This is the third in a series of interviews with deep tech investors, taking the temperature of their particular fields at the start of 2019, and reflecting on the year gone by. The first two installments dived into quantum computing and space.
What does 2019 hold for biotech? This was my question to Irina Haivas, Principal at Atomico. She has a broad range of interest and experience across the health and bio space, having been a surgeon, a health policy researcher and an investor in many different levels of business.
Irina and I chat about how the biotech space seems to be going through an evolution, as opposed to being at an inflection point; how and why investors with more digital backgrounds are moving into the bio and deep tech space; and which companies, funds and conferences she’ll be keeping her eye on in 2019.
GM: Irina, let’s start with a bit of a broad question – how would you capture 2018 in the world of health, biotech and deep tech?
IH: I think what we’ve seen over the past few years is the gap between science, or biology more specifically in this case, and what we used to call tech – the advanced technologies like computation and robotics and so on – is starting to close. The engineering space is going on a journey of evolution, so 2018 to me was another step on the journey of confirming the underlying thesis that there’s potential. There were larger rounds raised, new entrepreneurs starting up, new investors were brought to the table, continued progress from the technical and scientific point of view. The ecosystem is also becoming wiser and promises, challenges and ethical debates are a bigger part of the discussion, prompted, for instance, by the CRISPR babies story in China.
We take long term views and are thesis-driven. We don’t need to invest aggressively in year one, but we need to watch the space and look for signals of when our thesis starts to materialize. There’s the underlying thesis that biologists are going to create the next wave of innovation, that engineering biology is starting to be possible. But underneath that general idea, you have computational drug discovery, you have synthetic biology, you have brain-machine interfaces in neurotech, you have lab automation – the tools getting towards precision and miniaturization in the lab – you have the Industry 4.0 components applied to biology. And that’s just on the subset of therapeutics; you have the whole genomic and microbiome space too. It’s a super broad space and each bit of it is evolving at different times. To give you an example, when we were starting to speak about computational drug discovery a couple of years ago, there were only a few companies in the space. Now there are tens of them, and if you segment the space of drug discovery into small molecules, proteins, RNA and so on, the small molecules space is arguably quite crowded now, even though there is still a lot of room to grow and a lot of areas to tackle. And now you see the next wave of people trying to think about how we can move computational drug discovery from small molecules into proteins, RNA, and the other areas that are more difficult.
In the same way a company grows from series A to series B, the same happens to the whole space. And so I don’t think there are specific things that lead to hockey stick growth, it’s more underlying trends. What’s driving this is, first of all, a decrease in the cost of digitizing biological information, for instance, the price of sequencers has dramatically decreased, and will continue to go down. The same trends you see in other deep tech areas also come into play – trends in data, software, computation using machine learning, hardware enablers like automation and robotics. There are synergies in technical know-how, product, scalability, and business models.
GM: Do you think there was any specific that happened in the last 12 months that have been of particular importance to the sector?
IH: It depends. If you look at the U.S. versus Europe, I think the space in the U.S. has been a little bit ahead of Europe in that people are more aware of it. So we’re seeing companies raising their C rounds, not just seed and A. You have Zymergen in synthetic biology, and Benevolent in computational drug discovery and Recursion, too. It’s a sign that big companies can be built in this space.
GM: And what about Europe, you mentioned Benevolent of course, but what about more broadly?
IH: Everything I see in Europe is really, really early. I think when you see Benevolent past series A, Cambridge Medical Robotics is series C now, it’s easy to think, oh there is something huge happening here. However, the majority of the European opportunities are still seed and A. But deep tech businesses, and especially bio-businesses, are global from day one, which presents an opportunity for European companies and avoids the ‘country-by-country’ expansion issue.
In some ways I think Europe is better positioned in this space than it was in some of the consumer businesses, because you have all these world-leading research centers and engineering schools with researchers who, over the past few years, have woken up to the idea that they may not want a career in academia and would be able to build their own science business.
GM: So we are starting to see more investors which don’t have a bio background starting to move this space. We’re seeing this trend in deep tech in general, where VCs who tend to be more in the digital space realize there’s money to be made in deep tech and start jumping in. You can argue of course that this is a really positive thing, because obviously more money, more competition for investors, all these things that you would hope increase the number of companies, and the quality of companies getting funded, as well as knowing that different kinds of expertise in terms of the digital marketplace will come from those investors. But in biotech, the punch line is always Theranos, and the lack of experienced investors who played a big role in that whole debacle. I think Theranos is a massive outlier – I don’t think that that’s necessarily a microcosm of the industry as a whole – but I do think more discussion around investor experience is vital in spaces where the ‘products’ are linked with human health, amongst other hugely important societal areas.
IH: When you look at the engineering biology space, there is more interest and activity from the tech players than there are from the biotech players. And that’s partly because of the overall funding models. A lot of the biotech investors traditionally funded specific assets. What a lot of these engineering biology plays are, they’re platforms that can generate assets or can help generate assets, or help generate compounds in other industries. They’re generally cross-industry. But their key IP is in that intersection of biology, computer science and engineering, and so that has been an area that is closer to what tech investors are comfortable with.
Now there’s a set of challenges that any investor in this space has. First is monetizing this innovation. The current funding models sometimes don’t align with the natural evolution of the company – for instance, raising a round every 20 to 24 months and needing to prove certain things between that. Often these companies are very R&D-heavy, they’re capital intensive, and they may not have a product on the market until their series C or D. And so getting comfortable with the way you can monetize that innovation is one challenge. It’s the same for the founder too: the entrepreneur gets caught up in trying to marry what the requirement for money is in terms of what they should prove, with what the reality if what their business is.
So you have this deep continuous value creation curve which is not very well-aligned with your classical VC funding. You may start getting results for a couple of years while you have to raise money in 18 months. And, by the way, if you have a model of revenue based on the classical pharma model – which is up-front payment, last milestone plus royalties – that still doesn’t add up. The startup only gets the milestone payment once the compound goes through those gates, and so, they may not get anything for the first 12 months, and then get one lump payment, and then get nothing. It’s not like a continuous annual cash revenue or an increase in customers, monthly users or engagement; you cannot really measure it with a traditional metric of an internet business, whether it’s consumer or enterprise.
So there’s a challenge in monetizing innovation, then you have this continuous value creation curve – there’s a longer time to revenue. Then once you start scaling, there’s the challenge in how you actually build this whole interdisciplinary team. It sounds trivial, but it’s not actually that trivial to have a molecular biologist and then a chemist and a machine learning engineer and a robotics expert working together, because they’ve been trained with different vocabularies and they have different ways of thinking, and they now need to understand each other’s problems and work really closely together. And growing that? Well, the talent pool is still scarce, so that’s another challenge. And the other thing to consider with deep tech is that often actually going to market relies on some form of partnership with industry giants and so the challenges in navigating those are also there.
So you have to think as an investor: how much capital will this company need, can they continue to grow this team, can they get this mix of science, engineering and commercial right, and will they be able to translate this into the real world with a huge player? So you have all of these challenges that investors are still trying to struggle with. But on the flip side, if you actually manage to do it, the opportunities are huge. The question in deep tech is never, ‘is there a market, is there a need?’, because generally there is – there’s a huge market. It’s more around, ‘does it work, how do you monetize it, is it feasible within your normal VC time frame or is it more like a research project?’. It’s never around, ‘will this be important enough?’. And that’s the funny thing: it is generally a very important problem that can make a strong impact in terms of everything – health, sustainability, resources, a lot of human potential more generally – but they’ve been thought of as societal challenges, not business opportunities, in the past. I think what’s happening is people are starting to see opportunities.
GM: Looking ahead to 2019, what companies and funds will you be following along with in Europe and beyond?
IH: I’m interested in some of the ones growing out of their seed stages and into Series A. You have Lab Genius and GTN for example. Something I found interesting was that the Y Combinator summer class last year had about 25% bio companies. And a year before they had zero. I haven’t done the exercise of looking through a portfolio of all the seed funds in Europe, but Entrepreneur First now has much more bio in their cohort, some of the investors like Kindred, their portfolios have increasing numbers of deep tech companies. You also have funds like Blue Yard in Germany, where they are only focused on deep tech, whether it’s bio or quantum or whatever else. And that’s what happens, right – the seed investments come in first and a trend is spotted, and then the A investors start getting interested. I would worry if, all of a sudden, the Y Combinator class, and the other influential seed players, reduced their interest. That would be a worrying signal as they are helping drive this recent growth of the industry in general.
GM: Ok, final question – what conferences and events in 2019 will you be attending or keeping an eye on?
IH: I should start by saying I don’t think there’s actually a good event that is focused on this space that is a global one. I think you can capture it by going to various events, of course, but not one that captures the full sector. The J.P. Morgan Healthcare Conference is the big one. You have Health 2.0 in the U.S., their annual event. For the more specific biotech stuff, you have to go to more specific science conferences. And then there’s obviously for AI more broadly, there’s NeurIPS; for healthcare IT, there’s HIMSS. In London there’s RAAIS, and then there’s Hello Tomorrow in Paris which is increasingly good at capturing the deep tech space.