment cycles, to run an iterative engineering approach to reach the outcomes that our customers need.

Ena Cratsenburg:

Take us through what actually happens when we engage a customer and start a cell programming project.

Jen Wipf:

When we start working with customers, we set up a cross-functional joint steering committee, and this is a team of people who are looking after both the technical and the commercial elements of that cell program. We find that through the process of often, our first cell program, we identify next areas of interest for our customers. They start to view us as a strategic thought partner, as technical advisors, and we understand more about their strategic interests and how biology can help support that. So we find that this joint steering committee often identifies new areas of interest for our customers, new cell programs that we can work on next.

Jen Wipf:

One of the things that we can offer to customers is the ability to flex up or flex down their R&D resources and their spend. What that means is that they don’t have to spend a bunch of capital to build out lab space and automation at the scale that we have. And even if they decided to do that, they wouldn’t have the years of experience building the scale and building the codebase that we have. We’ve been at this for over a decade now.

Ena Cratsenburg:

Yeah.

Jen Wipf:

What kind of new customer conversations are you having?

Ena Cratsenburg:

I’ve been doing BD in the synthetic biology world for the past decade and a half. What’s really exciting to me is to see that as the synthetic biology platform becomes more and more mainstream, there’s a lot more interest and understanding of what the platform can do. And because of the success that we’ve had with our existing customers, we’re getting existing customers talking to us about doing more projects. But those existing customers, as they launch new products, make the synthetic biology platform more real, and that attracts more and more customers. So the diversity of customers we’re seeing and the speed at which we’re getting really good traction with customers who want to use our platform, has really accelerated in recent years.

Ena Cratsenburg:

We’re getting a lot of inbound inquiries from customers about what can the biology platform do for them. They’re asking us questions that actually allows us to think more creatively about how our platform can be applied. So I’m more excited than ever about our pipeline, more excited than ever about the possibilities in synthetic biology. And I think it’s only going to explode from here.

Marijn Dekkers:

One of the things that gets me very excited about Ginkgo is the enormous breadth of applications, where our platform is relevant and can lead to breakthrough innovations. And we’ve purposely developed a corporate structure that will allow us to do that. We don’t just focus on one or two or three markets, one or two or three applications, but have set up the capability to be meaningful to a lot of different industries with partners, obviously, that have deep expertise in those industries. And that to me is the optimum leverage of what Ginkgo has built over the last 15 years.

Mike Leonard:

Motif is a food technology company and we’re here to create plant-based foods that people actually crave. And that’s kind of a high bar when you look at where the industry is at today. Where consumers really aren’t getting what they expect from their plant-based foods, they don’t taste right, the texture’s not right, the nutrition is not where it needs to be. We believe those gaps exist today because the basic science of how to formulate with plant-based foods isn’t really well known. And technology tools to really create ingredients that make a difference to close those gaps, haven’t really existed. From an ingredient standpoint, the technology that Ginkgo brings to the table and that we partner on is a huge unlock to deliver those properties.

Jen Wipf:

And plant-based food. This is really popular right now. So how is Motif going to compete?

Mike Leonard:

Well, the plant-based market is exploding right now in food. And we’re really well positioned to take advantage of a lot of that growth. One of the reasons we can do that so effectively is because of our partnership with Ginkgo and the great technology platform that codebase on Foundry gives us to develop new ingredients that don’t exist anywhere else. So the ability to create foods within this space that really tastes the way people expect them to taste, that perform the way consumers expect. Think of a burger that actually tastes meaty and that has the right texture to have pieces of the meat stick between your teeth. Think about cheese that’s gooey and melty and stretchy. We can enable those types of foods with the technologies that we’re building together.

Jen Wipf:

And how has the Ginkgo partnership helped enable you to build some of that technology?

Mike Leonard:

The real advantage to our partnership is the thought partnership that we have as a combined team. We’re very close partners and we’re colleagues in this effort. Also the advantaged technology of the foundry and codebase really provide us with a competitive advantage that nobody else in this industry has. We can literally screen thousands and thousands of variants of potential ingredients all at the same time, faster than anyone else can, and pick the ingredients that perform the best in plant-based meat, dairy, or nutrition applications. So we can move faster than anybody because of Ginkgo’s technology and we know how to make all that technology work in food better than anyone else in the industry can.

Jen Wipf:

When you have an idea about a technology need for food, and you come to Ginkgo to talk about that need, how does that work?

Mike Leonard:

The technology base at Ginkgo is amazing, but the intelligence of the people, the team at Ginkgo, is also second-to-none. We’re very fortunate to work with such amazing scientists. And so we started square one with an idea of what kind of functionality and food we are trying to target. And we worked together to identify the best way to generate those targets using the foundry. So we start from the very initial phases of what does the screening have to look like, and then what our approach is going to be to design the right organisms to make those ingredients. So that process can take anywhere from a few to six months and we’re together every step of the way until we actually have an organism in our labs that we can grow and scale up to commercial production.

Jen Wipf:

Once Ginkgo has done the engineering of the organism, how do we work with you to put that into market? To make that real?

Mike Leonard:

When we receive material from Ginkgo, it’s not just a handoff of a microbe, it’s a handover of all sorts of information and insights that enable us to quickly go to commercial scale and actually produce ingredients for these applications. It’s a full body of knowledge that’s transferred. The thinking, the partnership, and the conditions that allow us to be successful from day one, when we go into a commercial environment.

Jen Wipf:

So you’ve been with Motif for two years and you’ve seen a bunch of change. How does that pace compare to competitors or to other people who are working in synthetic biology?

Mike Leonard:

The innovation cycle here is breakneck speed, and that’s enabled by the throughput of the foundry and, again, the talent of the team at Ginkgo, and the way we work together on our partnership. I’ve been here for less than two years, but I’ve already seen more experimentation, more iteration, and innovation than I’ve seen in most of my time in the industry.

Jen Wipf:

Everything is fast here for sure. Let’s talk a little bit about the products. What’s it like when you’ve tasted one of these products that we’ve been making for the first time?

Mike Leonard:

We’ve actually gone into actual market applications. We’re actually selling a prototype product now in a food service environment, which contains Motif ingredients that we collaborated on to produce. To be able to be in that situation less than two years from inception is just astounding. But the feedback we’ve received on these products is incredible. We’re finding that our product is beating market incumbents and performing at a higher level than what you can buy in the store today.

Jen Wipf:

Why are your investors excited about Motif?

Mike Leonard:

They’re excited by exactly that combination you mentioned earlier. They see the value in the advantaged technology that codebase and foundry bring to the table. They see the team at Ginkgo, how they work with the Motif team. They see our partnership and combining that incredible technology on the front end with our ability to execute and commercialize in the food industry, with all the experience we have. That’s a combination that they can’t find anywhere else. And it’s very compelling from an investment standpoint. We’re going to invent new ingredients that the industry’s never seen. And we’re going to do things from a science standpoint and an innovation standpoint that will really change the world of food in ways that are hard to predict now.

Jen Wipf:

Sounds delicious. I can’t wait. Thanks Mike, for talking to us today. I really enjoyed it.

Mike Leonard:

Thanks Jen.

Mike Gorenstein:

It’s great. We have the industry expertise and you have, overall, the platform that plugs in. I would say it’s like if I wanted to start an e-commerce company, I wouldn’t try and build a data server farm. I would go to Amazon and say, “Hey, we need to get hosted on your platform.” So I think there’s really no overlap. It’s designing the organisms, they’re fungible. The cannabinoids you make are fungible with what we grow and extract. So we already have the base products to market. It’s then innovating, adding new cannabinoids, and tweaking the brand messaging. And I also think one of the things that’s amazing, the fermentation facility is a great example where we were looking at [inaudible 00:14:31] and then someone knew that, “Hey, there’s a facility that might be available.” And so, while that’s not part of the collaboration initially, just teaming up and saying, “All right, we’re going to work together to go and find this facility and retrofit it and scale it up.” So to me, especially given the equity relationship, it’s a full partnership.

Mike Miille:

So Joyn was actually launched and founded back in 2017, October of 2017. And the vision was to bring together the agricultural and microbial expertise at Bayer with the synthetic biology expertise at Ginkgo and marry the two together with the vision of engineering microbes for agricultural solutions. And that was the basis for the company. So in 2017, when we launched it, it was me halftime. It was the interim CEO and fast forward to today, Joyn is 75 employees. We’ve got about 50 of them in Boston here, cohabitating with the Ginkgo team. And another 20 in California in Woodland at a Bayer site doing our plant science work. And it’s been an exciting adventure for us as we’ve sort of... Essentially pioneering the use of, and the approach of, engineering microbes for agricultural solutions. That’s really the key thing. And so it’s been a great partnership between both Bayer and Ginkgo to drive this.

Mike Miille:

And we’re joined as the beneficiary of being a joint venture that has these two highly supportive parents. It’s actually been from the very beginning, and has been very much a team effort. And I think what you have to understand is that that microbe or that chassis that we’re using in its natural form, there are no microbes that do this. So with Ginkgo, we’re able to use the foundry and the technologies that Ginkgo’s developed to essentially go through with what Ginkgo will call design build test. And so we’ll find a starting point. We’ll find a microbe that has some baseline activity. And then with the help of the Ginkgo and the foundry technology, we’ll go through iteration after iteration improving the amount of nitrogen that’s fixed and the amount of nitrogen that’s being transferred or the high throughput.

Mike Miille:

And the scale that Ginkgo brings is something that not only a small company like Joyn, that even somebody like Bayer, doesn’t have, right? And it’s extremely unique to Ginkgo. And so that’s why this partnership between the two, like taking the agricultural and microbial power of Bayer, and then combining that with Ginkgo is a partner for Joyn. That’s why we’re in such a unique position compared to anybody else out there in terms of the resources, the tools, the technology, and even the know-how that’s there, that all has to go into doing something nobody’s ever done.

Sasha Calder:

Historically, we had seen that products are created in a way where it was really you needed a quality product, it could hit costs, and there was performance. So the quality performance costs as the main drivers. And now we’re seeing the brands who are coming to our table, who are saying, “We need Genomatica.” Sustainability is the driving cause. So they’re saying, “We need sustainability, we also need costs, and we also need performance.” And we’re able to bring it to life and bring it to scale. And so what synthetic biology reminds us is that sustainability is how we can deliver in a new way. And it takes collaborations like our partnership with Ginkgo and other folks to bring this work to life and to accelerate the changes.

Deniz Kural:

Our partnership with Ginkgo Bioworks has been really fruitful. They work with us to understand our needs and identify the areas in which their technologies could help advance our goals. Ginkgo built systems to express the COVID-19 antibodies we had discovered, and they tested the antibodies for spike protein binding and neutralization activity. Pairing our computational antibody discovery platform with Ginkgo’s foundry was instrumental in validating proof points for our COVID-19 program. Ginkgo hasn’t just been incremental [inaudible 00:18:45], it allowed us to scale our platform’s tangible output. With the addition of Ginkgo’s complementary methods, we’ve been able to evaluate more of our computer sequences than we otherwise would have been able to within our budget. Together, we’ve been working on molecules with exciting potential relevant to the COVID-19 pandemic, while at the same time laying the technological groundwork for responding rapidly to future threats.

Dr. Arie Belldegrun:

Hello, I’m Dr. Arie Belldegrun, a physician scientist, and a UCLA professor, and a Ginkgo investor, and incoming board member. I have with me three outstanding scientists and leaders in the biotech and life-sized industry. Today, you will hear some of the ideas from that discussion. We spoke about the value of synthetic biology or syn bio for the biotech and pharma world and the potential of Ginkgo’s value and contribution to the space. Enjoy.

David Chang:

So let’s first talk about synthetic biology. I mean, to me, this is really a continuum of the recombinant DNA technology. I mean, now in the genomic era, we understand the functions of many genes. And what we can do now is not only understanding the functions of the genes, but what different segments of each gene does in producing protein. Now in the current genomic era, we can piece different parts together and come up with gene that can do much better than what the natural gene does. I think this is really the synthetic biology at the core. And now what Ginkgo, I believe, is doing is industrializing the process of synthetic biology. I’ve been involved in the chimeric antigen receptor drug development for the last eight or nine years. And when I think about the chimeric antigen receptor itself, that is an outcome of synthetic biology.

David Chang:

Chimeric antigen receptor doesn’t exist in nature. It is pieced together using three or four different genes. And you come up with a protein that will enable the T-cells to do its job much better in seeking out and destroying the cancer cells. And this is not just a science fiction, they are full FDA approved products using chimeric antigen receptor technology. And there are thousands more in development as we speak right now. And what the Ginkgo biology scientists have done is modularize synthetic biology to make this occur in a much more efficient and speedy way.

David Chang:

So something like chimeric antigen receptor technology from the inception of the idea, which occurred in the late 1980s, to actually perfecting the so-called second generation that we are all using, it took about 15 years. And we are still looking for a better chimeric antigen receptor in a construct. And I think this can be done in a much speedier away, not in 15 years, and hopefully in a matter of months and that’s where Ginkgo is coming in.

Mitch Finer:

There’s three key areas that synthetic biology can have an impact on gene editing. First, what’s important with gene editing enzymes is to be able to sample the genome, that is to edit any base anywhere. And if we focus on RNA-guided nucleases, the CRISPR-Cas systems that allow you the greatest flexibility, those systems are dependent upon a primer that can see the nucleotide sequence that one wants to target, but they have to see adjacent to that primer of what’s called a PAM, or protospacer adjacent motif. Otherwise, you can’t target your specific sequence. And as editing becomes more precise, the enzymes that are available being developed by the current prop of companies, Strep pyogenes, Cas9, Staph aureus Cas9, Cpf1 have very limited PAM sequences. And you can only target against those PAM sequences. Your primer must be preceded or followed by those PAM sequences.

Tom Knight:

I think there’s several immediate applications that come to mind for the development of synthetic biology, ginkgo’s platform in the application to therapeutics. Perhaps the most immediate one, and the one that I think is perhaps going to be most important, is development of new antibiotics. We have a collaboration with Roche that is looking at antibiotics that can treat some of the gram positive organisms that are difficult otherwise to treat. Another area that I see as very promising is in the high throughput production of protein therapeutics. Most of the proteins that now are being produced are using primarily natural amino acids. And I think as we go to the more challenging targets in the protein therapeutic space, that increasingly we’re seeing those proteins, including a very important number of unnatural acids. And I think that there’s a new job opportunity to use recoded bacterial organisms that may be able to simply express those specific unnatural amino acids in a more natural way and avoid the use of chemical processes during the synthesis.

Launching Strategic Ventures

Jason Kakoyiannis:

So what is the signature we look for when starting or ideating a new strategic venture? That signature actually has three pieces or three prongs. We’re usually looking for a large market opportunity where biotechnology has had a toehold, but been under-leveraged or under-invested, where typically we see that innovation is siloed out and potentially under-resourced. And then the second prong, where we can aggregate that work on Ginkgo’s platform in order to take advantage of our economies of scale, de-risk technical risk and accelerate programs so that we can develop multiple solutions and products. And third prong, we look for opportunities where we can partner with corporate strategics or seasoned executives that have deep networks and expertise in a channel.

Jason Kakoyiannis:

So the advantages of strategic ventures are fairly clear. These companies are born day one with immediate access to Ginkgo’s cell programming platform, mature de-risked with 400 plus scientists ready to rock day one and take programs. They don’t need to, for instance, take and undergo that typical lag time that startups have of booting up their own technical team, hiring their own engineering team, developing their own lab, right? So instead they can orbit around their customers, around their product development, around their application science, the things that will eventually drive the core value for those businesses. We think of this as a classic division of labor by comparative advantage, although it’s actually startlingly rare in venturing where typically companies spend their first years of life and their first rounds of investor capital actually building up and proving out their technical platform. Here we think we’ve obviated that.

Jason Kakoyiannis:

So, as I said, instead of focusing on cell engineering, these companies can maniacally instead concentrate on product development and market applications, et cetera, and so that’s where they build up expertise and build up capability. So as a result, these strategic ventures teams looked very different than the Ginkgo team. They look complimentary to the Ginkgo team. In the case of Motif, for instance, you see world-class food scientists, you see sensory experts, people who are really well versed in understanding how ingredients can be formulated and mixed to solve texture, taste, other sensorial problems and create new experiences for consumers in the food space. Allonnia, there are teams and folks who are well-versed veterans in the bio-remediation space, process engineers that can marry biology with mechanical, physical, chemical systems that can then be deployed onto sites to remediate waste problems. Neither of these companies needs to have a team to build out a cell engineering platform. Ginkgo obviously covers that. But I’d say by far the most critical element for success for these op-cos is the leader. What’s needed in every case is this kind of alchemical mixture of someone who has a powerful vision for how biology can transform or disrupt an industry, someone with an expert understanding of their field and the gravitas to bring along customers and peers and someone who has that aptitude for translating a new technology. In this case biology into their market.

Nicole Richards:

I think the relationship with Ginkgo is really a game changer for Allonnia. Using biology for waste has been around for decades and it works, but it’s inefficient in how it’s used today. The use of natural biology has limitations and Ginkgo’s role in progressing the ability to read and write DNA is really unique and affords much more capabilities to Allonnia solutions than have ever been possible before. And it gives us more shots on goal with their foundry and code base. And an example of this is we’re working on a biosensor contaminant project. And so we’re looking to create a biosensor that detects contaminants in the field, and we’re working with Ginkgo to develop this. So through that work that we’ve been doing over the last couple of months is we’ve been able to test a hundred trillion constructs, a hundred trillion. To me that’s amazing. And it’s something that was never possible before and could never be done manually. So I think this is a great example of how their capabilities are really allowing us to be more successful in the development that we’re trying to do.

Jasmina Aganovic:

So we are of course, relying on Ginkgo to do biotech work, which enables us to remain focused on our industry and what we are good at. We don’t have to build out the technical infrastructure, which is expensive and costly and risky on the biotech front, nor do we have to hire a massive team for that expertise. So we’re able to rely on Ginkgo for the biotech work we’ll have, of course, some very important biotech expertise, but we don’t have to build out the team nor the infrastructure. And we view this as an agility play for us. It allows us to be agile. It allows us to be very efficient with our capital as well, and to focus on our industry and what we are good at. So if you think about the tool set of the industry thus far, effectively, for as far as we’ve known of the personal care industry, it has relied on extracting the ingredients that we use from the world around us, whether it’s relying on petrochemicals, animals, and then more recently plants. This is certainly a way of sourcing ingredients, but presents challenges and problems from a sustainability standpoint.

Jasmina Aganovic:

We believe that by turning to biology and biotechnology, we can not only solve some of those sustainability challenges, but perhaps more importantly, and what we’re most excited about, start to open up entirely new possibilities in beauty and personal care around the types of actives we talk about, the types of actives we formulate with, functionality and performance, and fundamentally changing how we construct formulations and products.

Jon McIntyre:

We’re going to create new food experiences for people and by doing so help the industry convert more people over. That’s only possible because our partners at Ginkgo can really deliver on the platform of analyzing the opportunities and discovering things that I don’t have to build the infrastructure to do. I have to have the knowledge of what should we be looking for and then how to apply it. And I think that is the true essence of the partnership that allows us to be aggressive in the other areas, and I would say that proof will be in the pudding over the next several years. We will surpass the other players who are really trying to create better tasting plant-based foods. And I think we already have quite a bit of proof in a very short amount of time that the products that we have developed with our new technologies inside in consumer testing and in sensory testing, outperformed pretty much all the products on the market today. And so obviously we’re in a hurry to get those into the market, but that would have not occurred if we weren’t able to balance Ginkgo’s power in what they do and us building a company with unique sets of powers that complement those.

Jasmina Aganovic:

We are going to have a pipeline of innovative, differentiated ingredients that will not only solve existing problems, but push into new white space for this industry. So that in and of itself is valuable and powerful. And we have unique access to that very much so because of our relationship with Ginkgo. Effectively, we have this multi-billion dollar platform that is able to do this work for us at a speed and a cost that makes this viable in this industry. It enables us to stay focused on the application area that we are experts in, so we get to stay focused on the formulation and the analytical piece so that we can confirm how we bring these ingredients to market in an experiential way that is still powerful and high-performing.

Jon McIntyre:

There is a Ginkgo sphere, which is Ginkgo has a whole series of connections in different industries, different applications, different products, and different people that think differently. First of all, it’s exciting. It’s great to be tapped into. So the other CEOs of companies that have spun out of Ginkgo or a partner with Ginkgo’s, we connect one-on-one or in a group. We leverage that network to help each other out. We leverage that network to get new ideas. And so, first of all, just the partner companies create one network. And then Ginkgo was built with great investors. We have definitely built relationships with many of them. We’re excited to bring in some new investors that compliment those. And I think that network of investors has also created opportunities that we would not have seen previously. The other thing is Ginkgo has an unbelievably diverse set of people in the company. And as we’ve learned more about the people in the company, it’s helped us connect. And the reverse of that is I think that Ginkgo has realized that we’ve built an interesting company with quite a few smart and interesting people in that network goes both ways.

Care at Ginkgo — Biosecurity

Matt McKnight:

Hi everybody, I’m Matt. I’m the chief commercial officer at Ginkgo, really excited to be here to talk about bio-security. I know we just spent a bunch of time talking about the amazing products being built on the platform. I think this is a really important connective piece to that, just like in any industry that grows, if you think about computing and you think about the digital revolution, it wouldn’t exist without really powerful cybersecurity tools. And so from our standpoint, this amazing ecosystem that we’re building on top of the Ginkgo platform, we also have a responsibility when we think about the care we use in engineering biology to integrate security tools over time into everything we’re doing with our partners, into their products, to make sure that we’re engendering the right kind of development. And it’s really deeply built into who we are about how much it’s important to care about how our platform is used.

Matt McKnight:

Biology is such a powerful tool. It’s something that we have to be thinking about when we’re thinking about applications of our technology. We have to be thinking about it when we’re thinking about the security around biology. Today, we have this amazing group of people that have come to Ginkgo as advisors and as part of the team to really help us think about how to do that security piece in a really a powerful way. So I’m excited to have with us, General Tom Bostick. General Bostick was the head of the US Army Corps of engineers, and then in a way that’s really close to our hearts, moved over to be a biotech executive, and has been just a great mentor for us and an advisor for us at Ginkgo. Renee Wegrzyn runs all of our bio-security efforts focused on the US government and has joined Ginkgo in the last year from 10 years at DARPA.

Matt McKnight:

And so just brings us amazing set of experiences that has been really helpful for us as we think about what our role and responsibility are both on the culture side, but also on the technology side. And Andy Weber, who has this amazing set of history and stories around 30 years of engaging in this world, how do we protect ourselves from bio threats and from other things that exist on this planet, and has just this wealth of knowledge about how governments around the world work. And most recently, in government was an assistant Secretary of Defense and the Obama administration focused on these issues. So really excited to be here today, to have the opportunity to talk about bio-security in the context of what we’re building here at Ginkgo. Maybe I’d love to just start with you, Andy, right?

Matt McKnight:

We’re coming out of COVID, certainly the world is engaged with biology over the last year in a way that maybe is different in the last century. How much should we be thinking about bio-security and how are you kind of thinking about the next decade?

Andy Weber:

Well, we’re living through the largest biological event of our lifetimes, and we’ve seen an acceleration in the technologies that are helping us get through this. It’s been an amazing amount of progress. I think we’re at this inflection point and it’s a little bit like we were in the early nineties with the internet and smartphones, we have this new sector of the economy that’s really launching now. And it’s enabled by the digitization of biology, the ability to program cells, and we’re just tapping into that now and it’s going to change everything. So, we have an opportunity though, to bake bio-security into it now and not have that vulnerability that we’ve seen in the cyber world, where they didn’t really think about designing cyber security into the systems from the beginning.

Andy Weber:

And now there’s a huge investment in playing defense. So I think we also have an opportunity to establish the norms for this new sector of our economy and to establish some taboos, what not to do with this amazing power that’s been unleashed.

Matt McKnight:

So Tom I’ll go to you, right? I alluded to it, but this incredible unique combination of deep national security experience, running massive organizations in the US Army and then existing in the biotech ecosystem, how would you address the same kind of the same question? Why, after all what we fundamentally believe, is that biology and making things out of biology will transform economic output in the next 5, 10, 50 years. How have you engaged in that topic? What has changed? What are the things on your mind as we think about this interplay between security and economic outcome?

Tom Bostick:

Well, thanks, Matt. It’s great to be here. And I love being a senior advisor at Ginkgo, and what I’d say is I spent much of my life on the national security side of the house with Department of Defense. As you pointed out, it was building better dams, and now I’m building better DNA. And that was a difficult transition, but it’s a transition I was very happy to make because I truly believe that biology has a chance to make a huge difference in the future of our world and that we live in. And much of it’s going to come down to trust. When you think about bio-security, bio-security is the facilitator for the bio-economy, but it’s going to do that by building trust. And by building trust, what I’m saying is that people need to feel comfortable, they need to understand what’s happening to them. And when scientists do things, people most often trust that solution in times of crisis, and the crisis could be COVID, and you’ve seen people trust the science and trust the scientists take the vaccine.

Tom Bostick:

If you’re in stage four cancer, and there’s a new immunology solution, people will trust that, even though there’s some risks there. But when you think about where the world is going with many, many more people on the planet in the next 30 years, we need that trust not to exist just at the extreme of crisis, but throughout our daily lives. A good example is what Ginkgo is doing with K through 12 pooled testing. The kids going to school in the middle of a pandemic, and they’re doing that because the teachers, the mothers and fathers, aunts, and uncles, and the children trust that they’re in a secure facility in the school. And they trust that because of the bio-security platform that Ginkgo has provided.

Matt McKnight:

So what we’re doing in K-12, really it’s this mindset shift. It’s this mindset shift from, we use biotechnology in healthcare purposes only. What we’re doing in K through 12 is really offering schools the ability to test classrooms as cohorts and generate data like they would generate testing data or any other type of data in a school setting, to make better decisions. So, right, if we imagine a world with hundreds, thousands, tens of thousands of products made in this incredibly powerful, efficient way coming off of the Ginkgo platform, you were saying, let’s not just have security in the extremes, an mRNA vaccine that’s massively amazing to bring us out of our current crisis. We’re also saying, let’s have consistent regular security and trust throughout. So Renee, I think that that’s, especially as you’ve thought about this transition from DARPA into building this at Ginkgo, what is it about what we’re doing that gives us this unique advantage to build the tools, to generate this trust that you’re talking about, Tom? Coming from DARPA, what have you seen? And, what is it that you reflect on there?

Renee Wegrzyn:

I do see very much that Ginkgo is in some ways, almost like an ARPA of the private sector. And what I mean by that is, when I was at DARPA, we were building breakthrough technologies for national security. And so really Ginkgo is using its platform to create the next breakthroughs for the bio economy. And it’s not prescribed to a single application at the end of the day, it’s food security, it could be K through eight testing, but it’s really based on this platform. And we were successful in bringing K through eight testing and in helping respond on the vaccine side of things, not because we’re a pandemic preparedness company, it’s because we’re a platform company that is able to pivot and respond to what that challenge is. And so a year of powerful biology, here it was the pandemic, but it’s the powerful response of what our platform gave, where we could respond. And we’re going to use that in the future for our customers, bring us your challenge, maybe it’s the supply chain issue is the next thing we deal with. Maybe there’s an outbreak in agriculture that actually brings an economic to our shores. We’re going to be ready to respond, because we built a platform to do that.

Matt McKnight:

So you were incredibly important in building our K through 12 testing program. And I think connecting a couple of these pieces would be really helpful for us to understand. So at this point, our lab network that we’ve partnered with to qualify to run testing across the country has enough capacity to test every student, teacher and in America, right? And that gives them this data layer to be comfortable in knowing, like any other piece of data, what’s going on with COVID-19 in their communities. Can you just share a little bit about what you did differently to bring biology to these communities that had never really engaged with something like test every kid every week?

Renee Wegrzyn:

Yeah. In the Baltimore city schools example, I think is a really great one in the way that Ginkgo approached the challenge. So rather than go to Baltimore city and say, “Hey, we have the solution, this is what you should do.” We came to them, told them what we think we’re capable of, but really wanted to listen to them and understand, what do you need actually, and what is going to be workable in your communities? And so this wasn’t a single conversation, this was many, many conversations over many days and weeks to understand, how can we be on the same level? And does this work for your students? Does this work for your parents? Because the parents have to give consent, of course, for their students to be in the testing program. And we knew if we got that right in Baltimore city and invested the time that that would allow us to then bring that to other cities is much easier and a faster way. And that really did prove to be the case that we were able to scale to now thousands of schools across the United States.

Matt McKnight:

So what could you imagine with your kind of DARPA hat on, crises create opportunities to change how we do things to better prepare ourselves for the future, every major crisis in human history, things have come out of it, right? That are unique and different. So we’re testing kids across America in schools. What do you see that turning into if we get it really right as a country or as a world, what could that do to prepare ourselves in the future? And Andy, I’m going to ask you the same thing in a second.

Renee Wegrzyn:

I might give you two answers, because I think there’s two differences, there’s a scientific way and there’s a cultural way that you can answer that. And so, the first is, kids are really excited about having this technology, our creative team has really made an effort, there’s even comic books that the kids have now, so they can learn about the testing. And so going back to the lab network, what I’m really excited about on the technological side is not what those labs are doing now, it’s what those labs were doing before COVID, right? We’ve partnered with labs that were doing environmental monitoring, they’re looking at wastewater, they were sampling from the environment. There are labs that were doing cancer diagnostics, labs that were doing a hundred tests a week to a hundred thousand tests a week. So, there’s so much potential in that network, now that we are working with those partners and how can we really leverage that going forward to continue to understand our biological environment now connected through this digital layer that we built to really be ready for what’s next.

Matt McKnight:

Andy, in your last job, or if you look forward, if you had a network, the ability to monitor in an anonymized way, what was going on in the biological ecosystem, how would that have changed what you could have done or how we would have prepared as a country?

Andy Weber:

Yeah, well, these technologies and the distribution of them widely are going to give us the capability of having that weather map, where you get the weather report every day for infectious disease everywhere in the world, real time. And that will allow us to nip epidemics in the bud. So the information piece, the genetic sequencing piece, it’s all coming together. And I think because of the COVID crisis, the application of these bio technologies has leaped ahead a decade, in just a year. So now we’ve made that much progress, we’ll sustain it and improve upon it. And the benefit to humanity will just continue to grow.

Tom Bostick:

And when you think about bio-security, it is an early warning. It’s trying to identify the infectious diseases early on, so you prevent the sort of damage that we saw with COVID with deaths and infections and people getting sick. And I think in the future, just like you talked about earlier with cybersecurity, leaders will be asking what’s their bio-security strategy? How do they approach it so that the company is more resilient? And I think in the future, you’re going to see chief operating officer’s briefing boards about their bio-security strategy and that bio-security strategy in all these different companies are going to have to lean on the private sector expertise that can deliver on that. I think that’s going to be ubiquitous as well, and we’ve seen it already with what’s happened in COVID. So the question is, how does that get extended? How much are our boards willing to invest in? And I will tell you that, with my public and private sector experience, it’s a tough decision. How much do you invest in almost preventative maintenance? And some folks are willing to take risks, and when you take that risk, you pay a lot more on the backend as opposed to doing it on the front end.

Matt McKnight:

How do you see Ginkgo continuing to engage with the Department of Defense, some of the other governmental research organizations, what’s that interplay with just the continued innovation spirit at Ginkgo, and where can we continue to use that as part of this development, both in bio-security and otherwise?

Andy Weber:

Six years ago, the co-founders came to me for help. They wanted to make a contribution to national security and it’s amazing how respected they are in the Department of Defense. As leaders of this new sector of our economy that has applications across the Department of Defense and the Department of Health and Human Services, and it’s been an education process. But at this point when the government thinks about this, they turn to Ginkgo, they turn to the leadership here because they know that that’s where the capability lies.

Matt McKnight:

So we’re in all of these communities across the country now, and really focused on using testing as a data generator so that people can make decisions on a classroom level or a grade level, and not on a community-wide level, right? This is the idea that these are decision tools to make better, more nimble, sophisticated decisions, but they’re in schools, right? And obviously the current administration has invested massively in

testing in schools, and we’re playing a huge role in supporting that. But Andy, as you look towards the future, right, I think we see lots of different opportunities out of a crisis that we’ve changed, we’ve given schools and other parts of the community new tools. What could this be used for as we go forward? What are the other ways to build on this infrastructure that has now been laid as a country or as our communities?

Andy Weber:

Well, I see it as part of an early warning system, a weather map, if you will, for infectious disease. So we can see those storms coming and actually prevent them from happening.

Renee Wegrzyn:

There’s such a visual reaction to somebody when you say a forecast, right? You think of the weatherman and here’s, here’s this forecast. And what we haven’t really talked about yet is our dashboards. And so not only are we generating this data where we’ve developed the capability to digest that information, and then give that to a decision maker who might not have a PhD in molecular biology, but can say, “Wow, okay. My rates have been going up and look at my rates relative to the community. And, oh, by the way, this last month I tested a hundred thousand kids.” And these are really important points that on the decision makers can bring forward to know how to move. And I’m really excited about that interface with the communities. I’d actually be really curious, Tom, like you, running an organization that is global like Army Corps, what were the tools that you worked with that helped you make those decisions?

Tom Bostick:

One of the things I was going to follow up on, what both of your excellent points are, is that I’ve been involved in a lot of disasters and responding to those disasters. In some places you’ll find people are prepared more than others, Florida, they’ve seen a lot of hurricanes and places where earthquakes in their operations centering and what Ginkgo has done with this capability that it’s placed out there with K through 12, it’s almost like a public private partnership on a grand scale. A lot of these cities and towns and communities and states have not had to respond in the way that some other states have had to respond with disaster. So I give huge kudos to what Ginkgo has done in that particular way. Not directly in the K through 12 testing, which has been huge, but really macro level, how does the public and private partnership come together in a way that makes meaningful change?

Tom Bostick:

But the Corps system is to work with governments just like Ginkgo has done. So I just stood back in awe to watch Ginkgo do what maybe the Corps would do, but we’re not experts in schools. But I see a lot more public private partnership and Ginkgo has helped to facilitate that, at the tactical level all the way up to the state.

Matt McKnight:

Well, that was great, Tom, thank you. And I just want to everybody here, but also kind of in the spirit of the whole company, this has been a really amazing, hard, challenging, fulfilling year. And I appreciate all the work that you all have done to help us try to have the impact that we’ve had both on the bio-security front, but also on the platform build front and look forward to many years to come and thank you all for your guidance and work and very much appreciate your time.

Tom Bostick:

Well, thank you, Matt.

Andy Weber:

Thank you, Matt.

Care at Ginkgo — Investing in ESG

Anna Marie Wagner:

All right good afternoon, and thanks for joining us again. We just finished up this great conversation on bio-security and the importance in building that kind of infrastructure as this kind of technology really, really takes off. To continue this conversation about care, I’m thrilled to bring two luminaries in the field of impact and ESG into this conversation to really kick off the conversation on the role of sustainability and ESG topics in investing.

Anna Marie Wagner:

So just brief introductions here, Katherine Collins is the head of sustainable investing at Putnam Investments. There, she manages several sustainable equity funds totalling over $7 billion, and she collaborates more broadly with portfolio managers and analysts on integrating ESG into their investing theses across the roughly $200 billion dollars that Putnam invests. Prior to joining platinum Katherine founded and ran Honeybee Capital Foundation, which was an independent research company focused on sustainable investment issues, and did that after nearly 20 years as an equity research analyst and portfolio manager at Fidelity Investments.

Anna Marie Wagner:

We’re also joined by Governor Deval Patrick, who’s a founding partner at the Bain Capital Double Impact Fund, which is an $800 million private equity fund focused on scaling mission-driven companies. Previously served two terms as the governor of Massachusetts following a long career in both public service, including as the assistant attorney general for civil rights under President Clinton, and in the private sector as the general counsel for both Texaco and Coca-Cola. So thank you both for joining me. I’m really-

Governor Deval Patrick:

Great to be with you.

Anna Marie Wagner:

... really excited [crosstalk 00:01:45] again.

Governor Deval Patrick:

Thank you.

Anna Marie Wagner:

Maybe just to get us started, Katherine, you manage over $7 billion dollars of dedicated sustainability oriented capital at Putnam, and not to mention your impact on the broader portfolio, that is a lot of capital. So just curious, how did that happen and what have been your goals with those funds?

Katherine Collins:

Well, it is a lot of capital and it’s an honor to, to steward it. First of all it’s not just me, I manage the portfolios with my colleague, Stephanie Dobson. We have a dedicated Sustainable Investing Team. But even more important than that is the fact that our team is embedded in the Equity Research Team at Putnam, that really is the key to how things came about. Putnam took the time in planning for this team and this effort overall to step back and say, “How can we approach sustainable investing in a way that it extends our traditional strength as active long-term fundamental managers?” So instead of setting up this team as island unto itself, or a boutique down the hallway, or an administrative function, they really took the time to plan for this team to be part of our core equity research process and the portfolios that you mentioned and everything else comes from that foundation of long-term integrated fundamental research. So that’s really the key to everything, is recognizing sustainability issues as core long-term strategic issues that are relevant for any business leader and any investor.

Governor Deval Patrick:

Yeah. I’m going to second what Katherine says, that we have to think about sustainability as an integral and central part of all investment decisions, or business decisions, and frankly, all government decisions. I think that for me, all of this is in the frame of how we shift and must shift from a focus on short-termism to long-term value? What we’ve been trying to do at Bain Capital, and I feel really, really great about the success we’ve had, is to demonstrate that choosing between doing good and doing well, between financial return and measurable social or environmental impact, turns out to be a false choice all along.

Anna Marie Wagner:

So I’d love to dig into that topic because I think there’s definitely a perception that impact investing must have lower returns. You’re describing it as a false choice, Deval. I think that perception exists either because ESG oriented companies must obviously not care about profits because they’re optimizing on some other dimension. Or maybe the more neutral pushback is that it’s just a smaller potential investable universe. So it must be more competitive. You’ve heard that concept before, but you’ve both raised real amounts of capital against us, but then very large institutional investment firms that I know personally definitely care about returns. So I’m curious how you then think about the critique? You described it as a false choice, Governor Patrick, but I’d love to dig into that a little bit more.

Governor Deval Patrick:

I’ll start, and simply say that when we were organizing the Double Impact Fund at Bain Capital, it was the first impact investment fund at any institutional investment firm, any private equity firm. We made a decision to strive for superior returns, not as a value judgment for what others may do, but because we wanted to demonstrate that you didn’t have to make that choice if you didn’t want to, you might choose to but if you didn’t want, you didn’t have to. We chose sectors in which to invest where we knew we could generate that sort of returns. So health and wellness, sustainability broadly described, education and workforce development. All of these are secular trends with an awful lot of activity. There are great mission-driven companies that are in the lower middle market, middle market in North America who are looking for value aligned capital so that they grow, because they are concerned that the investors come along and say, “Well take it from here. We like what you’ve done.” But that the mission will get lost as they grow.

Governor Deval Patrick:

I’m delighted that as the first fund is now deployed and the second fund is well underway. I believe we are in the top quintile of the Cambridge Associates measure, not just of impact investing funds, but of middle market funds, regular way middle market funds. That is what we’re trying to show. You can do this at scale, you can do it over time, and it is about thinking about, and organizing toward, and being intentional about long-term value to all stakeholders instead of just short-term return for a handful of shareholders.

Katherine Collins:

It’s interesting that the theory and the math of traditional finance and neoclassical economics is really zero sum math. So there’s a reason for this really strong root of either or thinking on this topic. There are two bridges that are important, one we just touched on is relevance. As soon as you recognize sustainability issues as relevant to long term business success, all kinds of doors open up. Then the second key, is the short-term long-term element that Governor Patrick just mentioned. Once you get past a decision that might be hard in the first week or the first month and really extend your time horizon, it’s amazing how much alignment there is between something that is sensible and additive from a sustainability perspective, and also sensible and additive to company performance.

Katherine Collins:

So our premise at Putnam and the goals of the funds that I’m running are very explicitly to seek out companies where excellence in sustainability is making the company stronger. It’s not just that they happen to be managing these things in parallel, and they’re doing a good job at both, it’s that one is fueling the other in a direct and positive way. So just as one small proof point it’s not forever, but our two lead Public Equity Portfolios just hit their three-year anniversary, which is very important in the public equity world. Our Sustainable Leaders Portfolio at that anniversary mark was roughly 400 basis points annualized ahead of the S&P, and our sustainable future product which is solutions innovation oriented was about 600 basis points ahead of its benchmark. The rest will make [inaudible 00:08:08] growth benchmark. So to Governor Patrick’s point, those are great numbers, not just within a little slice of ESG centric portfolios. Those are just great numbers, and I think are proving out that thesis.

Governor Deval Patrick:

I think Katherine is exactly right. What we want is whatever kind of investing professionals are doing is to be intentional about the impact of that investing on multiple stakeholders. That is a fact of investing. Every business decision has some kind of impact. If you’re intentional about the impact beyond the shareholders, then you get better outcomes. It turns out, I think you get a better return as well.

Anna Marie Wagner:

Maybe just to end our time together here, a couple of questions for each of you. I’d love to just selfishly understand what themes you’re most excited about in this area. What over the next five years do you think is going to maybe drive the most impact? Or be the most important areas of focus for your funds? Then just given the audience today, I thought it might be helpful for you to just share any thinking or advice on how they might incorporate some of these ideas or themes into their own strategies, if they’re approaching it really for the first time?

Katherine Collins:

One of the tools that we’ve used for a number of years is this big giant thematic map. Honestly, it got a little bit sprawling, so we recently reorganized it under a publication called Investing to Thrive. It’s got three main layers. One layer is individually thriving, health and human wellbeing. The second is thriving systems and society with a lot of really interesting complexity within that layer. The third is a thriving planet, supporting life as we know it. So a few of the themes that are highlighted in that report and really interesting and important to us from an investment perspective, are also interesting and important I think to Ginkgo and companies like it. One is the movement towards circular economy where we’re thinking much more of the economy as an ecosystem, as opposed to this linear extraction and disposal kind of model that came with the industrial era.

Katherine Collins:

A lot of implications there for all types of materials, all types of logistics, all types of consumer oriented companies, really thinking about that full life cycle has implications across almost every type of business that we look at. A second main area of focus is thinking about natural solutions and biological solutions. Almost everything that we invented synthetic, mostly hydrocarbon based chemicals in the last century, can be solved and solved potentially better with biological solutions.

Katherine Collins:

So, again, there’s a wide, wide range of implications there across lots of different sectors and products and types of companies. But those are two of many areas on that map. I’ll note that the ethos there again is asking this question, what is needed for thriving? So we’re not looking for innovation or developments that are clever. We see a lot of investment ideas and there are a lot of very successful companies that just do something kind of cool and neat, but maybe not so essential in the grand scheme of the world. Those can be fantastic businesses, sometimes they can be fantastic investments.

Katherine Collins:

But there’s a much rarer tier of companies that I would put in the wise category. These are companies that are doing something truly innovative, but they’re doing it with a care and attention to the longterm that we’ve been talking about today, that really might create some essential foundational capabilities in the world that didn’t exist before. “Ooh!”, When you see that kind of opportunity, that is a really exciting one. Not without risk, for sure if that care isn’t there, it can be disastrous, but boy, when those things combine, it can be really powerful. So that’s what we’re seeing in terms of themes and some of the areas that we’re focused on from an investment perspective.

Governor Deval Patrick:

For all of those executives and all of us and lots and lots of other people to your second question, Anna Marie, sorting out what it means to have rigor around environmental, social, and governance standards has to be understood as more than compliant. Compliance is important, that’s not what I’m saying. But what it is you’re doing to lead, what it is you’re doing to stretch, and how intentional you are about that, as distinct from having a bragging point or a marketing detail on the side, is the sort of thing we are looking for.

Governor Deval Patrick:

I’ll say just one last thing. My team is tired of hearing me say that I am... But I will say “I am confident that there is a regular way widget company out there, that hasn’t thought at all about ESG or sustainability potential. Where a private equity investor with the right team and the right executive leadership could take that widget company, and turn it into a high impact enterprise.” One day we will start to do that. When we start to do that and show that it can be done and they can generate alpha on the financial side as well as on the impact side, everything changes.

Anna Marie Wagner:

I love that Governor Patrick we’ve actually observed the same thing from our standpoint where Katherine, you mentioned earlier that biology can impact just about everything. But I’ve gone and I’ve spoken at chemical conferences, and they’re full of oil executives from Texas, who’ve never thought about biology in their industry, had “How could that be implied?” So Governor Patrick, I think you’re absolutely right, there are so many industries where from our perspective and kind of an environmental solution... Which may actually have a real business and long-term kind of strategic impact as well. It just isn’t even on the radar yet, but could in fact be one of the most important strategic business drivers for these companies going forward.

Anna Marie Wagner:

I get really excited as well about finding those pockets that just haven’t even thought about it yet. Finding a way to demonstrate the value, and take these very large established industries, and help drive impact there. That’s certainly one of the core sort of tenants and values of what we’re doing at Ginkgo. So I have really appreciated you being a sounding board to us and to the industry more broadly. I can’t thank you both enough for joining us today. I think you’re both luminaries in this field and innovators in the field, and are clearly having an impact far beyond your funds. So thank you so much for joining us this afternoon and wish you the best.

Governor Deval Patrick:

Great to be with you.

Katherine Collins:

[crosstalk 00:15:12] with you. What a joy.

Governor Deval Patrick:

Take good care.

Financials and Model

Anna Marie Wagner:

So you just saw how care is really embodied in how we think about the platform. And it’s really not just because we think it’s the right thing to do, although of course we do, but it’s because we really believe that this is critical to building a sustainable business. And so we wanted to follow these sessions about care, with the session about our financial performance. So for the final session today, I wanted to introduce our CFO, Mark Dmytruk, and then virtually our CAO, Chief Accounting Officer Marie Fallon, who couldn’t be with us in person today and talk about how this business model has matured and evolved and answer some of the questions that I know you and I get a lot from investors and try to shed a little bit more light on those topics. So thanks for joining us, Mark. Can you share a little bit about your background?

Mark Dmytruk:

Yeah, sure. Happy to do that. So I joined Ginkgo as a new CFO about six months ago, and I’ve spent about the past 20 years in the Life Science space. I spent 10 years with Thermo Fisher Scientific and then the past almost 10 years with Syneos Health, the global CRO contract research organization, serving the biopharma industry. And then prior to all of that, I had a career with Ernst and Young.

Anna Marie Wagner:

Okay. And then Marie, who’s joining us virtually. Could you introduce yourself quickly for everybody?

Marie Fallon:

Absolutely. And I’m sorry I couldn’t be there with you in person. Marie Fallon. I work here at Ginkgo. I’m the Chief Accounting Officer. Prior to this, I have been at big institutional companies in controllership roles, a variety of different roles, focused on accounting, reporting, internal controls. Prior to that, I was with Ernst and Young for 10 years as a senior auditor.

Anna Marie Wagner:

Okay well, I know I for one am very glad that you joined us and you’ve been a great asset to the team. So I thought, sort of selfishly, I get asked a lot of questions by investors and thought we could use this time to help bring a little bit of color to those. And to set the stage, we obviously have these kind of two core elements of our business model, the first being the Foundry Revenue, which is just as customers pay us to use the platform on sort of a usage basis, but then we have this downstream value component. And part of that is a sort of a more traditional milestone and royalty model, which you can ascribe a value to, through some projection modeling.

Anna Marie Wagner:

But then we also have this equity component for some of our transactions, which we’ll accept in lieu of a royalty, particularly with earlier stage companies. And, and the, the interesting thing about those is we can look at the historical data that we have on how third-party investors have put a value on that. And that really does help us think about the kind of cumulative value of these programs on a combined basis. And so, one of the questions that I get sort of on this point is how do we think about the margin profile of the business, given the kind of difference in timing in these different elements of the model?

Mark Dmytruk:

So the first thing that you have to recognize is that the numbers you’re looking at both historically and in our projection period, are only the Foundry Revenue line. And so all of that downstream value share that we’ve been talking about, as you know, that’ll contribute ultimately at a 100% contribution margin when it flows through, none of that is-

Anna Marie Wagner:

Because we are done doing the work at that point.

Mark Dmytruk:

Exactly. Yeah. And so none of that is in the numbers and therefore in the margins that you’re looking at. So, but just to talk about the Foundry Revenue line, so you can see that we are projecting that by 2024, we’ll be approaching breakeven on the EBITDA line. I would expect that it would mature into a 20 to 30% EBITDA business line.

Anna Marie Wagner:

Sorry, why 20 to 30%?

Mark Dmytruk:

Yeah. So it’s a very typical margin profile of a life science tools company or a pharma services company. And I’ve worked in those two industries for the past 20 years. And so that’s the Foundry Revenue line. And then the question really becomes, okay, how do you then think about the downstream value contribution? And so the way we think about it internally is we do factor that downstream value share in when we think about the pro forma sort of economics and margin of a particular program. So when we sign a new customer on for a new program and, just to take an illustrative example, let’s just say that we’ve got a program that is going to cost us $4 million of work to deliver over the next, call it two years. And so our fully burdened costs $4 million, we would charge the client $5 million of Foundry usage revenue for that-

Anna Marie Wagner:

And that’s that 20% EBITDA margin for that kind of business.

Mark Dmytruk:

In the sort of mature stage for Ginkgo, we would have a 20% EBITDA margin. And that’s exactly the five million less the four. And so that’s your Foundry Revenue. And then on top of that, we would negotiate a downstream value share. And today based on the data that we have, we are seeing that the downstream value share is worth about a $15 million net present value per program.

Anna Marie Wagner:

And what does net present value mean? How do we get those numbers? What do they represent?

Mark Dmytruk:

So the 15 million net present value is a risk adjusted NPV. And so we have looked at the probability of both technical success and commercial success. And so we are not saying that every program will be commercially successful, but once you risk adjust for that, the net present value for all programs is $15 million.

Mark Dmytruk:

And how did we come up with the 15?

Anna Marie Wagner:

So that is based on actual experience of programs that are in flight today, and have been over the past couple of years. And it is sort of more specifically calculated with reference to those programs where we have an equity interest. And so the advantage with those is that they are marked to fair market value by third-party investors. So we do have a reference point. We can look at what investors are valuing a particular customer at. We know our percent ownership in that customer. And so we have a reference point to get to the 15 million NPV.

Anna Marie Wagner:

Yeah, and then, so in that way, it’s really not even entirely academic because we... There is, in what you’re saying is, there’s real demand from investors for these kinds of equity positions at a certain value. And that is how we came up with the $15 million number. And so we... It sounds like we’re making a choice, to own those equity positions or royalty streams rather than sort of monetizing them upfront via the customer or their investors.

Mark Dmytruk:

We could, in theory, just sell that equity investment today to one of the third-party investors at that valuation. And then we would be bringing that cash in today. So then to take, just to follow on that, so if you take that example where we have 5 million of revenue for the Foundry Revenue, and then 15 million that we monetize today for the downstream value share, that would be a total cash inflow for that program of $20 million. And that’s on a program that would cost us 4 million to deliver. So then when you look at that margin profile, you’ll see it’s about an 80% contribution margin. And that’s how I think you would expect to see the Ginkgo margin profile trend up to over time.

Anna Marie Wagner:

That seems like a really high margin profile? Why does that feel right to you? What do we look at that makes that feel, sort of on a blended basis, appropriate for the business?

Mark Dmytruk:

Yeah. I mean, it’s certainly higher than what you see in pharma services or life science tools, but more comparable to what you see in software or the biopharma industry where intellectual property is a key component. And so that’s the core... One of the core features of the Ginkgo business model is that we are bringing intellectual property via our code base, and also our Foundry capability to a client. And so we’re able to negotiate those kinds of downstream value economics, more comparable with those other industries.

Anna Marie Wagner:

So this whole conversation about what is equity worth today, and could we monetize it now versus later? It sort of reminds me of another question that I got asked a lot, which is when would we choose to eventually sell down an equity position that we might own? Why would we do it this year versus next year? Will we hold it forever? How do you think about that?

Mark Dmytruk:

So, I think the short answer, that’s something that we will be evaluating over time, but the short answer is as long as Ginkgo is continuing to contribute value to that customer, we would look to hold on to our equity interest in that customer. And so we do expect to expand the number of programs with many of our clients. And so if the customer reaches a point where the work that we’ve done, the organisms that we have transferred over are fully in the market. And at that point in time, the equity value in what we’ve created is fully realized. Then that would be at the point at time at which we would look to be downselling our position or exiting an equity position.

Anna Marie Wagner:

So with these multiple components of our business model, obviously there can be some complexity on how and when it shows up on the P&L. So I thought it’d be helpful for Marie to just walk us through some of the accounting. Marie, can you help investors understand sort of what they’ll see over time as the model matures, and as these downstream value elements start being realized?

Marie Fallon:

Sure. So royalty and milestone-based revenues, those are the more traditional revenue streams that most of you are probably familiar with. The equity stakes, that is a little bit different. Ginkgo is a little bit different in that. You may or may not see that equity on our balance sheet. That’s because of the accounting rules and whether the nature of the company is a public company or a private company, but you certainly will see the value of that equity come through downstream when we sell the shares. That could come through as other income or revenue at that time. But because it is so unique, it’s a little bit difficult to forecast. From a fulsome accounting perspective, it’s difficult to see that in advance. But for that reason, we’re going to continue to provide more information and more clarity throughout the course of this process to help you become more acclimated with it, since it is a bit unusual.

Anna Marie Wagner:

So how would an investor, if it’s not going to show up on our balance sheet, how would investors be able to think about the value of programs where we might have an equity position? What can they look at?

Mark Dmytruk:

So a couple of things. First of all, you should look at our program counts, and that’s a key metric. We’re going to be talking a lot about how many programs, how many new programs have we signed up in this time period this quarter, or this year, and what’s our cumulative program count, because remember, even if we’re done performing R and D services for a given program, we still have a right to either a royalty or an equity interest. And so the cumulative program count is an important metric. And then the 15 million net present value number that we’ve talked about. Again, that’s based on real data and historical data, but we will have more experience with that data point as well in time.

Anna Marie Wagner:

So with that... I think that was a really helpful overview of some of the questions that I get a lot and I know you get a lot from investors. Maybe now we can just flip to a quick review of the historical financials. I’ll pass that to Marie too, to help walk us through that. Marie?

Marie Fallon:

So in 2020, we increased total revenues to $77 million from $54 million in 2019, 40% growth. The drivers of that growth included our increase in Foundry Revenues, as well as the launch of our bio-security offering. Again, Foundry Revenues represent what we get paid from customers for usage on those Foundry programs. This is the most predictable component of our revenue. And we typically earn Foundry Revenue from a particular program over the course of two to three years. We increased the total number of active programs, generating revenue from 36 in 2019 to 49 in 2020. And that is despite the impact from COVID. This includes 18 new programs in 2020. And in total, we worked with 22 active customers. Our loss from operations in 2020 increased to $137 million. That’s driven mostly because of our higher R and D expenses, but those higher R and D expenses supported the growth in Foundry operations, as well as enhancements in Foundry and the code base assets, and of course, the development of this biosecurity offering. We ended 2020 with about $380 million cash in hand.

Anna Marie Wagner:

So then let’s talk a little bit about how we thought about you internally building up the projections for the business, both for 2021 of course, but then the longer term projections. How do you think about it? What gives you confidence in those numbers and what should we be looking for?

Mark Dmytruk:

Yeah, so if you look at our projections in 2021, we’re expecting $150 million of total revenue, and that comprises about a $100 million of Foundry Revenue and $50 million of biosecurity revenue. And we based the 2021 projections on two areas where we had high confidence, which was the firstly number of programs that were already in backlog. And therefore we have to just execute against those, but the budgets have been established and the work had already been signed up with the client. And then secondly, the conversion in the near term of a portion of our pipeline, which was most probable. And so that’s really what 2021 is based on. We just... Because of the nature of our business, we have pretty good visibility into the next 18 months of revenue at any given point in time. And that’s just because of the programs that have been signed plus there’s a relatively long sales cycle in our programs. And so we sort of know what’s realistic in the next 18 months.

Mark Dmytruk:

Now, when you go outside of 18 months in the longer term, you can see that by 2025, we’re expecting to be bringing on at that point in time, about 500 new programs on an annual basis onto the platform. Seems like a big number when you look at what we’re doing today, and it is a large increase. However, when you triangulated against the total number of R&D projects that are being done today, that could be done on the Ginkgo platform, it’s really a very small market share. When you then kind of layer onto that the fact that Ginkgo is participating across all industry verticals, it’s not just biopharma R and D projects that we’re trying to bring onto the platform, the agriculture, the food tech, et cetera, et cetera, just the vast kind of addressable market, we again get confidence in that 500 number.

Mark Dmytruk:

And then finally, again, just as a reminder, with each new program that comes on the platform, we improve our cost structure because of the Foundry scale economic. That’s an improvement we expect to be passing along to our customers in terms of some of those cost savings. And secondly, we... The code base gets more valuable. And so we think when you look at the whole picture together, we think that the 500 program count by 2025 is very achievable. And then just to give you kind of a footnote before we wrap up on financials, really just two points. The first is that the projections are reminder, the projections I just discussed do not include any downstream value share revenue, income, or cash flows. And then the second footnote is around our bio-security revenue. You’ll see that we are not projecting out our bio-security revenue beyond 2021. The 2021 projection of $50 million is based really on just the bookings that we have to date and because of the significant uncertainty and how that market is going to develop, we just felt at best not to try to predict it.

Mark Dmytruk:

However, we do believe there is a long-term business in biosecurity. We believe we’re well positioned to be a leader in that business. And as soon as we have more sort of definition on how that market is evolving, we would anticipate providing projections on how that will trend as well.

Anna Marie Wagner:

Well, thanks again, Mark, for joining me here and helping answer some of the questions that we get a lot from investors. We’re going to flip over now to doing the Q&A. So if you haven’t already, feel free to submit any questions via the open exchange platform or via Twitter at Ginkgo. I’m assembling those and we’re going to turn over in just a moment to the executive team that you’ve met over the past few hours to answer as many of those questions as possible. Thanks so much again for joining us and we look forward to hosting you in person, hopefully again soon.

Harry Sloan:

Well, that was pretty impressive. Hi, I’m Harry Sloan from Soaring Eagle. And thank you for joining us the last couple of hours. And you’ve had a chance to learn about Ginkgo’s technology platform, and it’s very disruptive model. We at Soaring Eagle, we’re attracted to Ginkgo, because we see it as a true category of one company. And that’s a company that’s not only the leader in its field, but is actually the creator of the field itself, which is synthetic biology. We’ve partnered on this deal with Dr. Arie Belldegrun. He’s a leader in the field of cell and gene therapy. And we believe that our team at Soaring Eagle is uniquely positioned to lead this investment into Ginkgo.

Harry Sloan:

Over the last few months, we’ve been so impressed with the sense of mission shared not only by the five founders, but all the employees we’ve met at Ginkgo. You’ve now had an opportunity to meet this team and learn more about the company they have built and they’ll continue to build. So we’re excited to significantly capitalize this company for growth, building on the truly unique platform of the Foundry, the code base and again, this incredibly talented team. We’re confident about the value we believe Ginkgo will create not only for the investors, but also for the world, driving health and sustainability at a global level. Again, I thank you all for attending.

Jason Kelly:

Well, thanks for spending a few hours with us today for Ginkgo’s first investor day. I think as a mission driven company with a long-term vision, we’ve been really fortunate in the investors we’ve had to date who really believed in that vision, believed in the team that was pulling it together. We’re excited for a new phase as we take the company public and bring along a whole new set of investors that share our vision for how biology can change the world. So, thanks again.

Outro with Jason Kelly

Jason Kelly:

Well, thanks for spending a few hours with us today for Ginkgo’s first Investor Day. Ginkgo is a mission-driven company with a long-term vision. We’ve been really fortunate in the investors we’ve had to date who really believed in that vision, believed in the team that was pulling it together. We’re excited for a new phase as we take the company public and bring along a whole new set of investors that share our vision for how biology can change the world. So, thanks again.

Question & Answer Session

Anna Marie Wagner:

All right. Welcome back, everybody, and thanks for staying with us for the last few hours for our very first investor day. I’m thrilled to be here with my friends and colleagues at Ginkgo whom you just heard from over the past few hours, who are going to answer some of the questions that have come in through the platform and via Twitter. And so Jason, there was one that came in that was one of my favorites. So, I’m going to throw the first one to you. Vince on Twitter says, “Whilst listening to SRNG at Ginkgo’s investor day, pretty sure 95% of investors have no idea what these people are talking about, even though they’re trying to explain the science. Everyone is waiting to hear, the business revenue potential as opposed to the science behind Ginkgo.” And then Costa Michailidis says, “Can you cover the basics in your own words? What does Ginkgo sell to which customer, for what cost? Like, what’s the business model in a couple of sentences?” So I’m going to give you 30 seconds. Let’s see if you can do it there.

Jason Kelly:

Awesome. I love it. So, yeah. The core idea behind Ginkgo is cells run on digital code in the form of DNA. Kind of like computers run on zeros and ones, cells run on ADCs and Gs. Because you can program them, we should expect there’s going to be app developers, right? Folks who want to program cells to do new things, take those to market and make money doing it. Ginkgo, simply we’re an app store, right? We provide tools to folks that want to program cells to do new things, to make it easier and faster for them to do it. And then we help them bring those cells to market and in exchange for that, they pay us. They pay us both while we’re developing the cell and just like you would in a mobile phone app store, we get a piece of the value of the app. And that’s how we make money.

Anna Marie Wagner:

That was pretty close to 30 seconds. I’ll give it to you. And then on StockTwits here, OddMarketableSecurity says, “Fancy video with lots of fancy words. Some fancy words I haven’t heard them say. 15 billion and 150 million of revs. They’re doing a lot of talking to not address the elephant in the room.” So, let’s address the elephant in the room. How do we get to a $15 billion valuation with $150 million of revenue this year?

Jason Kelly:

Yeah. This comes back to ... I’ll touch on this app store idea again here. So, there’s two ways we get paid. We get paid while we’re developing a cell for a customer. They pay us effectively fees for using the facility I’m sitting in front of and that Barry and Kristen walked through earlier, our Foundry, on a usage basis. Right? So, in 2021, we guide towards a hundred million out of that 150 is foundry revenue from using that facility. Okay? Straightforward to understand.

Jason Kelly:

The app store side of the business, though, ultimately we are going to get a piece of the value of those programmed cells for customers back to Ginkgo. That’s a new idea in biotech. It’s actually been a very, very successful business model in tech, but in biotech, you haven’t really seen it. People tend to develop their own apps, right? If you’re a Genentech or a Roche, you’ve got a drug, you own that thing a hundred percent, you’re really a product company. Well, Ginkgo’s not a product company; we’re a platform. And so when these apps get developed, we get a piece either through royalties or through equity in the companies that are developing those applications. And that comes back to us in the long run, right? So in the near term, that’s not where the revenues are coming, but over time as those apps go to market, that’s going to be in my view, the lion’s share of the value of the company.

Jason Kelly:

And that’s not included, if you look at our projection in the financial model, you know, you and Mark walked through this in the video that’s all Foundry revenue. It doesn’t include that value coming back to us through royalties or equity in the applications. And so, if you look at our numbers, we ended last year with 48 cell programs like that. We’re adding 23 new programs this year, seven just in the first quarter. The rate we’re adding these is going up dramatically. And when you see news, for example, last week, Motif FoodWorks announced a more than $250 million fundraise. That’s great news for Ginkgo shareholders, because we have a good chunk of equity in Motif, because they’re an app developer on our platform. When Kronos says they’re going to market with a cannabinoid, that’s good news for Ginkgo, right? And so, that’s the part of it that ultimately is justifying the $15 billion valuation. It’s really where the majority of the value of Ginkgo is going to come from in the future; that app store.

Anna Marie Wagner:

Great. Thanks, Jason. So a bunch of questions have come in on the platform around ... you know, I think folks who are building their models and trying to kind of get under the hood and get under the weeds. And so, Mark, I was hoping ... One of the topics we didn’t cover in the last session was really some of the underlying drivers of the model in both the foundry business and the downstream. How would you guide people towards their sort of modeling endeavors around this business?

Mark Dmytruk:

Yeah. So I guess the way that we think about it is we start with foundry capacity and our ability to improve throughput in that capacity. And so, as you know, and as we’ve discussed, one of the tenets of our strategy is to get more programs on the foundry. As we get more programs on the foundry, that drives a foundry scale economic. It also pushes us to make investments in technology, which gives us productivity improvements. And so you start with foundry capacity and how much of that do we have, and how quickly can we add to that? We’re then sort of focused in getting more programs on the foundry. That drives a scale economic. That builds code base. All of that in turn enhances the value proposition. That scale economic results in a cost savings that we can pass on to our customers, and so we do that. It also, like I said, enhances the code base, which makes what we’re offering more valuable, and it makes the next project easier and faster.

Mark Dmytruk:

And so collectively over time, and we’ve talked about that flywheel, what you see is the revenue is increasing and us taking on more programs, and the overall company profitability starts to improve. And as you’ve seen, we’re expecting to start approaching breakeven on the EBITDA line around end of 2024, sort of roughly speaking. And what you’re seeing there in terms of a driver is really, we’re just leveraging our R&D and [inaudible] infrastructure on a higher revenue base. And none of that includes the downstream value shares. So the other sort of core driver of the business is that you will start to see the monetization of either royalty or equity interests also contributing to the bottom line.

Anna Marie Wagner:

Great. Thanks, Mark. So, you mentioned that the sort of first element of the model is capacity. Barry, you talked a lot about Knight’s Law. I think folks find that concept really interesting, but how the hell do we keep Knight’s Law going, and what gives you confidence that we can maintain that going forward? What are the top challenges that you see?

Barry Canton:

Great question. One we always like to talk about, first of all, I have to say that neither I nor anyone at Ginkgo can predict the future, but I’ll note that neither could Gordon Moore in 1965, when he made the prediction that ultimately became the Moore’s Law that we know today. Instead, he saw a trend, which we have seen, and we have shown you all. And he saw no fundamental physical reason why that trend could not continue. All that was required was continuing investment driven by tremendous commercial opportunity, and we believe that the exact same conditions are true today in synthetic biology. So, we just need to do the work.

Barry Canton:

To be more practical about the answer, Knight’s law is driven by automation and miniaturization of the way we do the work in our Foundries. We have a lot of low-hanging fruit still to be captured or still to be collected in terms of how we do that work and how we automate it. And that’s just using the technologies that are mature and available to us today. As we work with our partners, folks like Twist and Berkeley Lights, and as we see how their technologies are improving, we can see how we’re going to be able to continue to increase the scale and drive down the unit costs of the work in our foundries. So in the midterm, we look at those kinds of technologies for better DNA printing, better measurement of how cells are performing, greater miniaturization as being the drivers of Knight’s Law. And then as we look to the longer term, the reality is that cells and DNA are really, really tiny and they make copies of themselves very easily. And so what that points to is the ability for us to really miniaturize our operations and our work down to the scale of individual cells and molecules. And in the kind of multiplex, library-based work we do already, we’re able to realize that potential in certain cases today and in the future, in many cases or most of the cases of the projects that we work on. So we see both near, mid and long-term ways to continue to drive the scale and the efficiencies that are going to drive Knight’s Law.

Anna Marie Wagner:

Great. Thanks. Thanks, Barry. And Patrick, I think codebase is always an interesting topic for folks and it definitely is part of Knight’s Law, but we don’t have the same kind of historical metrics that we’ve been able to plot out for people around codebase. And so we get a lot of questions around how do you measure codebase? What metrics should we be looking for? What are you going to report on? And so I’d love you to just talk a little bit about, as the head of codebase, how you think about measuring codebase and really what matters there.

Patrick Boyle :

Yeah. That’s a great question. And I think we’re still trying to wrap our heads around codebase on how best to quantify it. But for us, there are kind of two key factors that we try to keep a track of. One is just sheer quantity. And that’s really where we leverage the scale of the foundry to make sure that we’re basically sourcing, generating and characterizing as much unique biology as we can year over year. So from my perspective, we actually rely a lot on Knight’s Law to say if we are actually scaling the ability of the foundry to improve the number of operations we can do year over year, for my perspective, that means we can continue to drive the quantity of new codebase that we can develop.

Patrick Boyle :

Now, how do we use that to actually help our customers achieve their goals faster? That’s where quality comes in. And one of the metrics we use for quality is how often are we actually reusing particular codebase assets. Some really important stuff sits on the shelf for a year or more before we find the right opportunity to reuse it, but certain things we go back to over and over again. And that’s what we’re trying to really quantify into what we’re calling cell development kits, basically playbooks that we can apply over and over again, reusing a valuable codebase that has been proven over the course of multiple projects. So again Knight’s Law means that we can really deliver on quantity and mine through that for useful information and useful new strategies and designs, but ultimately, reuse is how we measure quality and something that we pay a lot of attention to.

Anna Marie Wagner:

Great. Thanks. So maybe then wrapping up the [crosstalk]... Oh. Go ahead.

Jason Kelly:

[crosstalk]. Patrick, I think that CDK is an inspired name. So this is coming out of software development kits. And as I understand it, this is part of the package you get as part of engaging with a mobile phone ecosystem. If you want to develop an app, you get from Apple an SDK and it helps you put the button on the phone in the right place. It’s existing code that makes it easier to launch an application. And in exchange for that, because that’s a valuable thing for a developer, Apple’s getting to take a toll on those apps that get developed. And so this is very much in line, even the naming of things here, this idea of the CDK. We think the evolution of genetic engineering and cell programming, we’re taking lessons from software to do it. And I think this is what I’m really excited about is these CDKs.

Anna Marie Wagner:

Thanks, guys. So just rounding out the capacity topic, an important driver of our capacity is also just our operations and how well we function together as a team. Obviously, folks have seen our sort of vision for the future and that involves a lot of growth. So Reshma, I’d love – and this is my own question, it didn’t get submitted, I just like it and like talking about it — I’d love to just ask you what you see as the biggest kind of operational hurdles and how you think about scaling up an organization like Ginkgo over the next four or five years.

Reshma Shetty:

Yeah. I think we really think about the challenges of scaling on sort of two fronts. The first is really around our culture. So we talk a lot here at Ginkgo about growing our culture. And that’s because for a mission driven company like Ginkgo, our team is fundamental and instrumental to Ginkgo’s success overall. And the biggest impact we can have on our team is really fostering a culture here at Ginkgo that helps us attract the best talent, retain the best talent. And really, I think at the end of the day, culture has a huge outsized influence on that team’s performance. And again, team performance equals Ginkgo success. And so we really like to think about our culture as not just who we are today, but who we aspire to be. And so continuing to grow our culture as we grow the company, I think is fundamental to being able to scale effectively.

Reshma Shetty:

I think the second front that we think about sort of the operational challenges of scaling is really around all the normal things like organizations have to do when they scale. They need to specialize roles. They need to add organizational structure. They need to introduce process. And I think Ben Horowitz actually writes really eloquently on this topic. He talks about how you need to give ground grudgingly to this stuff. And so at Ginkgo, we really try to balance. We know as we grow, we need to add specialization, we need to add process, we need to add structure to our organization, but we don’t want to get ahead of our skis on that, because there’s a cost and an overhead to all of those things. And so striking that right balance of giving ground grudgingly to adding those things to our company as we grow is really important. And we’re really fortunate, because we have members like Christian Henry and Sean [inaudible] who have led fast-growing technology companies, and so they’ve been a great source of advice and guidance as we grow.

Anna Marie Wagner:

Yeah. I totally agree. All right. So kind of going back to Mark’s answer earlier, first input is capacity, then we actually have to go find some demand. So Ena and Jen and Matt, we’re lucky to have you guys on the phone, because you lead our commercial business. So maybe Ena, I’ll start with you. We got a question from Varro Analytics on Twitter, saying, “How far into the future do you generally have visibility on bookings? And what are the limits on that visibility?” And so I might just ask talk about kind of our sales cycle and process and what that looks like at Ginkgo and the visibility that Barrow is asking about.

Ena Cratsenburg:

Yeah. That’s a great question. Thank you for that. So let me start with the deal process to really kind of provide a bit of context to that question. So when we work with a potential customer on a project, we really start with a collaborative process. We sit down with our customers to define what are their strategic requirements. And from that we define the specific technical needs and how our foundry can actually support that. And that’s when we get kind of the early start of really figuring out what the project looks like. Then we enter into a parallel path of the technical teams really discussing with our customer’s technical team on the specific requirements under what we call a technical development plan. And in that technical development plan, we’ll define the deliverables, the milestones, the objectives, the timeline, et cetera, and the budget associated with those programs.

Ena Cratsenburg:

And at the same time, the commercial discussions also take place. And we have a cross-functional deal team that really kind of drive those discussions forward, going from figuring out what the framing of the deal looks like, what the term sheet looks like, all the way to negotiating the final terms of the agreement. That includes all aspects ranging from economics and intellectual property terms. So once we complete that negotiation process and the technical teams have a defined and approved TDP in place, we then kick off the project. And that’s where the commercial operations team really kind of takes center stage and liaise with the customer to not only implement the collaboration internally, it can go, but also to foster the communications to make sure that the collaboration is as transparent and as successful as possible.

Ena Cratsenburg:

So that deal process is not a two-week process. It takes time to make that happen. And so we have a number of deals that are moving through the deal process in any single point in time. And we’re constantly monitoring and reviewing the status of these deal negotiations as they move through the different stages in the pipeline. And the pipeline includes deals that are ranging from very mature conversations, where we’re in deep discussions on the definitive agreement, all the way to early stage conversations, where we just signed a CBA with a customer and

Ena Cratsenburg:

And trying to figure out what the projects are that we will collaborate together and you have everything in between. So during this process, as we get more and more visibility into the technical development plan and understand what our deliverables would be, we have better indication of what our revenues would look like because by the time the TDPs are in place, we have very good visibility into the revenues that we would expect.

Anna Marie Wagner:

Great. Thanks, Ena. So, that’s the first half of the question, which is like, how do we win customers? And then we have to actually deliver for customers. So, Jen, you in the past ran our commercial operations team, and now you run both commercial operations as well as business development. And so we’ve got a couple of questions on scale up and sort of customer success. So from, I’m not even to try to pronounce this person’s name on Twitter, Toftgaard, I think: “What do you do to ensure a successful scale up to commercial production? Do you have pilot facilities or do you leave all that to the customers?” And then from DominicDo2 on Twitter: “The bottom line, how fast can you scale a molecule, at what size tank, how many molecules have you scaled at what size production? This is the bottleneck for synthetic biology. So how are you doing on it?”

Jennifer Wipf:

Sure. So Jason mentioned earlier that we share in a piece of the value for the programs we work on for our customers, so that means we don’t just send over a vile of engineered organisms and say, good luck. Instead, we have a deployment team that has expertise in fermentation scale up, downstream process development, QA QC. And so they work both in the lab we have here in Boston, at headquarters, also with some mid-scale pilot partners that we have, and also a contract manufacturing organization we have a tolling arrangement for some products that we do make ourselves. And so that team has worked on a variety of commercialization efforts, so we’ve scaled a number of compounds, including flavors and fragrances, proteins, other chemicals, many of which are on the market today.

Jennifer Wipf:

You talked about what to what scales, so that’s highly dependent on the product that we’re making. And so production scale is relative to the customer. On the very high end, we’ve scaled up processes up to several hundred thousand liters and some higher value compounds production scale is some might think it’s quite small. So we work with customers in different ways because our customers have a variety of expertise in production themselves. So that might mean that we’re transferring processes directly to them, to their pilot facilities or their production facilities. That might mean we’re partnering with them to find sort of a supply chain manufacturing company that would work for them. In some cases, they’re on the market to buy a facility themselves and we’ve helped them do that as well. So a variety of models that we work with customers. They’re all oriented around getting products to market.

Jennifer Wipf:

And then you asked a question about how fast is this. I think time is highly dependent on scale, familiarity with the processes, what the capital requirements are, if people have a facility themselves. And so because we work on such a wide variety, it’s hard to answer that directly. We do have a couple tricks up our sleeve to speed that up. One of that is that we have a iterative nature of engineering organisms. So often we’re able to transfer intermediate strains that they can start working with right away. And that both gives us feedback back into our engineering process, as well as speeds up the scale up to commercialization.

Anna Marie Wagner:

Great. Thanks guys. Yeah, go ahead, Jason.

Jason Kelly:

Got one small bit to it, just again to hammer home this idea of the app store, right? So one of the things you’re going to get on the tech side by participating in an app store ecosystem is they’re going to help you with distribution, right? Because they want your app to get out to as many customers as possible because the mobile phone company is going to be collecting value every time you sell that app, or when someone does a purchase through it. Very much the same, Jen’s team on operations. We want these cells to go to market because Ginkgo is going to get value back when they do. So this is like an adjacent capability to our cell programming. It’s kind of like, yeah, Apple gives you the program, the SDK and the distribution, right? Ginkgo’s going to give you the CDK and we’re going to help you with deployment and fermentation through our partner network, right? And that’s a hundred percent in line with our business model here.

Anna Marie Wagner:

Helpful clarity, Jason. You’re getting good at the 30 second explanation. So maybe we won’t get those comments on our next investor day. We love those comments. So thanks Ena and Jen for the help understanding sort of how we work with our customers and come up with those collaborations. Maybe just, we can now touch on a couple areas of growth that I think are really capturing everyone’s attention. And those two sectors are pharma, which is certainly a real growth area for us, especially over the past year, and then biosecurity. So maybe Ena starting with pharma, we got a question also from Varro Analytics, a lot of questions from Varro Analytics: “what areas can Foundry be most readily applied to right now in the biopharma sector? And what is @Arie_belldegrun’s vision?” Arie is unfortunately not here with us, although we’re thrilled he’s joining the board, but can you talk a little bit about how we’re approaching pharma and what pharmacies’ on our platform right now?

Ena Cratsenburg:

Yeah, definitely. And thank you again for the question. We’re super excited to have Arie on the board. We’re really looking forward to working with him and getting his insights and advice into some of the areas that we’re really excited about. So this is huge for us. There are many, many areas in pharma that we’re really excited about, and it ranges everywhere, from the drug discovery and development process at the front end to the manufacturing process at the tail end, once a drug candidate has been FDA approved. Just to give you an example of some of the projects that we’ve done so far, so in the area of mRNA vaccines, which now we all know how valuable they are and what they can do; we’ve worked with Moderna and we’re working with others as well in the space, in the production of key, raw materials in the manufacturing of mRNA vaccines.

Ena Cratsenburg:

It’s going to be an area that we will continue to focus on. And we’re really excited about the different possibilities of using the platform to improve the manufacturing process for these important therapeutics and life lifesaving therapeutics in many instances, especially as those are being used for cancer. We have a deal that we announced not too long ago with Biogen, where we are developing a next gen AAV production platform for gene therapy. And that’s a really exciting area for us to be digging deep into. We previously have signed a deal with Roche where we use our genome mining platform to discover novel antibiotics. So that is less in the manufacturing side, and more in the upfront drug discovery and development side. And along the same category of drug discovery and development, during COVID we worked with a small AI enabled drug discovery company called Totient. They are now acquired by AbSci, where we used our Foundry to help express and screen thousands of antibody candidates that they have uncovered during their computational process and find those that are neutralizing against COVID-19. So that’s an exciting area that we look to do more in, in the antibody discovery and development area. We’re also working with others to improve the manufacturing of APIs, small molecules and biologics, and we’re also excited about cell therapy. There’s a lot we can do in the area of cell therapy, whether it is to optimize the car constructs, to make them ultimately more efficacious and more manufacturable, as well as working with manufacturers of cell therapy to help make their process more robust. So the way we see pharma is that as the pharma sector continues to use biology as a way to develop novel therapeutics or discover or improve these newer modalities, we’ll continue to see new applications of the Ginkgo foundry to help solve specific biology cell programming problems. And what we’re seeing is precisely that. As more of these new pharma companies and big pharma companies are looking for specific ways to address the near-term challenges, they now see that cell programming is a very valuable enabler to help them get to their ultimate goals.

Anna Marie Wagner:

And I was on mute.

Anna Marie Wagner:

... it’s never, never too late in the pandemic to figure out how to unmute yourself. So that’s one really important growth area for us of course. Thank you, Ena. The second area that’s obviously been the newer and really impactful is biosecurity and specifically this year, K12 testing. So Matt, I’d love you to talk about... Another elephant in the room, I think, is like, “What happens to biosecurity when COVID’s over?” I think we’re all hoping and praying that life gets back to normal. What happens to this business in 2022, 2023?

Matthew McKnight:

Yeah. Thanks, Anna Marie. And look, I think this is... The first part of this is everybody’s experienced. So I think it’s very clear that globally COVID has shown us the need for this forward-thinking technology first integrated approach to biosecurity. Biology has caused massive, massive damage over the last year and it’s something that we feel very strongly and have been working on as a team for the last 15 months that we can do something to help. But that’s a pandemic moment. The second piece that’s really important, if you think about building a biological engineering platform, doing what we are doing, building an app store, and you use the digital revolution as a metaphor, cybersecurity is a massive business to enable the digital ecosystem to work.

Matthew McKnight:

There will be a massive industry at some point in biosecurity to power this biological manufacturing revolution. That is something that we feel very strongly about from a platform standpoint, that because biology is so powerful, we also need to be building the tools of biosecurity for that purpose. So for us, there’s this two-sided mission orientation to build the platform in a secure and transparent and caring way with biosecurity tools, but also to help respond to pandemics. This is not the last pathogen that will have pandemic potential. And so the direct question, though, of what happens to the businesses is really an interesting one. It’s pretty clear to us it’s a matter of scale and timing, not really whether it will develop.

Matthew McKnight:

We’re seeing indications that governments are taking the response to this pandemic very seriously. Private companies are thinking about what biosecurity looks like. In the US alone, we think that kind of the reports are $16 trillion of economic output, GDP lost due to this pandemic. People are saying we should spend 20 to $ 40 billion a year to protect the world from the next pandemic. We’re one of the major providers of K12 surveillance testing across the country, something that’s a new thing that people haven’t done in the past. So we’re excited about it, but we’re also cautious, because we’re still in the midst of the pandemic. So from a standpoint of what we’re looking at, how we’re thinking about it, how we’re guiding our partners and otherwise, it’s both of those, excited, important long-term mission component and being cautious about setting how and at what time that will become a really large and robust market. But ultimately something that we care deeply about and are spending a lot of time on.

Anna Marie Wagner:

Thanks, Matt. And second element of care that’s, I think, really important to us relates to a really nice question that we got in that says, “How and where do you draw the line with requests either from...” And this is for you, Jason. “From either commercial or government sources that may raise ethical concerns because of the potential uses from the results. Are you prepared to deny requests that cross that line despite potential revenue losses?”

Jason Kelly:

Yes. This is a super good question. And Matt touched on this, but we do think it’s really important to note that we do care how our platform is used in the world. As we enter an era where you can program cells like you program computers, that’s a big deal. Biology’s responsible for our food, our atmosphere, clean water, as we’re living through this pandemic, our public health. And so starting from a footing that we do care what happens with our platform, it isn’t just as simple as [inaudible] whatever someone pays for. It is an important line to draw. I’ll point out one of the things that was really interesting during COVID, I think people tend... Actually I think Governor Patrick touched on this during the investor day presentation. He said it’s a false choice between doing good and making money, being a successful company. It’s not quite so simple.

Jason Kelly:

I agree with that. I think people frequently imagine, okay, the thing you’re not going to do and not make money doing. But what we also saw during the pandemic is it was so volatile, things were moving so quickly and there were all these questions of like, “Can you do that?” And you would make these decisions to say, “Well, I don’t know. Is it going to get schools open? Is it going to help this thing in society?” And those are caring how your platform’s used too. So it can also be ways that would actually lead to expanding the business if it’s the right thing to do. And so I do think this is an important topic going forward. I’m not going to pretend we have it all figured out. It’s going to be a collective question for society, how we want to deploy engineered biology in the future, but we want to start by saying we care how the platform is used.

Anna Marie Wagner:

Thanks, Jason. So we’re just about out of time. So I’m just going to do a couple more questions. The next set are for me. But I just like the Twitter handles, so I’m going to read them all. And it’s around the process here for this SPAC transaction. So SPACDoggyDog wants to know when we expect the ticker to change to DNA. And then a couple other folks asked what’s the status of the S-4, when do we believe the final one will be filed. So how’s the process going? And when is this expected to close? So nothing at this point would indicate any change in the timing. We’re still expecting to close in the third quarter of this year. We have received the first round of comments from the SEC and would expect to file our first amendment sometime next week. Obviously, we can’t control the timing of SEC review, but still expect that we’ll be closing in the third quarter. But obviously at this point, can’t provide a precise date, but we’ll update folks as that goes.

Anna Marie Wagner:

All right. So last question here is for you, Jason. There are two that are related. So Costa Michailidis wants to know, “How long until I can code up a full-on fire-breathing dragon in my garage? Because!... Then, I can launch my “Dragon Toasted Bagels” business?” And then Chris Oswald would like to know if he can be the first one to fly a dino.

Jason Kelly:

Yeah. So 20 years. Yeah. Yeah.

Anna Marie Wagner:

So that’s [inaudible]. Are you making Chris a promise? [crosstalk]-

Jason Kelly:

Defer to our head of codebase, Patrick, the man who’s designed more synthetic DNA than anyone on planet Earth. Patrick, what’s your estimates on dragon?

Patrick Boyle:

I’ll add a plus or minus five years to that estimate, just to have some error bars, but...

Anna Marie Wagner:

[inaudible]. What did you say, Jason? 20 or 25?.

Jason Kelly:

Yeah. Yeah. 20 [crosstalk] 20 years out.

Anna Marie Wagner:

So 15 to 25 years, Costa will be able to code up a full fire-breathing dragon in his garage and Chris is going to be able to be the first one to fly a dino. Or you’re going to reserve that right?

Jason Kelly:

[crosstalk].

Matthew McKnight:

I think we’ll have to have a charity auction for who gets to.

Anna Marie Wagner:

Why not? I like that. Okay. Charity auction. All right. You heard it here first.

Jason Kelly:

Or you just get a job here at Ginkgo. We have a... Yeah. If you want to fly, be the first one on the dragon, you should be working here. Yeah.

Anna Marie Wagner:

All right. Well, I know we’re about out of time here and everyone spent a lot of time with us today, learning about the business. So just want to say a heartfelt thank you to everybody for joining us today and spending your time learning about Ginkgo. Jason, I don’t know if you have any parting thoughts, but we’re wrapping up, wrapping up the day here, and look forward to being able to host you guys in-person hopefully next year.

Jason Kelly:

Yeah. Thanks, everybody, for the time today, really. It’s wonderful to have a chance to speak with you all.

ADDITIONAL LEGAL INFORMATION

Forward-Looking Statements Legend

This document contains certain forward-looking statements within the meaning of the federal securities laws with respect to the proposed transaction between Ginkgo and Soaring Eagle Acquisition Corp. (“SRNG”), including statements regarding the benefits of the transaction, the anticipated timing of the transaction, the services offered by Ginkgo and the markets in which it operates, and Ginkgo’s projected future results. These forward-looking statements generally are identified by the words “believe,” “project,” “expect,” “anticipate,” “estimate,” “intend,” “strategy,” “future,” “opportunity,” “plan,” “may,” “should,” “will,” “would,” “will be,” “will continue,” “will likely result,” and similar expressions. Forward-looking statements are predictions, projections and other statements about future events that are based on current expectations and assumptions and, as a result, are subject to risks and uncertainties. Many factors could cause actual future events to differ materially from the forward-looking statements in this document, including but not limited to: (i) the risk that the transaction may not be completed in a timely manner or at all, which may adversely affect the price of SRNG’s securities, (ii) the risk that the transaction may not be completed by SRNG’s business combination deadline and the potential failure to obtain an extension of the business combination deadline if sought by SRNG, (iii) the failure to satisfy the conditions to the consummation of the transaction, including the adoption of the agreement and plan of merger by the shareholders of SRNG and Ginkgo, the satisfaction of the minimum trust account amount following redemptions by SRNG’s public shareholders and the receipt of certain governmental and regulatory approvals, (iv) the lack of a third party valuation in determining whether or not to pursue the proposed transaction, (v) the occurrence of any event, change or other circumstance that could give rise to the termination of the agreement and plan of merger, (vi) the effect of the announcement or pendency of the transaction on Ginkgo business relationships, performance, and business generally, (vii) risks that the proposed transaction disrupts current plans of Ginkgo and potential difficulties in Ginkgo employee retention as a result of the proposed transaction, (viii) the outcome of any legal proceedings that may be instituted against Ginkgo or against SRNG related to the agreement and plan of merger or the proposed transaction, (ix) the ability to maintain the listing of SRNG’s securities on Nasdaq, (x) volatility in the price of SRNG’s securities due to a variety of factors, including changes in the competitive and highly regulated industries in which Ginkgo plans to operate, variations in performance across competitors, changes in laws and regulations affecting Ginkgo’s business and changes in the combined capital structure, (xi) the ability to implement business plans, forecasts, and other expectations after the completion of the proposed transaction, and identify and realize additional opportunities, and (xii) the risk of downturns in demand for products using synthetic biology. The foregoing list of factors is not exhaustive. You should carefully consider the foregoing factors and the other risks and uncertainties described in the “Risk Factors” section of SRNG’s proxy statement/prospectus relating to the transaction, and in SRNG’s other filings with the Securities and Exchange Commission (the “SEC”). SRNG and Ginkgo caution that the foregoing list of factors is not exclusive. SRNG and Ginkgo caution readers not to place undue reliance upon any forward-looking statements, which speak only as of the date made. Neither SRNG nor Ginkgo undertake or accept any obligation or undertaking to release publicly any updates or revisions to any forward-looking statements to reflect any change in its expectations or any change in events, conditions or circumstances on which any such statement is based.

Additional Information and Where to Find It

This document relates to a proposed transaction between Ginkgo and SRNG. This document does not constitute an offer to sell or exchange, or the solicitation of an offer to buy or exchange, any securities, nor shall there be any sale of securities in any jurisdiction in which such offer, sale or exchange would be unlawful prior to registration or qualification under the securities laws of any such jurisdiction. In connection with the proposed transaction, SRNG filed a registration statement on Form S-4 with the SEC on May 14, 2021, which included a proxy statement of SRNG and a prospectus of SRNG. The definitive proxy statement/prospectus will be sent to all SRNG shareholders as of the record date to be established for voting on the proposed business combination and Ginkgo stockholders. SRNG also will file other documents regarding the proposed transaction with the SEC. Before making any voting decision, investors and security holders of SRNG and Ginkgo are urged to read the registration statement, the proxy statement/prospectus and all other relevant documents filed or that will be filed with the SEC in connection with the proposed transaction as they become available because they will contain important information about the proposed transaction.

Investors and security holders may obtain free copies of the proxy statement/prospectus and all other relevant documents filed or that will be filed with the SEC by SRNG through the website maintained by the SEC at www.sec.gov. In addition, the documents filed by SRNG may be obtained free of charge by written request to SRNG at 955 Fifth Avenue, New York, NY, 10075, Attention: Eli Baker, Chief Financial Officer, (310) 209-7280.

Participants in Solicitation

SRNG’s and Ginkgo and their respective directors and officers may be deemed to be participants in the solicitation of proxies from SRNG’s stockholders in connection with the proposed transaction.

Information about SRNG’s directors and executive officers and their ownership of SRNG’s securities is set forth in SRNG’s filings with the SEC. To the extent that holdings of SRNG’s securities have changed since the amounts printed in SRNG’s proxy statement, such changes have been or will be reflected on Statements of Change in Ownership on Form 4 filed with the SEC. Additional information regarding the interests of those persons and other persons who may be deemed participants in the proposed transaction may be obtained by reading the proxy statement/prospectus regarding the proposed transaction when it becomes available. You may obtain free copies of these documents as described in the preceding paragraph.