Richard Daly joined DNAnexus roughly seven years ago as CEO after stints with Baxter Laboratories and as CEO of lab-based genetic sequencing company Visible Genetics. During his tenure with the company, he has shaped it as a global leader for the secure sharing and management of genomic data in the cloud to enable collaboration among researchers and clinicians alike. Daly took time recently to chat with Clinical OMICs Editor in Chief Chris Anderson about the history of the company, and its role in helping accelerate the delivery of precision medicine via translational informatics.
Chris Anderson: Can you provide me with a brief history of DNAnexus?
Richard Daly, CEO, DNAnexus: The company was founded nine years ago by three visionaries who saw the growth in the placement of gene sequencing instruments. Even though they had high expectations for the rate of that growth, they underestimated it. What they understood was that the data was going to overwhelm what is called on-premise compute—compute installations that are in the same building or institution of a sequencing instrument. Their thought was that the data could be taken into the public commercial clouds and then analyzed.
Around 2013, it became clear that there were some unique elements around the processing of genomic data. One was that there were very few high-volume sequencing centers around the world and the users of the data tended to not even be on the same continent as the sequencing center itself. So we encountered the issue that to be effective in processing this data, we needed to have a global network.
So we built a global network in 2013 and 2014, and the underlying compute engine of the platform to handle very large-scale problems in genomics. We began running the largest genomic analysis in the world on the cloud, and this gave us our early credibility.
[Since then] several other trends have kicked in that lead directly to translational medicine. As the cost of obtaining the sample began to drop significantly—and the ability to process data began to increase significantly—the value of the data began to rise rapidly.
And that gets us into translational informatics. That is, to take information from the research phase and apply it directly to patient care or drug discovery.
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