In this article, I’ll try to sum up my learnings as an investor and describe some of the barriers to transforming lab experiments into a sustainable business. What are the first steps to creating a business? What are the success factors that we (i.e. investors) try to identify? And what are the risks associated with investing in early-stage lab spin-offs?
I have been investing in tech start-ups for the past 3 years, and recently I joined Elaia’s Deep Tech Seed team. As a VC, this is as early as it gets. I spend my time going from one lab to another, looking for research projects that could lead to the next successful start-up.
Investing in deep tech is becoming a trend, beyond the buzz, what does it really entail?
It is all about trying to create viable companies out of research carried out in laboratories. While it’s an obvious way to create value, it has its own specificities. In addition to following the same general rules as any startup (market opportunity, capacity to execute, etc.), it also has its very own particularities due to its context. Managing intellectual property, building a business team, assessing the proper time (and cash) to market or evaluating the risk/reward profile.
This spin-off strategy can vary from one research sector to another. In this article, I will be using microfluidics as a case study (quick reminder: microfluidics refers to the manipulation of fluids that are geometrically constrained to a small scale).
So why microfluidics?
- It illustrates perfectly the different specificities linked to investing early in lab spin-offs.
- Diversity in applications — today microfluidics is used in the development of DNA chips, lab-on-a-chip and organ-on-a-chip technologies, water treatment, and many others.
- Multidisciplinarity = Innovation — it involves engineering, physics, biology, nanotechnology, and chemistry. The disciplines of one sector can be translated into applications in another. For example, molecular biology strongly contributed to shaping this industry. And its emergence was driven by the rise of miniaturization and inspired by microelectronics.
What are the essentials to starting a deep tech start-up?
I’ll be starting with the hard pill to swallow: market potential. VC investment decisions will always be business-driven.
As investors, we see on a daily basis a lot of great technology, but only a few products satisfy a strong market need. So don’t hesitate to spend some time and effort challenging your market hypotheses.
Another crucial element investors try to validate early is timing.
2. Who’s leading the project?
One of the reasons a lot of applicative research does not turn into a company is that no one is focusing on taking the technology out of the lab. Sometimes it’s easier to find a CTO (someone who has already worked on the technology), than a CEO. Another mistake we see way too often is: keeping the CTO as CEO. The problem with that? You might end up focusing on tech development and completely forget implementing a business strategy or evaluating commercial opportunities.
All VCs will tell you they invest first of all in a complete and complementary team, especially in early-stage. At Elaia, if we see a lab-spin off technology with high potential and are able to prove the attractiveness by hiring a CEO, that validates our investment strategy!
Note: if anyone has insights on how to optimize the matching of research projects with potential CEOs at startup creation — please get in touch!
3. Intellectual property — Patents Vs. publications
When a tech transitions from laboratory to industry, the big question of « who owns what » becomes of importance.
Patentable technology is a great asset for the future company and its commercialization — and is also a valuation boost. A big mistake we see way too often: researchers publish their findings before protecting them.
Tech transfer entities can provide great help at this point. And as with all technology in the transition to industry, the IP is an issue that must be resolved. There are various existing options such as royalties, up-front payments or equity.
But the differences in valuations placed by universities and industries on lab spin-off technologies can become a serious issue. If the university places the value of an invention too high, will it still be worthwhile to develop it into a commercial technology?
In microfluidics, patents have been crucial especially for the droplet encapsulation technology. There have been multiple patent infringement lawsuits, for example, Bio-Rad Laboratories sued 10x Genomics on multiple occurrences. Here’s an opinion article about that!
4. Incorporation & the associated timing
As long as the startup’s internal operations are organized, the incorporation itself is not that important (except for the administrative assignments — that’s if you’re still at the full R&D level). Then what’s important?
The moment you choose to get out of the lab is extremely important. Until then, yes you can continue to profit from a lot of things including premises, scientific instruments, lab network & events, grants… Most importantly: it doesn’t start the VC clock. Why is that important? Because that’s directly linked to the milestones achieved by the company which is linked to its valuation and thus your dilution when you get VC money.
5. Ownership — operational Vs. non-operational
Lab spin-offs are the result of consistent research, and sometimes collaborations between multiple labs. Company structuring might become complicated if scientists who supervised or conducted the research do not want to be part of the operational entrepreneurship experience. How do you value the startup at creation? And is that value/ownership linked to past research or is it yet to be created? Those questions do not resonate the same way for operational and non-operational members.
Unfortunately, there’s no magic recipe to follow — but as investors, we always try to create an ownership balance if we think it’s missing.
Obviously, the operational team has to stay motivated and well-compensated. Capital is probably the only negotiation power a startup has over well-established companies to attract talent — so it should be used wisely!
Have a working prototype demonstrating the technology’s core function. In the beginning, it doesn’t matter if it’s ugly, bulky, or expensive. But make sure it validates major technological challenges.
It’s also up to investors to see through the bulkiness of your prototype — so make sure you’re pitching the right folks.
7. From prototype to a product — what to consider?
These are points to consider early, but will probably take multiple years to develop in some sectors. Let’s consider our use case:
This part entails designing a product that responds to users’ needs but is easy to scale up, which is probably one of the most challenging aspects.
How translatable are the devices outside of the labs in which they were developed? How well can lab proof of concepts be deployed in large numbers by different groups of people?
- High quality, high volumes
Repeatability is crucial to move into the mainstream as a standardized tool. Devices need to be “plug and play” and easy to set up. In microfluidics, a lot of devices are made in-house using soft lithography and PDMS. The real challenge is translating these designs into commercially viable devices that can be mass fabricated, and in a lot of cases translated to plastics or glass.
To address these needs, commercial microfluidics platforms are being developed and are already available. There’s still a lot to be done though because most of these platforms lock down a particular method and target a specific sector of application.
A lot of companies choose to combine the development of instruments and consumables. This can provide better compatibility across products and maybe a faster development cycle. The downside? It can present a high risk of dependency which comes with a lower negotiation capacity.
Being able to afford fabrication/manufacturing is not enough, lowering cost allows you to get better margins and be more competitive.
Consistent, cheap, high quality and large volumes! So how can early-stage start-ups have it all?
Manufacturing companies can help with fabrication, while investors can provide the financial support needed to launch the first large production batch, and sales will then pay for successive ones.
Another point to consider early into product development is your business model. In microfluidics, it’s crucial: probably the most common business model for microfluidics-based companies is the “razor and blades” business model — consumables contribute to a huge part of the company’s revenues.
But problems might start if competitors are able to decrease the price of a consumable item. Thus, successful companies with this model, usually have an effective monopoly on the products. Another point to consider is that this market is quite fragmented, with a low customer concentration. For example, 10x Genomics has no direct account representing more than 5% of revenues, and they were able to gain $150,000 annually in consumable pull-through revenue for every Chromium instrument sold. This proves that their current monopole position allows them to highly price their consumables.
8. Financials — The fundraising process
There are multiple financing options for deep tech start-ups:
Funding also varies significantly depending on the sector. Deep tech startups require high investments early on, thus public funding plays an important role. They also rarely follow the typical funding progression of software start-ups.
Don’t get me wrong they are still raising an increasing amount of VC money. For example, European startups raised around $34.3 billion in 2019, up from $24.6 billion last year and $15.3 billion in 2015.
The microfluidic sector has been no outcast, with 1000+ companies worldwide and 3600+ patents, the sector has been attracting an increasing number of investors.
According to Yole Développement since 2017, around $2.24B have been invested in a total of 92 operations (sequencing/genomics: $998M, and single-cell analysis >$100M). Illumina has been a leading investor but also an acquirer of a lot of microfluidic technologies.
Once you start considering VC investors, it might be useful to understand the risks they’re trying to evaluate.
Risks associated with investing early in lab spin-offs.
I like to think of this as a game of over/underestimates. As an investor, you could:
- Overestimate the technology — the technology isn’t capable of delivering what it promised. Or just doesn’t function as wished.
- Underestimate time to market — it’ll take much longer to translate the technology into a product. This is really risky because in some cases, by the time the product is ready, end-users might not need it anymore. Or it might get surpassed by another technology.
- Overestimate the science or underestimate the fiction — Theranos, Juicero, or the obvious example of “overvaluing real estate” or WeWork.
- Underestimate the hype — how many times have you heard the word “disruptive” and “deep tech” since 2017? But somehow your startup will still be too “hardware/capital intensive/with long sale cycles/early on/…” for most of those investors.
The problem with hypes and VCs: “VC FOMO”. For some reason or another, we feel obliged to bet on a tech competitor and we’re too scared we’re missing out on the wave of the next big thing.
- Overestimate your competition — a lot of VCs invest in bundles. A startup could become very interesting all of a sudden because some other VC “just sent their investment proposal”. The problem with that? A lot of VCs end up externalizing their due diligence and obvious warnings might be missed.
So you might be wondering, why we bother?
Positive impact! From energy to healthcare, we need more scientific innovation to bring forward real solutions. And it’s possible to invest early stage in deep tech lab spin-offs and obtain a positive financial performance.
Elaia invests in tech and deep tech startups from pre-seed to series A, so ping us, or feel free to recommend entrepreneurs we should meet!
Thanks to Louisa Mesnard and Marc Rougier for their kind help in writing this article.