Cloud computing and biotech are the two most important nonlinearly-growing economic sectors. These two sectors intersect in Seattle in a unique way that has important implications for all involved. Small changes now will make big changes in what our lives are like decades from today, and Seattleites will have a ringside seat.
For now, there are only three organizations with the resources and outlook to be cloud providers: Amazon, Google, and Microsoft. Two of the three are headquartered in the Seattle area, and the third, Google, has a research presence here. Only Microsoft and Amazon appear interested in supplying cloud services per se, and really are setting the cloud agenda. This leaves Seattle with a planet-wide dominance it enjoys in no other economic area except perhaps global health. Such dominance shouldn’t be taken for granted (see: aerospace), but for now if you want to drive the cloud agenda in research, development, startups, or bizdev, you are going to spend time in Seattle.
While Seattle is a top-tier biotech hub, there is no area of biotech where Seattle predominates the way it does in cloud computing. However, it happens that Microsoft’s and Amazon’s cloud groups take disproportionate interest in biotech. Amazon’s cloud leadership includes people with strong biotech backgrounds, and Amazon’s new South Lake Union campus is literally surrounded by cutting-edge biotech research. Health IT is a key sector for Microsoft, and the Azure group has reached out to genomics researchers and others.
Compared to big cloud users like FarmVille and Netflix, biotech isn’t a big cloud consumer, and biotech probably never will be the biggest. Conversely, recent events make the cloud very important to biotech. The most important such development is next-gen DNA sequencing, which has used new chemistries to produce lower-quality DNA sequences very, very cheaply. At the same time, lower read quality increases the computational task of assembling reads. The result is that computational analysis costs are often higher than the wet chemistry costs; sometimes many times higher.
Consider why this situation might cause DNA sequencer makers to have a collective forehead-slap. Instruments are inexpensive with ever-increasing capacity. Reagents are cheap and bound to get much, much cheaper. Yet computation costs are going up. What’s the one part of the business the instrument makers don’t have a big piece of? Computational analysis. Oops.
As computation needs rise, cloud computing can make a big difference. Cloud computing promises systematically lower computation and storage costs, and frictionless scalability. Local companies like Geospiza and Labkey (as well as my company, Insilicos) exploit these advantages to offer computational services that biotech instrument vendors may now be wishing they owned and controlled.
Until recently, biotech researchers typically didn’t track computing expenses because the expenses were usually small and many researchers didn’t pay for computing out of their own budgets anyway. Those days are over for DNA sequencing. Other areas of biotech, such as protein folding, routinely have big computation problems, and in proteomics and many other areas, computation problems are growing faster than computer capacity. In future, much of biology research will have to plan and budget for computation as an integral part of most experiments.
Inevitably, most of this complicated computing will be done using cloud computing. Cloud computing has such economies of scale that it ultimately wins for a lot of things, particularly where computation demand fluctuates heavily over a period of hours to days. Scientific computing fits this profile: big computation, varying drastically over the course of an experiment. Consequently, scientists who use cloud computing will have an edge of those who do not, and in due time computational biology will largely be performed in the cloud.
But what kind of cloud?
Microsoft and Amazon have different things in mind
