“We live in interesting times” – this is what we were told by Torbjorn Roe Isaksen (the Norwegian Minister of Trade and Industry) at the Cutting Edge festival in Oslo this week. I tend to agree and it is not the curse it once was. As we watched Cellink print a 3D ear during Itedale Namro Redwan’s short presentation and listened to Thomas Anglero (IBM) explain why the current generation are always on their phones (and making millions while seemingly taking endless selfies) it is difficult to argue that these aren’t interesting times.

A trend that is very interesting, and evident from all the talks I attended, is the importance of (and increasing reliance on) artificial intelligence/machine learning in all fields of research, including life sciences. We are entering an age of digital health, of precision medicine, and one of the keys to this field is the capacity to analyse the huge amount of data that is now so readily available.

I was in the early stages of my PhD when the first full human genome was released. It was the culmination of over a decade of work and a billion dollars of funding, and although I was conducting my research in plant sciences, it was still a hugely exciting development. The next challenge seemed to be how to deal with all the information that was now available (including all the other genomes that were being sequenced). The next decade saw new ways to analyse all the genes that had been identified, which generated even more data. We are now at a point where it is possible to sequence a human genome in less than a day at a cost of a few thousand dollars. Even MORE data.

Thus, the challenge life sciences is facing is how to use all the information it is producing to implement practical solutions to increasingly complex problems. Indeed, the data itself is showing us that the problems we are facing are more complex than we previously thought. As Daniel Thurley (Roche) explained, we have known about lung cancer since the 18th century, but until very recently it was classified as one of three types: small-cell, non-small cell and “other”. We are now discovering that non-small cell lung cancer alone is actually tens of distinct diseases. Indeed every single cancer is different and being able to characterise each cancer at the molecular level will enable more effective treatments. This is the world of personalised medicine.

Personalised medicine is something that has been suggested for several years, but with the increased use of artificial intelligence and the realisation that “expensive drugs are drugs that don’t work”, we are on the way to making them a reality.

Artificial intelligence and machine learning represent tools to process the vast amounts of information being produced. The clear message is not that AI will replace skilled workers, but that it will make us more effective and efficient researchers, workers and problem solvers.

The increase in the use of AI in the development of new therapies and diagnostics represents its own challenges in a world where intellectual property is a key part of any business strategy in this area. Developments in patent law around the world have impacted on how we obtain protection for computer implemented inventions, therapeutics and diagnostic methods. Having a multidisciplinary team of patent law experts capable of dealing with cross-overs between technologies will be key to obtaining protection in the world of digital health and personalised medicine.

Interesting times indeed!


“Expensive drugs are the drugs that don’t work” – Steinar Thoresen, Abbvie