Biotechnology Must Head for the Cloud

Sajith Wickramasekara

It’s clear that the rate of hardware innovation in life science is staggering. Illumina recently made headlines by announcing it had dropped the cost of sequencing one human genome to a mere $1,000. While this cost excludes the much greater costs associated with data analysis and interpretation, it’s still a remarkable milestone considering that the first human genome cost $3 billion to sequence just over a decade ago. That’s a 3,000,000x improvement.

In contrast, the state of software is unacceptable and progressing much more slowly. How many scientists do you know who use spreadsheets to organize DNA? Or who collaborate by emailing files around? Or who can’t actually search their colleagues’ sequence data? If synthetic biology is going to reimagine genetic engineering, it won’t be on the foundation of archaic software tools.

We need a cloud-based platform for scientific research, designed from the ground up for collaboration. Legacy desktop software has compounded systemic problems in science: poor scientific reproducibility, delayed access to new computational techniques, and rampant IT overhead. These issues are a thorn in the side of all scientists, and it’s our responsibility to fix them if we want to accelerate science.


The reproducibility of peer-reviewed research is currently under fire. Scientists at Amgen tried to reproduce 53 landmark cancer studies, only to find that all but 6 could not be confirmed ...

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