Field is headed back to platform and enabling platforms
In 10 years, there will be the equivalent of 20 Ginkgo Bioworks. Figure 1 is a mind map of where we are in synthetic biology - Generation 1&2 - and where we are going - Generation 3&4. In short, synthetic biology has shifted from platform (Generation 1) to product offerings (Generation 2) and is headed back to platforms (Generation 3&4). The nature of the new start-ups in Generation 3 will be much more clustered around chassis type and designed around design, build, test, learn (DBTL) principles from the onset. Generation 4 synthetic biology companies have required a critical mass of start-ups in order to be financially viable and are premised on their ability to optimize experimental and fermentation scale-up processes and that not many companies will have these capabilities in-house. This piece explains the state of Generation 1&2 and why the both Generation 3&4 companies are good investments in the future.
Earlier this year, I published a list of synthetic biology companies, most of which use precision fermentation to create products. Many of the products are consumer-facing from lab-made cement, soaps, gelatin, coffee with the breadth of these innovations only expanding! Domestic biomanufacturing of goods is better for carbon footprints, arable land use, and even for national security, according to the American Dynamists in the room. There are far reaching consequences for making the manufacture of goods purely a domestic exercise. Azeem Azhar in The Exponential Age sees the rise of synthetic biology manufacturing of commodities as a reason for rapid deglobalization in the next century. Although this brings the potential for massive geopolitic shifts, it requires a similarly revolutionary optimization in the way commodity synthetic biology companies achieve cost-parity, and eventual superiority, to incumbent petroleum-based products. In Ginkgo’s most recent 10-K, they estimate $2-4 T of direct annual impact from biomanufacturing.
The legacy synthetic biomanufacturing companies Amyris and Ginkgo/Zymergen haven’t performed well since going public (see in Appendix). However, Amyris has shortened the time in translating lab results to products from 3-4 year to less than 1 year, according to their most recent 10-K. They attribute this to ‘leverag[ing the] technology platform with proprietary strain construction, screening and analytics tools, advanced lab automation, and data integration.’ Currently Amyris has 13 products in the market. Ginkgo’s 10-K attributes is current and future success of its 105+ programs to it dual Foundry and Codebase.
I knew Ginkgo was likely collating its data and automating many of the processes but I hadn’t understood the economies of scale their platform is able to achieve. Namely, the 50% decrease in unit operations and 3X output which Ginkgo explains in their 10-K:
I wish we had more data on the late-stage but pre-IPO players like Geltor, Solugen, Bolt Threads and Checkerspot to see their unit economics and platform scalability. At least at this stage, these companies fundamentally distinct from Ginkgo as they focus on a very limited range of products without much talk of platform/expansion capabilities. Bolt Threads makes synthetic spider silk and mycelium-based leather for fashion and sports brands. Geltor is an Ingredients as a Service (IaaS company) that specifically produces elastin and collagen (patents here). It’s unclear how they’re improving their economies of scale and the exact nature of their platform (outside of elastin and collagen). Checkerspot uses algal-derived oil to make WNDR Alpine products such as skis, snowboards, and apparel. The exception of this trend being Solugen optimizes it enzymes and metal catalyst with ML for Agriculture, Cleaning, Water, Energy, and Infrastructure. Although only their water treatment core seems to be the only commercialized, they might be selling much more. Geltor, Bolt Threads, and Checkerspot, which have collectively raised over $640M give credence to the Steve Jobs adage, “Do not try everything. Do one thing well.” Geltor, Bolt Threads and Checkerspot show that niche companies done well can achieve significant traction.
As highlighted in Tsung Xu’s recent post, Checkerspot’s vertical integration is particularly unique as it sells its algal derived products directly to consumers, and did this in a remarkably short amount of time. Checkerspot was able to launch 3 commercial products within 4 years of incorporating the company. Checkspot’s success is partially attributed to the founders (Charles Dimmler and Scott Franklin) that benefitted from their prior work on D2C algal oils at Solazyme.
On one hand, we have the platform incumbents of Ginkgo and Amyris which are automating and broadening scope and using automation to solidify their competitive advantage. On the other hand, we have growth equity stage companies that are focusing (and presumably doing well) on niche products. The success of Geltor, Checkerspot, and Bolt Threads set the way for single product synthetic biology and I predict there will be many successful companies in which capture part of the market. However, Ginkgo’s every expanding and optimizing platform will be an existential threat (as Google is for many tech companies). Therefore, emerging companies (ones producing lab-made meat, milk, chocolate, cocoa, and beyond) will need to continually optimize their processes which could be accomplished by building their data engine platform (expensive/time consuming) or by partnering with a service/platform (potentially costly but instantaneous) company that’s able to model protein, culture, and potentially metabolic optimizations. To my knowledge the companies that are platforms able to help with design of experiments and scale-up analytics are Officinae, Deepmirror, Boston Bioworks and Invert Bio. I predict there will be more companies in this arena with differentiating criteria being ability to take the company from a service to a platform, long-term customer retention or life-time value of customer, and capturing enough of the data to reach the virtuous cycle.
An alternative future is one where companies build an automation and modeling platform that also producing products (essentially Ginkgo 2.0). But because they’re not retrospectively trying to understand the data, they’re able to better capitalize on the learnings and directly compete in a platform → product fashion. There are a few companies working towards this future (Cradle Bio, Eden Bio, and EV Biotech) and certainly many more will come.
My gut feeling is that there’s room for many companies to play in all arena purely product, platform, and product/platform areas given the 550 B to 1.2 T market size by 2030. To put this in perspective it’s the equivalent of 10-20 Ginkgo’s (by Sept 2022 market capitalization). If we continue along the Ginkgo trajectory that’s 1000-2000 large scale high-value production programs in full swing by 2030. Data capture and accelerated learnings that are possible with the platform and product/platform companies will create tremendous value while catapulting an entire industry. I’m interested in learning/ideating more about these types of companies that are creating data fly-wheels in the scale-up process. If you have ideas or new models here -please reach out.
There was some talk after the article whether the ‘enabling generation’ will create venture-scale returns. However, what people don’t realize is the ML talent constraints in synbio. Namely, there’s very little of it and most goes to drug discovery companies. With the glut of seed-stage synbio companies, very few have talent (or could afford talent) to build our their platform to reach economies of scale. Thus an investment in one of these companies would be a very reasonable bet (from what we understand) but contrary to the industry.
<Takeaway 1: Niche companies synthetic biomanufacturing companies have a place to play in the near-future bioeconomy>
<Takeaway 2: Legacy knowledge matters, even if the previous company didn’t materialize (e.g. Solazyme)>
On the other hand, Similarly Bolt Threads has a relatively sparse number of products, MYLO, M-SILK, and MICROSILK.
(Checkerspot was able to launch 4 commercial products within 4 years of incorporating the company.) Checkspot’s success is partially attributed to the founders (Charles Dimmler and Scott Franklin) in particular benefitted from the expertise of the founders that works on algae oils D2C at Solazyme (highlighted in Tsung Xu’s post). <Takeaway 1: Legacy knowledge matters, even if the previous company didn’t materialize (e.g. Solazyme)>
Given the rapid speed of commercialization of current biomanufacturing companies and the data/economies of scale of Ginkgo/Amyris,
become platforms (Ginkgo, Amyris, Geltor, Zymergen) to achieve scale, automation, capital efficiency. The synthetic biology industry boasts a new crop of growth equity stage companies, such as Solugen and Checkerspot. I’ve been seeing a host of new companies that are much more focused on automated approaches for ptoetess trial and error and enables you all to move to a more scaled, less services-oriented, venture-scale business in the long term
Appendix
