As I’ve written about elsewhere, the innovation we get in life sciences is not the product of a big machine where we pour money and basic science in one end and inventions pop out the other. It’s much more realistic to understand innovation as an emergent property of a complex adaptive ecosystem. In other words, the value, cost and disruptiveness of new medicines and new medical technologies are the result of innumerable and unpredictable interactions between the different inhabitants of the ecosystem. This means that rather than thinking of life sciences innovation as the output of a machine, it’s more accurate to think of it as the fruit of a garden.

This is more than an academic distinction; it has important practical implications, as a recent paper in the journal Nature reveals (‘Papers and patents are becoming less disruptive over time’, Park, Leahey and Funk). This work tries to understand the well-documented decline in research productivity in pharmaceuticals, semiconductors and other fields by studying how much papers and patents break with the past – a sort of proxy measure of radical, disruptive innovation. Using data from 45 million papers and almost four million patents over six decades, they find a decline in disruptiveness. This is a remarkable finding, all the more so because it contrasts with the popular view that we’re living in an age of disruption. Even more interesting is Park et al’s explanation of this decline. It seems to be caused by increasing narrowness in the use of prior knowledge. If you work as a scientist or with them, you will recognise this specialisation as the modern malaise of research. As one of my colleagues puts it, we learn more and more about less and less until we know everything about nothing. The authors end their abstract by suggesting that slowing rates of disruption may reflect a fundamental shift in the nature of science and technology. In other words, R&D may be evolving to be less innovative, not more.

Just in case the real-world implications of this work for research-based life sciences companies aren’t obvious, let me draw them out. As different specialist fields advance, they become narrower. This makes it harder to synthesise knowledge within a discipline, let alone between disciplines. And since innovation, unlike basic research, depends on synthesising different streams of new knowledge, innovation is likely to become more incremental and less disruptive. To someone who has studied the evolution of other once ‘advanced’ industries, such as chemicals, this begins to look like the antecedent of a pharmaceutical industry that is largely commoditised and low margin.

If that ‘less innovative, less profitable’ future scares far-sighted leaders of the life sciences industry, it’s less clear how they should respond. The natural limitations of humans incline our scientists towards becoming narrower in order to become more specialised. To put it another way, making our specialists more generalist doesn’t seem feasible. If there is an answer, it might lie in what I call ‘T-shaped crosstalk’. Crosstalk is the constructive discussion across scientific and functional boundaries. T-shaped refers to the skills needed to hold such conversations: a combination of shallow, broad knowledge across many areas and narrow, deep knowledge in one chosen area. The challenge is to find, train and keep the rare people who are able to develop T-shaped skills and function as R&D’s ‘connectome’, to steal the apposite neurologists’ term for neural connections within the brain.

Darwinian evolution theory prepares us to expect paradoxes, such as the exquisite adaptation of some species that confine them to a niche or the prolific breeding of others destroying their habitat. The rapid advance of the life sciences may be presenting another paradox; advanced specialists can only communicate narrowly and so only innovate incrementally. Resolving this paradox, perhaps by developing T-shaped crosstalkers, is another challenge facing leaders of the life sciences industry.

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