Image courtesy of The Opte Project & Lyon Labs.

Designing Science

Biology is the technology that unlocks the $100 trillion opportunity. But we need to do more, systematically, to harness the power of biology. We need better design.

What? Design?

To highlight the underappreciated role of design in scientific progress, we showcase how design operates at three different scales. At the molecular scale, at the company scale, and at the geopolitical scale.

We all remember the story of friar Gregor Mendel and his pea plant experiments in the garden beside the St Thomas Abbey in Moravia. As he interbred yellow peas with green peas, and tall peas with short peas, he discovered recessive and dominant traits in genetic inheritability. The beauty in the story is that we can understand it — we can empathetically project ourselves into his mind, and follow his observational logic to his extrapolations of scientific principle. In comparison, science today is so often dizzying. Incomprehensible to all but a few.

But is it truly so impenetrable? Can we not put ourselves in the mind of a scientist, today?

Fast forward from Gregor Mendel’s time by 170 years. It’s just a few years ago, in Mumbai, India, at the Indian Institute of Technology Bombay. Subhadeep Das is in the first year of his Ph.D. program. He wanted to make a gel that could cultivate naive stem cells into becoming brain neurons.

It took him a year. (He is exceptional.) How’d he do it?

He drew it, on paper, with a pencil — a kind of molecular machine, where each component had a purpose. “I sat in my academic supervisor’s office, drawing peptide structures, talking about what would work, let’s move this group into this or that position.”

“I put the piece of paper on the wall above my bed, thinking about how to make it work best.”

It was a minimalist machine. A sequence of 5 amino acids that was common in brain tissue. A pH on-switch. A hydrophilic group. A self-assembly trigger. Three of the amino-acid side chains rearranged for optimal spacing. The extreme minimalism was necessary to create a nanostructure friendly to stem cells.

He sent his drawing and specifications to a chemistry company, and they made the peptides for him, which came back as a dry powder. He mixed it with an aqueous solution, set to the desired pH. It turned into a gel, with precisely the right properties that, when he also mixed stem cells in, they grew into neurons. He published his paper, won an award, and when he came to IndieBio after finishing his PhD, he ran experiments putting his gel and stem cells into the brains of Parkinson’s mice. His treatment cured their Parkinson’s. Now Subhadeep is running a biotech company, working to bring his therapy to humans.

Whether you understand the chemistry or not, what’s important to perceive here — and it’s increasingly emblematic of biotech — is that Subhadeep didn’t “discover” a potential Parkinson’s treatment. He designed it.

He had to read from many fields of science, just to understand what might work. He learned from his professor how neurons prefer nanofibers over microfibers. He learned what made nanofibers. He had to learn to work with stem cells. He learned from material scientists that one factor affecting whether stem cells become bone cells or neurons is the hardness or softness of the material they’re on. He found the common amino acid sequence in brain amyloids with visualization software. He put all these tidbits of insight together.

But when he finally had an idea what to build, he designed it, from the chemistry up. He made 5 peptide designs, learned which worked better, improved his design a little, and then nailed it.

It’s controversial to talk about “designing science.” It brings to mind designer-babies and GMO foods and self-cloning to live forever. But Subhadeep’s story helps us understand that thoughtful design, working with the modern tools of biology, is the very thing driving the biotech explosion.

“Yeah, paper and pencil. That’s how I did it.”

Now I want to make a jarring leap. From the role design plays at the molecular level, I’m going to leap to the role design plays in launching and building companies. I’m going to try to persuade you of something preposterous: that design itself preserves, from the molecular scale to the organizational scale.

My background is in genetic engineering, finance, and design. Before IndieBio, I spent a decade at IDEO as a designer, first in Silicon Valley and then the Shanghai, China office. We worked for some of the world’s most famous companies, on some of the most technologically-advanced computing products of their time. You might think they have the process of creating and launching products down, but that’s not the case at all. In fact, turning a technology into a product, or a service, is not obvious at all. And getting that wrong is the main reason that 9 out of 10 attempts fail — whether those new product launches are from major corporations or startups.

Now think about how extra-hard this challenge might be for the special case of bioengineering.

Biotech is not inherently warm and fuzzy. Some might think it’s scary. Few people even try to understand it. Science alone cannot generate companies that people get excited about. Bioscience doesn’t translate easily or naturally into a business. Design had to play a transformative role.

A technology is not a product. Only meaningful products win market share. A meaningful product delivers both a functional and an emotional experience. A meaningful product creates a relationship between a company and its customers. That relationship is where the durable value is — it’s where trust is earned, and where customers feel like companies “get me.” Customers always have pain points and needs — just that, so often, it’s not what engineers and scientists assume it would be. The physical look of a product needs to communicate its story and purpose, just from what your eyes can take in.

When I created IndieBio, we now had the opportunity not just to design products, but to help design companies from scratch.

At the time, pharma and biotech startups had a cozy process. The startups identified a compound that did something safely and efficaciously. Once they had some proof it would work, they sold the startup and the compound to one of the big pharma companies. Pharma had learned to outsource its R&D to the increasing number of startups. Very few startups directly challenged pharma companies or grew into one. Biotech startups didn’t have business models; they didn’t intend to ever have to sell their product themselves. Their only goal was to sell their technology.

We rejected that tradition. We trained startups not to think that way. Instead, we trained startups to see how their scientific insight could become a platform for many products. This had started to happen in an occasional therapeutic company, but we took the idea where it had never gone before. We began to liberate technologies from the invisible trappings of conventional business models.

To make that jump is no small thing. They need momentum and energy. So we wanted our companies to leverage their tech into solving world problems — triggering an emotional reaction and becoming companies that consumers would root for, companies that people could get excited about. In this sense, our companies needed to be uncompromising, offering transformative solutions, not iterative solutions. We were creating brand new things that had never existed before; we needed investors to witness and feel the market’s excitement about them.

We also had to train scientists to move very fast, and to maintain that pace from IndieBio on. Considering most of our scientists have come from the languid realm of academia, this is a new tempo for them. We preach that “speed is safety.” Moving fast and adapting rapidly helps a startup avoid costly assumptions and migrate to an ideal product-market fit.

Clara Foods, in our first batch of startups, was one example of all this in action.

Arturo Elizondo and David Anchel had the idea of making real, vegan egg whites — without the chicken or the egg. By engineering yeast, they could get the yeast to express egg white proteins.

Their yeast, and their formula, could have easily just become a technology they sold off to a big food company to sell egg whites in a carton in the back corner of the grocery store. That’s what a scientist would do — sell his invention. Instead, we trained them to think like entrepreneurs, and to not be afraid of disrupting entire industries. Non-animal protein was a cause people could root for.

There are 12 different proteins in egg whites. And egg whites are used as an ingredient in so many foods, not just an egg white scramble. They’re used in baking, in pasta, in custards, in caesar salad dressing, in batters for deep frying, in marshmallows, in sauces, in meatballs, and even in lollipops. So we encouraged Arturo to make “performance” egg whites, adjusted and tuned for each different purpose. We steered him to make vegan egg whites that weren’t just as good as real egg whites, they would be better, and more suited to the specific purpose, than real egg whites. Soon, Arturo was showing off meringues that were fluffier and lighter than could ever be made from chicken eggs.

Not your typical biotech company.

The trick was, he didn’t make those first fluffy meringues from his engineered yeast. He knew he could do so, but it would take a long time to get right. We stressed the critical importance of prototyping, and using those prototypes to get early customer validation — so he could be sure that the protein ratios he would engineer were in fact what bakeries really preferred. They had to not just cook the way bakers expected, but also have the necessary shelf life and storage properties to work. So we had Arturo first make his custom egg whites chemically, without using yeast-expressed proteins. Once he had validated his prototypes with industrial customers, he could raise a seed round and get to work engineering his yeast to make those all over again, this time vegan. He’d sped up his development plan by a year. Perhaps most importantly, he’d avoiding spending a lot of money developing vegan performance egg whites, only to then discover they didn’t perform in the way the market wanted. It mitigated a significant amount of risk.

Today, Clara Foods is valued at over $100 million, far far more than they ever could have sold their formula for.

In our second batch of startups, we took this one step further. Alex Lorestani and Nick Ouzounov were nerds from Princeton; they had a unique process for re-engineering the bacteria e coli, so that it prioritized protein expression over cell division. What kind of proteins to make, however, was uncertain. We steered them to collagens, because performance collagens could work not just across many product lines, but across multiple industries at different price points. They could start with surgical grade collagen, which sells for $2,500 an ounce. As they scaled up, they could move into cosmetics grade animal-free collagen, at $300 a pound, and finally scale to animal-free gelatin for the food and candy industry, at $30 to $5 a pound. In each market, they could tune their collagens for performance needs.

Today, on social media, Geltor looks like an amazing beauty products company. Their first product, N-collage, won the Innovation of the Year Award at the CEW 2018 Beauty Awards. But it’s a really hardcore science company at heart.

Today, three years later, many scientists have read enough about the business model canvas that they understand this way of thinking. They grasp the idea of turning technology into a platform, and they know that they could apply their technology in several different industries, or, if it’s a therapeutic, apply their technology in different bodily systems. They may even have talked to potential customers in different industries. But they have a hard time deciding. And now it’s almost even harder for them, because the uncertainty among those options is simultaneously undermining. Startups have to work with speed and focus, making real progress every single week. Uncertainty of direction, for any length of time, is a killer.

Meanwhile, our team at IndieBio now has the knowledge accumulated from 94 startups. We pour that knowledge into new batches. We’ve developed contacts in almost every industry that help us find the optimal product or service that will match their needs. If an incoming IndieBio startup needs to talk to someone in the South African mining industry, or a big alcoholic beverages company, or to the Department of Defense, we’ve got that contact already. If they’re a therapeutic, and they need to talk to gene therapy companies, or hospital systems, or nanoparticle companies, we’ve got that. We have a vast networks of mentors and advisors as well. We know how venture investors will react, and we know how corporate venture thinks, and we know how consumers feel. All of this comes together into our counsel for startups. So when they come into IndieBio, stuck with uncertainty over path to market, we quickly shift them from uncertainty to confidence.

In biotech, having great science is simply not enough to succeed as a business. Academia is chock-full of amazing science that nobody can figure out a use for. Design is the difference between success and failure, between extinction and survival.

Old systems of production and distribution are preventing new technologies from realizing their potential for disruption. When Elon Musk launched Tesla, he brilliantly understood that, if he wanted to succeed, he couldn’t just redesign the electric car. He had to redesign the whole system. He had to build supercharger stations between cities, too — and now there are over 10,000 of them. He also had to build solar roofs, so that our Teslas in our garages weren’t being powered by coal-burning electricity plants.

Today, far more entrepreneurs and investors are willing to rethink entire systems, and the value of these redesigns far exceeds the value of the core technology. There are schemes to reinvent health care delivery, from scratch; don’t sell to pharma — reinvent it. There’s efforts underway to reinvent energy markets and food systems and all of banking.

My friend Enrique Allen, at Designer Fund, invests in startups where design can make a significant impact on the result. He talks about the delta of design — how much a difference better design can make. All over the economy we’re seeing the role of design in a great marriage with technology. AirBnB redesigned the hotel experience. August redesigned the door lock. Apple redesigned the retail experience of buying a computer. Uber redesigned mobility. Some markets and industries are well-designed; others are still lacking in elegant design — they’re still not easy to use or easy to understand. Fintech is an example of where he sees huge potential for design to unlock the disruption that everyone’s been promising. Everyone hears about bitcoin and blockchain, but too few people understand it. That’s a design problem.

It’s so common for bioengineering startups to have exactly that problem: few people really understand what they do, and why they matter, and why they’ll succeed. Their work is incredibly technical. Translating that into a persuasive story, driven by a company with a clear mission, is the role design plays.

Our companies make meat without the cow, and wood without the tree, and whiskey from molecules; they treat cancer drug-free, with food, and they make computers from neurons. A lot of this could be viewed as strange, unnatural and fantastical. But instead we have consumers excited and anticipating their products. It’s only because of good design, and a well-planned launch, that the companies are being celebrated the way they intend to be.

So now let’s make another jarring leap, from the organizational scale of IndieBio to the global geopolitical scale. Let’s zoom out all the way.

Biology is the technology that can save the planet and human health. But the system that currently cultivates biotech is not doing enough to get the most out of it.

Biotech lives inside a structure of economic incentives, government grants, and regulatory oversight. The term for this that economists use is “mechanism design.” If this were any other time in human history, we might say leave the mechanisms untouched; progress feels rapid. And it is — it’s just not rapid enough.

How can a better-designed system unlock biotech’s power to save us?

In the next article, that’s what we’ll be exploring.

Read more:
Executive Summary of the $100 Trillion Opportunity Series