Recent advancements in Artificial Intelligence (AI) have captured the attention of the life sciences and Medtech sectors, promising revolutionary changes.  At the recent LSX USA Congress in Boston, Massachusetts, where discussions frequently turned to the transformative potential of AI, excitement about the topic was at times palpable. Despite this though there was equally at times frustration and a sense that the topic was being over referenced and associated effects overstated.

As Secerna Partner, Jason Boakes, reflects on his experience at this event, it's impossible to ignore how AI is reshaping these fields and presenting both unprecedented opportunities and significant challenges for innovation, investment, and intellectual property.

Machine based adaptability and autonomy… don’t mention the A-Word

No reflection on my experience at the LSX USA Congress in Boston, Massachusetts last week would be complete without making reference to Artificial Intelligence (AI) and its impact in the Life Science and Medtech sectors. Of course the term AI itself is hard to clearly and fully define. The UK government says:

“An AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment.”

The term AI was coined in the 1950’s at a meeting at Dartmouth College again in Massachusetts, USA. Testament to that region’s consistency at an elite level in hard science. In the 50’s much of what we now think about AI was yet to be conceived of and some things that were considered AI related then like aspects of image processing would today already start to fall outside what many think of when the term is mentioned. AI is a movable feast in the sense its meaning changes with the times. I don’t know what it looks like, but I’ll know it when I see it.

Today much reference to AI is made in the context of Large Language Models (LLMs) like ChatGPT. User prompts are processed by analysing patterns in training datasets and most likely and hopefully useful outputs that might be text or image based are provided. It is the use of these models that many CEOs and business leaders, having a fear of missing out, are effectively challenging their businesses to use with the call to action “How can we use AI.”

For many at the cutting edge of investment and technological research where the operation of such models is well understood the term is starting to feel overhyped. A proliferation of new products in almost every field makes it operationally inefficient to benchmark and review the countless new offerings. Often any benefit is limited and quickly superseded. Risks associated with data privacy and confidentiality breaches can quickly offset any advantage derived from such use. Those businesses that use AI in such a context though can call themselves “innovative” using the lowest bar possible for qualification of that term and pat themselves on the back. More rarely is any true innovation in the sense of the creation of something new in a non-obvious way being achieved.

For some uses though the combination of inference engines and neural networks in association with healthcare hardware like robotic surgical tools or imaging devices is undoubtedly going to bring fabulous breakthroughs and open up new tantalising opportunities. Likewise, the ability to analyse huge datasets and spot trends and patterns will lead to the possibility of early and accurate diagnosis of disease and data driven discoveries that will themselves lead to lifesaving multi modal drugs and cell therapies. Seed or Series A funding and indeed later stage funding, particularly when PE is already invested and cannot get out, is still available despite the Biotech Winter.

Whilst Core AI advancements are relatively speaking more rare and associated patentability concerns more “traditional”, the patent landscape for applied AI inventions is littered now with sometimes well developed and sometimes spurious and opportunistic filings in almost all but the freshest of technical fields. Patent Offices themselves are finding it challenging to settle on agreed approaches for assessing the non-obviousness and indeed eligibility of AI related innovation in the Medtech and Life Science fields where that approach should balance offering due reward to those making incredible breakthrough with those who should have the right to operate in a way that builds only on what is well known and is “lying in the road”. Never has it been more important to have skilled and experienced patent advisors to help secure protection for your developments or help you clear the way as you seek to penetrate a new market.

 - Jason Boakes (Partner, Secerna LLP)