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| 5 minutes read

The birth of techbio - but what does techbio want to be when it grows up?

BIA’s TechBio UK Event

Bristows had the pleasure of attending TechBio UK 2022 on 13 October. It was a fantastic event held by the BioIndustry Association (BIA) that celebrated the emerging “techbio” subsector, which already has a thriving community in the UK. There were lots of cram-packed sessions, with valuable insights from many different speakers. There is too much to report on in one go – but here are some key takeaways from the day about the growth of techbio, and the journey that a business might take in this space - including some of the factors that are likely that lead to its success.

For a start, what is techbio? 

The term “techbio” is a little difficult to pin down precisely, but essentially captures deep-tech, data-driven businesses working at interface of biotechnology and technology, using their tools (such as AI) and insights from data to inform and transform drug discovery and patient care. The distinction between “techbio” and “biotech” is perhaps one of only a few degrees – with techbio businesses typically being one step further removed from the eventual product (be it a therapeutic or a device) but who work with traditional biotech and pharma companies in the R&D process. Techbio also differs from “healthtech” and “digital health”, whose focus is more pointed towards developing technology for delivery in a healthcare setting. However, these roles are often blurred and overlap in practice.

What investment is going into techbio?

A staggering amount of capital is being poured into techbio. In particular, the majority of funds are being invested in a few, select, companies who have managed to raise hundreds of millions and grab the headlines. Although the level of the investment in techbio has softened a little this year, this overall trend is expected to continue.

More generally, plenty of money is being spent on AI in drug discovery, across the whole of the life sciences sector. Speaker Vanela Bushi (from Hoxton Ventures) aptly reminded us of the Lewis Carroll quote from Alice in Wonderland: “My dear, here we must run as fast as we can, just to stay in place. And if you wish to go anywhere you must run twice as fast as that". Essentially, whilst AI and machine learning (ML) promise to bring new insights, deliver efficiencies and accelerate the drug development process, and therefore have the potential to mitigate the rising costs of R&D, perversely at the moment the costs of drug discovery are going up whilst these new technologies are establishing themselves.

What are investors looking for? Are there “two tribes” of investors?

Historically (and broadly speaking of course) there have been “two tribes” of investors. On the one hand there are the traditional biotech investors – who typically are looking to invest in companies that have discovered assets which are in (or earmarked for) the clinic, who heavily scrutinise the company’s data and proposed business model, and who are familiar, and relatively comfortable, with investing in companies that operate in a highly regulated environment. On the other hand, there are the traditional tech investors – who are particularly focussed on investing in companies that are building a platform, and who are perhaps more relaxed around what the business model looks like, but are more apprehensive about companies working in a very demanding regulatory landscape.    

There is a good number of traditional biotech investors in the UK/Europe but the feeling is that, on the whole, they are not moving or adapting fast enough for techbio. It seems that more traditional tech (as opposed to biotech) investors at the moment are making their move into this space. The good news is that more investment is now coming into the interface between tech and biotech, but there is a recognition that the UK/Europe needs more specialist investors for techbio (particularly for later stage funding) – something which is already happening in the US. Specialist techbio investors are looking for companies that have a good balance of both some promising assets AND a platform/non-therapeutic assets, with (importantly) strong IP around them.

Like any investor, techbio investors are looking for companies that have a good team – this is a key ingredient for success. In techbio, this needs to be a multidisciplinary team, but beyond that, what does a good team look like? The challenge in techbio is there is not a notable pool of people who’ve “been there, done that” and so the skills may not be there in most cases, or they are there but are not yet widely recognised. As one speaker at the BIA event said “there is no compression algorithm for experience”. Equally, companies in this space need to think carefully about the types of investors they bring in, who will be with them over a large part of their journey. If there is a diverse range investors around your Board table, how will that pan out?

Beware of the hype!

In various sessions throughout the day, a number of speakers were saying “beware of the hype”. When investing, it is important to establish that the technology is underpinned by good scientific evidence – as currently there is a tendency for the value of a business to become inflated just because AI/ML or large datasets are involved. In his keynote speech, investor and entrepreneur Andy Richards drew parallels with the dot com boom - which brought with it a new era of drug discovery, and in particular a rise in genomics companies. Back then, enthusiastic investors were buying into a similar model, valuing companies e.g. based on how much DNA they had sequenced or the size of their libraries that could be used against the targets, often with little or no validation. Then the bubble burst in 2000-2001. Andy said, “hyper growth in healthcare is dangerous". Some companies pivoted, but the rest fell by the wayside. In hindsight, those few businesses that survived were usually those who had built their own pipelines. In light of this, the perceived risk of investing in a techbio company today is relatively high, unless that company has been able to validate a target or candidate in the clinic - and in double quick time!

Techbio business models - challenges and opportunities, and growing up

In techbio, a key challenge for those starting out is finding the right business use cases, given the range of potential applications for which their technologies could be deployed. It is vital for techbio companies to collaborate with pharma and other players in the sector (and to take a sophisticated approach to partnering) to de-risk and scale up, and, in the process, work out what direction they should head in. Likewise, pharma is increasingly working with techbio organisations to help de-risk the drug discovery process. In some cases it can be hard for pharma to differentiate between the various AI/ML offerings out there and learn about the various companies’ individual strengths and specialisms. Pharma is now starting to do more paid-for evaluation work with companies up-front, to see if they are the right fit before embarking on a full collaboration.  

There is a good and varied range of businesses building up in the UK techbio space, who are tackling a range of problems with different approaches – creating competitive pressure in the marketplace. However, it was a clear takeaway from the event that how important it is for techbio businesses to have diversity in their own business models – who normally would be best advised to have a healthy mix of strategic partnering whilst also keeping an one eye on developing their own pipelines. In the words of Inga Deakin (Molten Ventures), the key question that they need to answer is “What are you going to be when you grow up?”  A pharma company? A biotech business?  A research tools provider? She advised that techbios should not just focus on the short term (which is often getting a quick exit and cashing out). The businesses that will be sustainable are the ones that focus on the longer term and – often it seems – those that use their technology to discover and develop assets for themselves, and in doing so transition from being a techbio into something else.


techbio, biotech, artificial intelligence, corporate and financing, health tech, life sciences, robotics