First published in our Biotech Review of the Year publication (Issue 10).
This demarcation is blurring now, with thanks, in part, to the growth of TechBio companies and the proliferation of AI within the life sciences sector. Indeed, investors from both tribes are slowly, but surely, starting to bridge the divide to become investors in life sciences tech – but currently there is only a relatively small (albeit growing) pool of investors that truly specialise in the TechBio space.
The rise of AI
It is clear that AI is making big waves in the life sciences industry. AI is being deployed in a wide variety of healthcare settings, including in diagnostics and also throughout all stages of the lifecycle of a medicine. For example, the speed and volume of data that AI can consume and the impressive analytics of some AI tools can significantly shorten traditional drug discovery lead times – and when designing a clinical trial, AI can radically improve the chances of selecting the right patients who will respond to the treatment – with the potential to make a big impact on cost savings and the timelines for medicine approvals. Having said this, at the moment, the costs of drug discovery are ironically going up in part due to the level of investment that is being made in adopting these new tools.
Big strides have been made right across the globe. Medicines that have been developed with the use of AI have been reaching the clinic in the last 3 years. In 2020, UK’s Exscientia made history when it announced the first AI-designed medicine to enter a clinical trial, for an established protein target. Various other companies have since followed suit, including Utah’s Recursion Pharmaceuticals and San Francisco’s Verge Genomics. Most notably, Insilico Medicine (headquartered in Hong Kong) took the next big leap, when in 2021 it began what is believed to be the first clinical trial for a medicine that has been developed wholly by AI. In a statement made by its chief scientific officer, the company said “we believe this is a significant milestone in the history of AI-powered drug discovery because to our knowledge the drug candidate is the first ever AI-discovered novel molecule based on an AI-discovered novel target”.
The birth of TechBio
With the direction of travel clear, the sector has been seeking a way to best acknowledge and accommodate the increasing prevalence of this new technology – and so we come to TechBio.
Whilst it is still hard to be precise about the exact nature of TechBios, they can be defined in comparison to their more traditional pharmaceutical cousins, BioTechs. As the name suggests, TechBios place an increased emphasis on the use of cutting-edge deep-tech and data-driven business models, and are likely to position themselves one step further removed from the eventual product. It is a subtle difference, but not one without precedent. A similar distinction happened in finance not too long ago, between FinTechs and TechFins. As Helen Panzarino of Imperial College Business School summarised, “FinTech companies’ core business is financial services…TechFin companies, in contrast, are technology companies that are leveraging their existing technologies, data, brands, customer bases or other assets to broaden their product offerings into financial services.”
Bridging investment appetites
So why must investor profiles evolve with the emergence of TechBios? The embrace of AI and deep-tech has not come without its challenges from an investment perspective. Whilst astonishing amounts of capital have been pouring into the TechBio space, most of the funds have been confined to investments in a few, select companies in headline-grabbing deals. When it comes down to it, the two traditional types of investors in tech and life sciences tend to have fundamentally different outlooks and risk appetites.
Life sciences investors are typically seeking an asset (a promising medicine candidate), backed up by credible scientific data. They understand the capital, time and regulation-intensive processes it takes to bring medicine to market. They also understand the inherent risks of the sector – most significantly, that being in it for the long haul might not even pay off.
In contrast, the tech investors are used to business models which focus on speed and innovating traditional ways of working – or which “move fast and break things”, to use a famous Mark Zuckerberg saying. Compared to a new medicine, a tech platform can be up and running swiftly, often with relatively little capital cost. Unlike a drug too, its evolution can come over time, whilst on the market. Nor – at least traditionally – have tech businesses been beholden to strict regulations around safety, efficacy and quality. Perhaps because of this, tech investors have less patience than life sciences investors when looking to get a return on their investment.
With increased emphasis on tech and the speed of development in this space, TechBios are bringing the two different attitudes into sharp relief. Yet we need more specialist investors to sit in this middle ground and understand the needs of this type of company. These include the need to have the right multidisciplinary team at the helm of the business and, crucially, for the company to strike the right balance between building a strong platform as well as having a number of promising therapeutic assets (either those of its own, or those generated in a collaboration). An investment approach that involves drip-feeding capital and which is dependent on having a clinical medicine candidate with little regard for the value of the platform and other non-therapeutic assets is unlikely to be a recipe for a TechBio’s success. Nevertheless, with all the hype that is currently surrounding AI, there is a weight of expectation that AI-enabled drug discovery will yield results at breakneck speeds. If a TechBio company has not been able to discover and validate a medicine target or a candidate within short order, investors will see it as a particularly risky venture.
Venture Capital activity shows that understanding of this sub-sector is growing and some specialist investors are emerging. But, as of yet, the pool is limited, and certainly in the UK/Europe. We need more. Building a TechBio business model can be harder than most, given the various uses their technology can be applied to. These businesses need experienced guidance to find the right use cases, and to de-risk and scale up. Key ingredients for a TechBio’s success include having diversity in its business models. Lessons learned from genomics companies that boomed in the dot-com era and then crashed, indicate that, for the long-term survival of a TechBio, it will need a healthy mix of strategic collaborations whilst also keeping one eye firmly on its own pipeline, and not just the pipelines of its pharma partners.
Only one point to score?
The lines are blurring, as sector borrows from sector to push forward. Interestingly, just as life sciences is borrowing from tech, so tech is borrowing from life sciences. Increasingly, the tech giants of the world are transforming their AI initiatives into something that would be more familiar to pharmaceutical-style demonstrations of value, creating wet labs for their testing (e.g. as seen with Isomorphic Labs, set up by Google’s parent, Alphabet).
There is wealth of opportunity there for investors, in the middle ground. It will come with time, but the traditional investors in the UK/Europe are not pivoting fast enough to keep apace with TechBio. The US investment community is betting heavily on TechBio and perhaps lessons are to be learned from across the pond. Almost twenty years ago, Frankie Goes to Hollywood sang “when two tribes go to war, a point is all that you can score”. Is it time to drop the two tribes and focus on creating a more sophisticated community of investors to support TechBio?