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Hi friends ​​👋,

Happy Monday! 

Last week, I wrote a piece on Optimism that seemed to resonate with a lot of people. Beyond the headlines, there are pretty mind-blowing advances happening across the board – from space to web3 to climate to biotech and beyond. Optimism isn’t blind faith that everything will work out; it’s a belief that by experimenting and accumulating knowledge, humans can overcome the inevitable challenges we’ll face. 

The best way I know to make the world more optimistic is for Not Boring to tell the stories of, and invest in, the people and companies solving those challenges. A lot of those companies work at the cutting edge of science and engineering, so we’ve expanded the Not Boring team by bringing on two Research Analysts who have the technical chops to help make sense of it all: 

• Rahul Rana: Deeptech, Space

• Elliot Hershberg: Biotech 

Elliot and Rahul will work with us at Not Boring Capital, and even better for all of us, write about companies, technologies, and ideas driving their spaces in Not Boring. These fields have the potential to fundamentally change the way we live, and I want Not Boring to be the place that you learn about them. In addition to being technically strong, they’re both excellent writers. You’ll meet Rahul in a few weeks when he publishes his first piece for Not Boring. 

Today, Elliot is going to take us on a journey through the world of synthetic biology by analyzing one of its most innovative companies: Ginkgo Bioworks. Elliot knows what he’s talking about. In addition to writing one of the best biotech newsletters on Substack, The Century of Biology (it’s really good: subscribe now), he’s currently a PhD student in the Department of Genetics at Stanford. It’s rare to find someone so technically strong who’s also so good at communicating what’s happening in his industry and imagining where it might be headed. In today’s piece, you’ll see what I mean. 

Synthetic biology might let humans harness “the awesome power of biology to create an abundant future,” as Elliot writes. Or as a Ginkgo site, syntheticbiology.com, asks: “Imagine a future designed with biology. What if you could grow anything?”

Let’s get to it.

Ginkgo Bioworks: The Organism Company

By Elliot Hershberg

If we were visited by intelligent life from elsewhere in the Universe, what would be the most embarrassing aspect of our current technological capacity? In some ways, it would be hard to pick. Despite the fact that we all carry supercomputers in our pockets, we dig up dead dinosaurs and burn them in combustion engines to power our cars, trains, planes, and cities. To make new molecules—drugs, compounds for agriculture, or any other chemical product—we rely on complex industrial systems that create far more waste than desired. Our approach to construction has escalating costs and can’t scale to support a growing population.

What if we figured out a way to do things differently? What if we found a way to have a more productive relationship with Nature? What if we could learn to grow anything?

This is the vision of synthetic biology. The researchers, engineers, labs, and companies in this discipline are aiming to dramatically change our approach to creating food, materials, chemicals, and physical structures by harnessing the only functioning nanotechnology that we know of: living systems.

Ginkgo Bioworks—The Organism Company—is a leading force in this new field. Their ambitious goal of becoming the first platform company in synthetic biology has generated strong reactions, both positive and negative. In this essay, I want to explore some of the Big Ideas that this company is pursuing, and provide a lens into what could be possible for the broader field of synthetic biology in the future. Today, Ginkgo’s platform is being used to engineer microbes that can be used to make agriculture more sustainable, grow valuable chemicals, and deliver therapeutics in a targeted fashion.

Given the utter insanity of the current markets and the fact that this is a publicly traded company, I want to be absolutely clear: this is not investment advice. My goal is to provide an honest and accurate assessment of the incredibly important experiment that Ginkgo is running for the biotechnology industry.

Here’s a map of where we’re going to go in order to explore this:

• What is synthetic biology?

• How biotechs makes money

• What does The Organism Company do?

• Major open questions 🐻

• An experiment in cooperative work structure

• What will the world look like if Ginkgo succeeds?

Let’s jump in! 🧬🌱

What is synthetic biology?

Let’s talk about circuit design. A good circuit does a few things. It should receive information and perform a computation based on the input to produce a reliable output. Input, computation, output. One of my favorite circuits senses an environmental gradient as input, and computes on that information to determine which set of machines it should turn on or off. I’m not describing a digital circuit; this is a genetic circuit found in Nature called the lac operon.

Think back to high school biology. Remember that cells encode instructions in DNA called genes. These instructions are copied into messenger RNA molecules that ultimately serve as a template for creating proteins, which are the machines that do most of the work inside of cells. In bacterial cells, this simple circuit involves a repressor component (shown in green) that is able to sense the sugar gradient in the cell, and compute on that information to control which set of genes gets turned on. The computation is: if lactose is present, the polymerase (yellow) can bind to the promoter sequence (orange) and turn on the genes to metabolize it. Else, keep the genes turned off.

Learning that these types of genetic circuits exist was a pretty big deal, and the French scientists François Jacob and Jacques Monod nabbed the 1965 Nobel Prize in Physiology for figuring it out. Even this early on, Jacob and Monod postulated that in principle it should be possible to create new circuits by combining regulatory DNA systems in different ways.

In the following decades, we developed several important tools for doing this. Molecular cloning unlocked the ability to assemble new sequences of DNA, and PCR let us make copies of DNA. These technologies led to the birth of genetic engineering, and arguably modern biotechnology at large. Genentech—previously trading under the $DNA stock ticker now held by Ginkgo before operating as a subsidiary of Roche—became a blockbuster success by using genetic engineering to create bacterial cells that produced human insulin.

While this was a defining success for biotech as an industry, the synthesis of insulin represented the peak of design complexity that was possible at the time. But as our ability to modify organisms remained limited, our ability to measure organisms underwent a mindblowing revolution. In 1990, the United States Department of Energy and the National Institutes of Health launched a $3 billion dollar project to sequence the entirety of the DNA bases that make up a human—which we call a genome. This marked the start of one of the craziest cost declines in the history of technology.

Many people in tech are familiar with Moore’s Law, which was the prediction that the number of transistors in a dense integrated circuit doubles about every two years. In practice, this means that we have ended up with computers in our pockets that are more powerful than the room-sized computers scientists used to get to the moon. The graph above—which is used in more than two thirds of genomics lectures—shows how DNA sequencing cost declines massively outperformed that rate. While the first human genome took a decade to sequence and cost $3 billion dollars, graduate students now routinely sequence genomes in a day for only $1,000 dollars or less. In the past few weeks, Ultima Genomics came out of stealth and announced their goal to usher in the $100 genome.

This change in measurement technology was a really big deal. After decades studying individual genes, geneticists began studying thousands of genes at a time. We also learned to adapt some of the fundamental tech to make high-throughput measurements of more parts of the cell, like RNA, metabolites and proteins. This was so transformative that it launched an entire new field called systems biology with the goal of making unifying models describing all of these measurements. As the Stanford bioengineer Markus Covert likes to say, “When I was growing up, biology was the science that you would take if you didn’t want to learn any math. Now that’s not the case anymore.” With a new stack of tools, molecular biology evolved into a quantitative discipline.

Synthetic biology was launched largely in response to this paradigm shift. The goal was to transform genetic engineering into a discipline capable of building new biological circuits from the ground up. The idea was to develop the capacity to engineer new organisms. 

The Century of Biology started with a bang when several studies were published in January 2000 describing the successful development of engineered genetic circuits—finally realizing the vision of Jacob and Monod. Over the last decades, synthetic biology has matured as a discipline, and has started to develop reusable community standards, which has decreased the overhead of launching new projects. One of the best demonstrations of this is iGEM—the International Genetically Engineered Machine competition—where undergraduates and high schoolers around the world compete to implement their best ideas in DNA code. Recent winners have developed new ways to manufacture fragrances, materials, and diagnostics, all using the shared iGEM building blocks.

So, what is synthetic biology? It depends on who you ask. According to Christina Agapakis, it is “the practice of engineering life.” For one of the pioneers of the field named Drew Endy, synthetic biology is focused on a meta-goal: to systematically improve our ability to use biology as an engineering substrate. 

Regardless of how you define it, the field of synthetic biology is comprised of dreamers and doers. The vision expands as far as you can imagine: designing programmable cell therapies, learning how to grow rocket ships and space stations, and bringing woolly mammoths back from extinction. In practice, there is a relentless focus on discovering new molecular tools, scaling DNA synthesis, and creating systems of re-usable standards and components. With the current rate of progress and the boundless possibilities on the horizon, Eric Schmidt has said that “your industry is at the same stage mine was in 40 years ago when I started my career in tech.”

How biotechs make money

So, synthetic biology is focused on learning how to build things using biology. Before analyzing Ginkgo, it’s also important to think about how the biotech industry makes money. By and large, the revenue that flows through the ecosystem comes from selling drugs.

This seems like a simple statement, but it has non-obvious implications. Drugs are a very unique product. They require an enormous amount of R&D, and have to make it through many expensive hurdles to demonstrate efficacy and safety before being approved. After all of this time and cost there is another problem: the actual chemicals can be manufactured incredibly cheaply, which is why generic versions of drugs can be sold for as low as a dollar a day.

Companies are incentivized to develop new drugs by the promise of patent and market exclusivity. Drug companies need to recoup all of their R&D and regulatory costs in the time window of their exclusivity—and have also found ways to extend the time that the window lasts. 

With this incentive structure, biotech has become an industry with public companies that have hundreds of employees and no product. The core value of these companies is the assets in their clinical pipeline—which stand the chance to become blockbuster drugs with market exclusivity if they are approved. Approved assets are primarily sold to major pharmaceutical companies.

From a business strategy perspective, this has meant that most value capture comes from pursuing highly specific vertical solutions—new drugs for specific diseases. Some of the most successful horizontal companies in the industry have focused on selling specific instruments or reagents to research labs and companies. An example of this type of company is Illumina, which sells DNA sequencers and the reagents necessary to generate new data. As biotech has matured, platform biotechs have emerged that are aiming to change this dynamic by offering more expansive R&D infrastructure that would have traditionally been built in-house by individual companies.

We’ve all benefited enormously from platform biotechs. Moderna isn’t a vaccine company, it is an mRNA therapeutics platform company. Before COVID, Moderna had created multiple internal portfolio companies that were pursuing specific vertical applications of their core technology. Because of the flexibility of their RNA tech, they were able to design their COVID vaccine in a matter of hours after receiving the DNA sequence of the virus. With the emergency vaccine approval, we saw one of the fastest transitions from R&D to clinical administration in history.

Some platform companies focus on providing R&D services to biotechs instead of launching their own internal companies like Moderna. Adimab, for example, partners with biotechs and pharma companies to help them make antibody therapies so that they don’t have to do it themselves. As one of the Adimab co-founders Tillman Gerngross put it, “Airlines don’t build their own airplanes, and there’s a good reason for that. They focus on the particular thing they’re good at and leave other parts to others. And I think our industry is maturing in a similar way.” This evolution will be essential for understanding Ginkgo.

What does The Organism Company do?

While biotech was heavily focused on making drugs, synthetic biologists continued to spend their time developing better ways to engineer organisms. Many of the founders of the discipline entered into the world of biology from computer science, electrical engineering, and other fields with a deep emphasis on general solutions and explicit standards.

These early leaders were deeply optimistic about the technological progress being made in both DNA sequencing and synthesis that provided the essential tooling to manipulate and engineer organisms. Engineers like Tom Knight and Drew Endy at MIT talked about what was necessary to take genetic engineering to the next level. In order to operate like other engineering disciplines, the field needed several new concepts.

First, builders needed standardized parts with predictable behavior that they could compose and assemble in new ways. There also needed to be meaningful abstraction layers—analogies were often made to modern programming languages that let programmers focus on logic instead of machine code. We needed to move from worrying about raw bases of DNA—ATTCGGATA—to programs closer to the lac operon. Another core emphasis was to more effectively coordinate labor—separating designers of genetic programs from the builders directly compiling it.

In other words, biology needed to develop the necessary infrastructure to become a true engineering discipline.

The iGEM competition has been one of the most vibrant communities for making progress on these foundational goals. The teams can spend their time focusing on their most ambitious ideas because they are building using a shared Parts Registry, a Distribution Kit, and a set of Assembly Standards. Instead of worrying about the behavior of every single enzyme in a new circuit, they can take enzymes off the shelf and spend their effort brainstorming how best to program molds into assembly lines producing foods, detergents, and medicines. This ethos is reflected in the beautifully nerdy fact that the iGEM grand prize is the BioBrick Trophy: a giant aluminum brick that looks like a Lego block.

Even as synthetic biology and iGEM gained traction, some of the leading professors like Tom Knight still struggled to get their work funded. The work didn’t neatly align with the core priorities of any major grant agencies and was very early. At one point, an MIT grad student named Jason Kelly asked Tom, “What do you think if we started a company?” Tom responded, “What would you think if I joined you?” While most professors were happy to “spin out” companies from their labs, Tom Knight wanted to dive in and join the adventure.

To learn more about what Ginkgo does, the challenges it faces, and what the world looks like if it succeeds…

Continue Reading Online

Thanks to Elliot for joining the team and coming out of the gate hot, and to Dan for editing and Simon Barnett for reading an early draft!

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Thanks for reading, and see you next week,

Packy