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Tech-bio vs biotech. We need less labels and more understanding of technology.

Our research on understanding how science and technology innovation is commercialised identified the critical importance of Internal Vector I1, which describes the conditional (or contingent) technology deployment model.

The Triple Chasm Model shows how this Technology Vector constitutes just one of the 12 Vectors critical to understanding commercialisation: it also illustrates the importance of not conflating technologies with markets, and of distinguishing between ‘pervasive’ digital technologies which can be applied across multiple market spaces and the vast array of scientific and technological innovations, with their own detailed taxonomies, which impact a smaller number of market spaces.

Understanding technology types is particularly important given the massive impact that digital technologies have on the creation, distribution and deployment of new products and services across a very wide range of market spaces. The Triple Chasm research revealed that commercialisation of new products and services can be segmented into 5 types of technology relevance as follows:

  • Type 1: Technology has no relevance at all, for example the creation of a new type of sandwich

  • Type 2: Which addresses digital technologies, where we can distinguish between 3 sub-types of digital technology relevance based on the application of digital technologies to enable commercialisation, which can be characterised as follows:

  • Type 2A: The deployment of generally available digital tools and techniques which can be used to manage the creation, distribution, and delivery of innovations, conventionally described as IT

  • Type 2B: Deployment of digital tools with a strong focus around data management, which enables the distribution and deployment of new innovations, for example, in media and telecoms or healthcare market spaces

  • Type 2C: The new generation of digitally enabled innovations, where virtual reality tools popularised as the ‘metaverse’ and ‘generative’ tools based on AI and machine-learning can generate new commercialisation pathways

  • Type 3: Which covers a very wide taxonomy of technologies which can provide the fundamental basis for any commercialisation, for example, the science behind new biomarkers, new kinds of material, or advances in quantum engineering.

These different technology types, based on the intensity of the digital interaction, can have significant impact on the structure of new market spaces and intellectual property: for example, Type 2A is unlikely to generate new IP but Type 2C raises interesting questions about how IP is generated and who owns it.

All this has important consequences for popular conceptions of commercialisation and the language used mainly by the investor community to describe their preferences. These include:

  • The historical demarcation used (for example by business schools and some investors) to differentiate between ‘tech’ and ‘bio’ is largely meaningless

  • The use of ‘tech’ as a pre-fix or a suffix (mainly by investors) are not accurate: terms like med-tech largely describe the integration of digital technologies with say a specific medical sensing technology (generally a Type 2A or 2B); fin-tech covers the automation of existing functionality (Type 2A or 2B); and the use of biotech is unclear but may have little to do with digital (probably a Type 3)

  • All these contortions have led to attempts to describe new AI-based approaches as ‘tech-bio’ (cf biotech), without really understanding the relationship between Type 2C digital technologies and Type3 advances in the biological sciences

  • Commercialisation strategies for new therapeutic innovations require a detailed understanding of the linkage between Types 2C and 3, coupled with clinical insights in emerging market spaces.

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