Scientific Scale as a Service

Scientific Scale as a Service

Scientific Scale as a Service


Status: Rough Draft

We can draw many parallels between the evolution of the software market and the emerging characteristics of biotech innovation. Over the past 20 years, the emergence of "scale as a service" has powered multiple "invisible innovation" waves in the world of software. In short, infrastructure begets applications begets the need for more infrastructure and so on. As the first generation of synthetic and computational bio companies reach the public markets and more private companies reach scale, the demand for modern infrastructure will continue to increase. This will create opportunities ranging from manufacturing and supply chain innovation to tooling that unlocks faster and cheaper research and development across the value chain. In the same way companies like Shopify, Stripe, and Twilio have become the operating systems of their respective domains, we expect (and will investigate opportunities to build) platforms that play similar roles in the scientific ecosystem.

API Layer for the Bioeconomy

One of the most profound impacts of the cloud era has been the emergence of scale as a service. Platforms like Twilio, Shopify, and Stripe build scale on behalf of their customers in important, but non-core, functions and enable access via a straightforward API call or subscription.

These companies can all be thought of as operating systems which sit above complex networks of institutions or infrastructure. They use software to remove complexity, making it easier for the underlying infrastructure services to be managed and consumed. Their platforms pool the collective scale of their customer bases. This means they can invest more in product development and extract better terms from suppliers. Their business models transform capital costs into operating costs and enable their underlying customers to run more flexible and leaner operations. They deliver their services over the internet, some of them via APIs. Importantly, they all make the process of starting and scaling a business easier and less capital intensive.

This infrastructure enables entirely new applications, which in turn require additional infrastructure. Eric Stromberg calls this progression "invisible innovation".


As scale begets scale, middleman after middleman is removed from the equation. Companies can bundle infrastructure from various scale as a service providers to go bigger faster (Uber, DoorDash, Instacart) or to target profitable niches that were previously unreachable (micro SaaS, niche eCommerce and creators).

These platforms play a critical role in shifting scarcity and, by extension, transforming how value is created and captured.

There is no shortage of "invisible innovation" left to unlock in consumer and enterprise markets, as Brad Gerstner recently alluded to:

We still think we're early in that transformation and the 20% penetration that has already occurred in the Cloud mostly came from Cloud-native businesses. These were businesses like Uber and Airbnb that grew up in the Cloud. For a United Airlines, for an iHeartRADIO, for the Fortune 1000, they're just starting their journey into the cloud.

But after a decade and a half of market evolution, the software infrastructure playbook is becoming more legible. These shared playbooks have created a path for aggressive capital providers like Tiger Global to enter the fray with models more aligned to the current state of the software world than the traditional VC firms they are competing with.

This maturation of the software innovation wave has led many to speculate on where the next surge of innovation will come from. As society grapples with two significant crises β€” COVID and climate change – biotech and "atoms"-related innovation (energy, materials, infrastructure) have emerged as the leading candidates.

What follows is focused on biotech β€” specifically, elements of computational and synthetic bio in order to unpack the parallels between software and biology.

Scientific Scale as a Service

Returning to how the last couple decades have played out in software, we might reason that the the most valuable aspect of scale as a service is not lowering costs, but increasing control. Scale as a service minimizes external contingencies and coordination, enabling precision execution that aligns with desired speed, scale, and budget.

This idea is expressed well in a comment made by an industry executive comparing Shopify to Magento.

"We can go home tonight, start a Shopify store and be selling by tomorrow. Whereas if we went to Magento, we'd have to hire a developer."

Across much of the biotech landscape, it is possible we are actually in the pre-Magento days. For all their promise and technological progress, we may look back on the current generation of companies (Ginkgo, Zymergen, Recursion) as the outsourced IT shops of the biotech revolution β€” more Infosys and Wipro than Shopify.

This is not a comment on the quality of the respective first gen companies β€” Infosys ($79b market cap), Wipro ($41b market cap), and others like them are massive. Instead, it is a comment on the scale of the opportunity ahead β€” like the internet, invisible innovation waves may end up revealing that the market for biology-based or enabled solutions is larger and more diverse than we could have imagined a priori.

Vertical Integration β†’ Horizontal Platforms

To date, vertical integration aimed at developing products (ex. specific therapeutics) β€” rather than horizontal infrastructure enabling platform dynamics to emerge β€” has been the name of the game in biotech.

As a16z notes, there is good reason for this. Technological and scientific barriers have largely limited the feasibility of horizontal platform approaches.

Because most traditional drug development programs are essentially independent discovery efforts, selling components or generalized infrastructure across the entire industry wasn’t really a viable option (too much customization needed).

As in software, we are starting to see the cycle of infrastructure begeting applications begeting more infrastructure start to play out. Technological breakthroughs from first generation companies β€” low cost gene sequencing (Illumina, 10X Genomics), biosynthesis and organism engineering (Twist, Ginkgo, Zymergen), and the integration of AI and advanced computing (Recursion Pharma) β€” are kickstarting access to scale for emerging companies aiming to improve human and planetary health.

The proto-platform technologies mentioned above began the (decades long) process of modularizing development of biology-driven products and services. As these early movers continue to grow, a new generation of horizontal platform companies are starting to emerge.

The aim of these companies range from:

  • Components aimed at creating an industry standards, including companies like Dyno Therapeutics pioneering drug delivery vectors and Alloy Therapeutics and its human antibody discovery platform.
  • Measurement tools ("Illumina for X") that allow us to interrogate biology at higher precision
  • Interfaces and integrated platforms (powered by AI, ML, and CV) that make complexity legible to systems and users
  • Automation, design for scale, and large scale manufacturing (ex. Resilience)

As a result, the industry is becoming more dynamic and entrepreneurial than ever before.

Going forward, lower costs to experiment (powered by improving will increase the rate at which researchers can design, build, test, and iterate biological systems. This will in turn accelerate the development of vaccines, gene and cell therapies, molecular engineering, and cloning. From this, applications will emerge across drug discovery, pharmaceuticals, food and agriculture, chemicals, and energy.

Proto Platforms β€” Ginkgo

The bio revolution hit a new inflection point recently with the public listings of "proto platform" companies like Ginkgo Bioworks ($15b market cap)

A quick glance through each company's investor presentation highlights how critical a platform and ecosystem story is to each of them. As this slide from Ginkgo shows, these companies are taking direct narrative and strategic queues from their software platform peers.


What is also apparent from the listing documents is how far off each is from realizing a true platform vision, and what business model and technological limitations their chosen paths might create on the journey towards the data moats and networked-driven flywheels they aspire to. This in turn helps highlight where emerging opportunities for company creation and scale lie.

The Ginkgo Bioworks model illustrates the nasency of scale as a service in biotech well.

  • Ginkgo has built what it calls the "leading horizontal platform for synthetic biology", making it possible to program cells as easily as we can program computers and enabling innovation across industries, including therapeutics, industrials, food and agriculture.
  • The company's business model is built on monetizing robotic labs (ex: "Bioworks 1") and data moats. Customers pay the company for R&D services, then agree to pay milestones and potentially royalties on commercialized products.
  • Yet despite promises of a "self-service" platform (though not until 2024), the company expects its ecosystem to reach ~ 500 new cell engineering programs by 2025. Per its own data, this represents only 1-2% of the market for cell engineering services.
  • This approach, large customers and long project cycles, may limit the company's ability to serve expanding and more diverse customer demand for their solution. To use a software analogy, they may play the role of old school CRM systems to the Salesforce that is to come. Again, this is not so much a comment on Ginkgo's ability to scale but an observation about overall market size (Oracle still has a $200b+ market cap, as does Salesforce)

We believe there are similar business model and technological path dependencies inherent in companies like Zymergen and Recursion Pharma that are worth exploring in more depth as we continue our research into the area.

  • Zymergen's approach demonstrating the effectiveness of their "biofacturing" platform has been to develop and market their own products (like Hyaline). Success with early products may lead them to go in the direction of a fully vertical approach and cede the materials platform opportunity to others. They are, of course, facing other issues...
  • Recursion, aims to industrialized drug discovery through its closed loop operating system. Early progress is highly promising, but the company's extensive investment in in-house infrastructure (hundreds of millions invested) which drives a competitive advantage today, could become a burden that limits speed and flexibility as invisible innovation unlocks access to infrastructural scale for more nimble competitors.

The goal with highlighting these potential challenges is not to suggest building direct next-gen, iterative, or "European" versions of these companies but to begin uncovering the potential paths for operating system development in the world of drug and materials discovery.

Projecting Invisible Innovation

As the first generation of companies across the biotech landscape reach market and (in some cases) scale β€” from synthetic biology to cell and gene therapy (CGT) β€” we are starting to observe a pattern with parallels to what occurred in software. Namely:

  1. Enabling scientific discoveries and modular primitives unlock...
  2. Early applications which highlight bottlenecks that...
  3. Yield opportunities for new infrastructure and platforms to emerge which...
  4. Massively increase previously "invisible" TAM via direct applications and adjacent products/services.

From there, we should expect the innovation wave to continue.

Using cell and gene therapy as an example, we can track the early stages of this evolution using actual companies and scientific breakthroughs.

After a decade of scientific innovation (genome sequencing, gene editing, AAV delivery, CAR-T cell engineering) and early business model innovation (outsourced CDMO), the first generation of applications (in this case, therapies) emerged.

The 300+ therapies currently in clinical trials highlighted a number of key bottlenecks to true scale β€” this ranged from standardized discovery, to more effective therapeutic delivery, to dealing with complex supply chain and manufacturing challenges.

Into this void have stepped a number of emerging horizontal platform players designing for scale by bringing advanced computation to market as a service, standardizing important parts of the value chain, and enabling new approaches to manufacturing and automation.


As in synthetic biology, the wave of invisible innovation in CGT powered by increasingly innovative scale as a service is in its nascent stages with what will likely to be decades of high growth ahead.