Deep Tech has the potential to solve some of society’s biggest problems… climate change, food and water insecurity, antimicrobial resistance, and the need for continual medical advances. These are just some of the ones we know about. Solutions derived from Deep Tech today could meet a myriad of needs in the future.
But there’s a catch …translating Deep Tech into real world solutions requires patience, which in today’s fast-moving world is something that is in rare supply.
So what is Deep Tech?
The term ‘Deep Tech’ is used to refer to startups that are building products or services based on fundamental new science or engineering.
Some of these startups – such as those building machine learning and AI software - fit more easily into the Venture Capital funding model by virtue of software being able to be de-risked more quickly and cheaply.
But a substantial share of Deep Tech innovations – such as medical devices, new forms of energy generation and storage, new computing architectures or new materials for carbon capture and sequestration - are embodied in hardware or require time-consuming and expensive iterations on prototypes and tests before they are ready to be released to customers.
Time is money…
Deep Tech takes time. Novel energy storage solutions, sustainable advanced materials, new computing paradigms and innovative therapeutics or medical devices – these all start from fundamental science in the lab and require iteration and experimentation before they are ready for commercialisation.
The technology itself embodies inherent uncertainties and, since these are novel solutions which often don’t yet have a clearly-defined customer base, so too does the market. Taken together these co-evolving risks can make the road to product-market fit substantially more complicated than a typical startup. And this combined with a long wait and expensive early experiments to discover if the tech will sink or swim can deter even the most science-friendly of investors.
Unlike academia where a negative result is considered a learning opportunity and part of knowledge advancement, the world of business is not so accommodating when things don’t work. Risk is embedded in investment but the question is ‘how much and how often?’
For therapeutics the biggest hurdle is phase 2 clinical trials, when testing is done for the first time in patients and usually several years after the initial research. Dr Roberto Solari is a Visiting Professor at Imperial College London and CEO and Co-founder of Myricx Pharma, a drug discovery company that is targeting a specific protein for treatment of a range of diseases. “Often at the phase 2 stage therapies turn out to be ineffective,” he says. “This isn’t because the science on which the therapy is based is wrong. It’s because human biology is extremely complex and, although we do wonderful breakthrough research to understand disease and pathology, the sum of what we know is actually very small compared to the sum of what we don’t know.”
Investors are looking for a probability of success, and for this you’ve got to have a strong IP position, some great science, experienced people and a clean line of sight to market.
Dr Solari describes drug discovery as an extremely risky business and one where success is an outlier event but not an impossibility. “Investors are looking for a probability of success,” he says. “And for this you’ve got to have a strong IP position, some great science, experienced people and a clean line of sight to market.”
Ramana Nanda, Professor of Entrepreneurial Finance and academic lead of the Institute for Deep Tech Entrepreneurship at Imperial, is particularly interested in understanding the financing challenges facing Deep Tech ventures.
“Venture Capital is the traditional source of financing for risky new ventures and it has surged in the past two decades,” he says. “But the overwhelming share of this investment has gone to startups in consumer and business products and services that don’t contain much technology risk. The key risk for this type of venture relates to whether there is an attractive revenue model, which is something the investors can learn quickly from early testing with consumers, requiring a small amount of ‘seed financing’. If startups achieve product-market fit, then the investors finance them to scale up, but if they don’t, the venture is shut down.”
Professor Nanda believes that by focusing on such ventures, Venture Capital investors and accelerator programmes are making rational decisions that are often likely to generate the highest return for their funds. However, it also means that, as a society, we are missing a highly valuable segment of innovation Tech where the uncertainty takes more time and money to reduce the inherent risks.
Despite the difficulty in building these ventures, the number of nascent Deep Tech entrepreneurs seem to be on the increase even beyond sectors such as AI and machine learning.
In part, this is due to the growing democratisation of infrastructure that allows for quicker and cheaper initial tinkering with hardware, made possible by technical advances such as rapid prototyping and commercial lab space that is beginning to be rented out to new startups.
According to Professor Oscar Ces, Co-Director of Imperial College Advanced Hackspace, more universities are enabling Deep Tech entrepreneurship throughout their community, so it is no longer just the remit of established academics.
“This has been a game-changer,” he says. “In the past academics would try to hit the bullseye with existing research programmes but now new young entrepreneurs without a well-established research group can see the problem and develop a solution from first principles. They don’t have so much technological baggage but they do still need funding and support for the commercialisation journey ahead of them.”
"Getting to the point where the market can see and touch and feel a product is usually a long way away for most Deep Tech companies. Our technology was on paper for years before we started to cut metal for our system. In that time we had to engage with the market because that is the only way you can learn whether you are making the right product.”
- Mike Simpson, CEO Cheesecake Ltd who are developing sustainable energy storage technology to support the charging of electric vehicles.
The world is your oyster but….
And this journey is fraught with choices... Raising capital for Deep Tech ventures requires a number of challenging decisions. Moreover, an additional aspect of being based on fundamental science is that Deep Tech can have multiple applications and therefore potentially multiple markets. This makes it adaptable and pivotable but can also create a dilemma in choosing which pipeline to focus on first.
Getting access to market expertise is so important for Deep Tech companies so they can understand the relevance of their technology for future customers. One discussion with an expert can save six months of going down a dead end which could be crucial to success.”
For Dr Simon Hepworth, Director of Enterprise at Imperial College London, the crucial point is "getting access to market expertise is so important for Deep Tech companies so they can understand the relevance of their technology to future customers. For life sciences companies addressing a particular disease area, the sector might be relatively well known but for materials it could go into variety of sectors. Being able to talk to experts seasoned in particular sectors who know the interests and the business models around how technology is traded in those sectors is vital. One discussion with an expert can save six months of going down a dead end which could be crucial to success.”
Life sciences ventures tend to be more targeted from the outset as they address a specific unmet healthcare need. Using a core technology these companies can still tackle a range of problems and examples include ProtonDx and DnaNudge who are both Imperial spin-outs and both working with lab-on-chip point-of-need diagnostic devices. They also both pivoted in the pandemic to develop COVID-19 tests, which brought both opportunity and challenge.
Founded in 2015, DnaNudge was a fully-fledged company at the time of the pandemic with a consumer technology that could extract genetic information to inform an individual’s dietary choices. In a few months they pivoted their tech into a rapid, accurate, portable and lab-free RT-PCR test for COVID-19 and in 2020 it was rolled out nationally in urgent care and elective surgery settings.
The ProtonDx team were still a research group when the COVID-19 pandemic hit and had just started to explore the market for their technology to diagnose and track dengue fever.
They refocussed to work on a COVID-19 test that provides results on a smartphone application which is synchronised to a cloud server. “For us COVID-19 provided an amazing opportunity to get out of the research environment and build a startup,” says Nick Moser, COO of ProtonDx. “The desire to contribute to the UK response to the pandemic accelerated us and drove us to tackle the engineering challenges of developing a commercial product for healthcare professionals.”
Pure engineering and material sciences ventures often have many possible applications. BladeBUG is an autonomous robot to inspect and repair wind turbines that will ultimately improve efficiency and sustainability, but this platform will be useful in many other domains. “Some have suggested these would be faster routes to market and revenue,” says BladeBUG CEO Chris Cieslak.
“There is nothing like our technology operating in offshore wind, so we’ve got to focus and succeed in that area first. Once we‘ve proven the technology in this challenging environment then we can help with maintenance and inspection in other areas such as civil infrastructure and shipping. These markets won’t disappear but if we lose our momentum in advancing wind energy that would do us a big injustice.”
"So we had this platform with an application for fast point-of-care applications driven by the consumer world but all of a sudden we had to deploy this consumer tech into a hospital setting for COVID-19. And the challenge wasn’t repurposing the technology… it was getting something different and novel into the hospitals and scaling innovation really fast."
- Chris Toumazou, Regius Professor of Engineering at Imperial College London, Co-founder and CEO, DnaNudge
Running the Deep Tech relay race
Common to all Deep Tech companies is a need for focus and tenacity to stay the distance. Professor Nanda suggests it is helpful to conceptualise the Deep Tech journey as four stages from basic science to a successful venture generating substantial cash flow.
Leg one of the relay is about research and invention. Leg two involves translating the invention into a piece of technology that can be tested with customers, beyond the confines of a controlled laboratory environment.
The third leg involves working out product-market fit, validating the value placed on the product or service by the targeted customer and ensuring the price they are willing to pay can sustain a profitable business. The fourth involves growing and scaling a business that has achieved product-market fit in order to build a large and successful enterprise.
“There are different sources of capital with different incentives and different requirements that often need to be brought in at different times to support the commercialisation of these technologies."
By virtue of the fact that most VCs and accelerator programmes focus on startups whose product or service is based on a well-understood existing technology, they effectively concentrate on the third and fourth leg of the relay. Universities and research councils offer grant funding and support for the initial leg.
What is missing tends to lie in that second phase, where there is a need for an organisational and financing model that will take the technology out of university labs and bring it to a point where commercial investors find it an attractive investment on a risk-adjusted basis.
“This is the conceptual challenge” says Professor Nanda. “There are different sources of capital with different incentives and different requirements that often need to be brought in at different times to support the commercialisation of these technologies. Understanding the degree to which these funding sources can be adapted and combined effectively to help commercialise Deep Tech is an important line of enquiry.”
Professor Nanda believes that grant funding, from the government and philanthropists is key to de-risking Deep Tech ventures in the early stages. This non-dilutive source of funding with no cashflow rights maps well to what Deep Tech startups need at this point in the journey when they are too risky for commercial investors. It also has that key ingredient…patience.
Globally, an estimated 1.5 trillion dollars of philanthropic capital is managed by thousands of foundations. “These technologies are addressing big issues that people care about,” Professor Nanda says. “And if we can develop a structured scientific approach to de-risking in the form of early translational experiments which commercial investors consider ‘research projects’ then this is something that philanthropists can get excited about financing. It also creates a framework for building towards value inflection that allows those who provide the funding to measure the impact of their grant making.”
IImperial’s Institute of Deep Tech Entrepreneurship has begun to address the challenge in this manner. Its Deep Tech Prime (DT Prime) programme is aimed squarely in the space between university and research council grant funding and commercial investors, Professor Ramana’s second leg of the relay.
DT Prime aims to address that by supporting teams to bridge the gap to a strong commercial footing using non-dilutive grant funding from the government and philanthropists. Without the patient capital at this stage, research teams spin out too early and try to raise the capital from investors. This can often lead to failure, with technologies not de-risked enough to attract commercial investors or IP not strong enough to cover the eventual shape of the tech.
“Important technologies often languish within universities and fail to achieve their potential social and economic impact,” says Professor David Klug, Associate Dean for Enterprise in the Faculty of Natural Sciences and one of the Co-Directors of Institute. “DT-Prime is aimed at reducing the frictions in this process. One important way we do this is to work with teams to develop and achieve technical milestones that address key uncertainties in the eyes of commercial investors. This not only increases the likelihood of investment when met, but also leads to substantial value inflection at spin-out, which means the founding team’s ownership is more valuable at the moment of commercialisation.”
“Important technologies often languish within universities and fail to achieve their potential social and economic impact,”
Launching in January 2022 with 9 teams ranging from drug discovery platforms to carbon-negative concrete, DT Prime could be described as a ‘pre-accelerator’ as it works with teams still at the pre-commercial stage that nevertheless have clear commercial ambitions and demonstrable progress.
“Our experience of running the pilot scheme is that shifting the mindset of the teams from open-ended research to focused development is key to success. We have achieved this by employing an experienced CTO from a successful startup to project manage the teams and help them to develop a more commercial, deadline focused approach.” says Peter Cawley, Associate Dean for Enterprise in the Faculty of Engineering and one of the Co-Directors of Institute.
“Few investors like funding R&D - what they want to know is if they give you X amount of money how much will they get back and when? They are not interested in moonshot ideas where all the money is being funnelled into building the device, which is why incubators, accelerators and grants are so vital to support R&D challenges in Deep Tech.”
- Kourosh Atefipur, Co-founder and CEO Valkyrie Industries, who are developing a wearable haptic suit to let users feel, touch and hold objects in virtual simulations.
Teaching Deep Tech entrepreneurship
Academia has often been critiqued for its tendency to be removed from the real world but in Deep Tech the two need to meet… intimately. This may require the academic mind to adapt and alter its perspective which, in turn, could benefit from a new learning approach.
Currently the standard way of teaching entrepreneurship is the Lean Startup model which sets out a series of stages through which startups should progress. “Although this is the globally accepted approach,” says Dr Simon Hepworth, Director of Enterprise at Imperial College London. “It’s not so appropriate for Deep Tech companies with their long runway of development. There’s a need for a pedagogy that is more suitable and can provide a toolbox from which Deep Tech entrepreneurs can pick and choose with the support of experts in this area.”
Identifying the common pinch points on the Deep Tech journey is not easy - each startup has their own story to tell with a different emphasis on the role of ‘luck’ - but it is an essential piece of research to inform new approaches to supporting these ventures and is planned as part of the work of Imperial’s Institute for Deep Tech Entrepreneurship. “We see the early process of building these nascent Deep Tech ventures as one of decision-making under uncertainty,” notes Nanda. Like a game of cards, one cannot predict the hand one is dealt, but there are better and worse ways to play in any given instance. He notes that extracting those insights for Deep Tech ventures is a key goal for the Institute.
"As a scientist in a university setting - you work on a project, you prove a concept, and perhaps you write a paper and then you move on to the next project. Whereas taking that work from finished project stage to a commercial application is a whole new body of work where you have to adapt, develop, expand, pivot.
And you really need to understand industry requirements – it’s not just scaling up but adapting the tech to meet all those requirements. That is the biggest challenge for Deep Tech companies – taking the step or the leap from lab scale to commercial scale.”
- Dr Ola Hekselman, CEO and Co-founder Solveteq – who are developing a solvent to recycle lead batteries.
Policy, belief and the next tech cluster
Beyond university and investor approaches to improve the commercialisation journey for Deep Tech, government policy is also a central to sustaining Deep Tech. This support comes in many shapes and sizes: as a funder, government can provide invaluable finances for translation; at a more subtle level, this support shores up belief around a Deep Tech venture.
Government can also be an important customer, providing a valuable demand for products. The US government played an essential role as a key early customer in the semiconductor revolution which virtually eliminated market risk and in the UK the NHS can guarantee a demand for a therapy or product once it meets certain criteria set by the regulator.
This role of policy in jump-starting innovation is often underplayed but it is important. “There is a huge role for government,” says Mike Simpson, CEO of Cheesecake Ltd who are working with National Highways (formerly Highways England) to share the technological risk for finding a solution for charging electric vehicles on the UK road network. “It’s not easy and takes a lot of energy, persistence and motivation but in clean tech we’re coming together to tackle this issue and there is clearly an appetite for this type of partnership.”
"It is not enough to have the best idea in the world, you need the finance to support the work at every stage.
Seed money can be sufficient at the beginning, so you can try and fail (and if so, fail quickly!), but for us grant funding quickly became crucial.
Alongside the money itself, grants are great platforms for independent reviewers, who provide tech and commercial due diligence and they also give credibility.
Private investors were reassured that our early stage venture had attracted public money, because it shows numerous authorities believe in it"
- Krisztina Kovacs-Schreiner, CEO of Lixea who are developing a novel chemical process to convert woody biomass to biofuels and are building a pilot plant utilising a combination of investment and €4.3 m of EU grants.
According to many Deep Tech entrepreneurs the role of UK policy could still be stronger. The recent Innovation Strategy proposes a deepening of ties between government, universities, businesses, and investors but, alongside this, perhaps there is a need for regulatory partnership that looks to reduce the barriers to startup experimentation and a deeper cultural change in the UK to enable more risk and greater belief over longer timelines.
Since the UK psyche has a reputation for caution, perhaps what Deep Tech requires is a sense of place to physically reflect the belief in the sector and if one looks back over the past several hundred years it is possible to see that the geographic locus of frontier innovation hubs has shifted as new technologies emerge.
“The drivers of success in Deep Tech are unique,” explains Professor Nanda. “In that startups are likely to benefit substantially from proximity to excellent universities, large companies, centres of finance and the seat of government. Combined with the growing startup culture and policy commitment to science and engineering, this makes the UK a strong contender to become one of the global Deep Tech hubs.”
Deep Tech is exciting. The science, the possibility and – let’s face it – the potentially huge amounts of money – are creating a buzz around this sector that’s difficult to ignore. But it faces complex and inter-related challenges, which require a multi-faceted approach to overcome.
Much of the solution will lie in funding, teaching and policy, but perhaps part of it is as simple as giving Deep Tech a home in the UK, enabling the formation of the next tech cluster so we can truly and deeply translate its potential.
The Imperial Institute for Deep Tech Entrepreneurship seeks to understand and address the key barriers to the successful commercialisation of Deep Tech ventures. It is currently focussed on three areas of work: Commercialisation Support, Ecosystem and Policy Support, Research and Pedagogy.