Medical innovation transformed

Medical innovation is being transformed. Two questions will determine the winners, say Christian Heubeck and Stephan Jellbauer at Weickmann: who can innovate inspired by AI and who best adjusts their IP

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Christian Heubeck and Stephan Jellbauer

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We are at the start of a whole series of transformational innovations in medical technologies. However, we cannot expect them to happen based on the classic models for discovery and commercialization. The process of medical innovation itself is changing and the eventual winners may not be who we expect.

There will be scope for disrupters, of course, but the balance of risk and reward is shifting towards those who manage the data on which AI depends. However, it is far from inevitable that existing industry structures will be replaced. Outcomes will revolve round two questions: who can master new ways of innovating inspired by AI? and who can adjust best to managing the asset on which medical innovation ultimately depends for realizing its value: intellectual property?

Computer modelling is transforming medical innovation. Previously, you first conducted a long process of research and trials, before launching an initial version. Only then would you start to gather insights into how it was performing. In many cases, of course, innovations never reached this point, overcome by any number of points of failure.

Now at the start, you can use AI to survey thousands of existing treatments against your target structures, such as proteins. You can then use a series of specific simulations to see what works best. You then may have a few compounds left that you can test in the lab and modulate the effects on the receptor.

Such modelling lets you synthesize compounds that are already known or might be even new and delay live tests until much later. One example of such innovation is where immune cells, such as T cells, from a patient are isolated and then re-programmed to treat a specific condition.

As a result, innovation will look and feel significantly different. Less time and resources will be necessary in the lab, as experimentation by trial and error is replaced by more computer modelling and simulation. One effect is that less reliance will be placed on live testing and it will only happen much later in the process.

To a high degree, medical innovation relies on the capture of IP to secure its value and its transfer into practice. Otherwise the whole chain of value falls apart. However, if the dynamics of medical innovation have changed, do our assumptions still hold about patents as the preferred route for securing the value in inventions? Or is it better to consider alternatives to keep pace with disruptive competitors whose models rely on data?

We began to see the outlines of what models might emerge in response to the pandemic. Without the use of computer models, it would have been next to impossible to target such a specific part of the virus as its spike. Trial and error in the lab would have taken too long. Moreover, IP proved that it was equal to the task of moving at the speed that today’s blockbusters require. It created the foundation for all the partnerships that formed and operated on an express schedule.

As of today, it appears that patents will remain integral to medical innovation for the foreseeable future,. However, a series of questions are coming into view about their extent and use. For now, answers tend to vary depending on where you are located. We are in the midst of a deep transformation, after all.

• The full article, ‘AI, personalised medicine and IP’ by Christian Heubeck and Stephen Jellbauer at Weickmann appears in ‘Winning with IP: Managing intellectual property today’, third edition, Novaro Publishing, October 2022.  See here for details.