As mergers between the major seed and crop protection players move forward, I wanted to share two major lenses on how I think about these developments. These are not meant to be conclusive opinions, but rather thoughts on how to look at different sides of the same coin. I’ll share the “beneficial” lense this week, and the “skeptical” lense next week.
Consolidation is Necessary to Spark a Major New Wave of Biotech Innovation
Although GM technology has been commercialized for over two decades, the precision and exactitude of changing genetic material in plants and other organisms is only now starting to be mastered. Initial GM technology, described simply, bombarded plant DNA with foreign DNA by applying radiation and other gene manipulation methods in the hope that the foreign DNA would “stick” to the gene and be stable across subsequent generations of plants.
As plant breeding and GM technology evolved, plant biologists learned to more quickly identify DNA markers of a successful gene transfer, test if certain seeds contained the properly inserted genes without having to either grow the plant to full maturity or destroy the seed, and better predict how various genes were likely to interact and express themselves as part of a full-grown plant. However, despite these incredible scientific advances, at its core, it’s possible to argue that GM technology remains relatively “young”.
Fast-forward to today, the emergence of direct gene manipulation technologies like CRISP/cas9 and its equivalents, dramatic reductions in gene sequencing costs, large data sets of agronomic performance in real-world (field settings), and an emerging understanding of how plants interact with many other organisms (fungi, insects, microbes) suggest that biology and data are on a giant collision course with promising potential applications.
Early GM was about relatively rudimentary applications, focused on combating weeds or pests. New GM technologies suggest we can optimize plants for other things – so-called output traits (non-browning Arctic apples, better frying Innate potatoes, etc.), or even other productivity traits (drought resistance). If we move beyond the plant, by harnessing and optimizing other living things that interact with the plant and using data to optimize plant growing conditions – the possibilities seem endless.
The practical application and success of this technology is by no means a slam dunk. There are so many factors at play (think crops, microbes, soil, weather, and the farmer all influencing each other) that developing practical solutions for farmers from these theoretical optimizations is perhaps at worst, a agronomist’s fantasy, and at best, very expensive and complex to develop. However, the potential of the technology is huge.
The consolidation of R&D powerhouses (like Monsanto and Bayer) may be necessary to spark a major new wave of biotech innovation. Specifically, the ability to spread out the cost of all the R&D expenses associated with not only plant breeding and gene manipulation, but also potentially other organism optimizations, as well as acquiring, compiling and analyzing agronomic performance data may indeed only be possible if done by a few major agriculture players with the wherewithal to take on such R&D costs, timelines and risk.
Pushing this thinking, one can even argue that monopolies may not be a bad thing. But that’s only one side of the story… more on this next week.