JP Morgan in Review: Expect Rapid Evolution in Sequence Analysis and Big Data Needs

Last week’s JP Morgan Healthcare Conference was the usual biotech extravaganza, filling downtown San Francisco with so many analysts and investors you could mistake it for Wall Street. The great thing about this event is that it serves as a platform for all of the presenting companies to lay out their plans for the new year — giving the rest of us guidance about what to expect.

jp morgan healthcare conference

Illumina, for example, announced its acquisition of Stanford spinout Moleculo, which has developed a way to generate multi-kilobase reads from sequencing-by-synthesis technologies. With Moleculo’s IP, Illumina will likely have users producing very long sequence reads in the first half of this year, though currently most existing assemblers and other sequence analysis algorithms have been optimized for much shorter reads. If this long-read technology performs as advertised, we anticipate a flurry of activity as developers tweak their aligners and assemblers to make the most of these multi-kilobase reads.

In applied markets, Illumina acquired prenatal testing firm Verinata Health, and Life Technologies announced the formation of Claritas Genomics, a joint venture with Boston Children’s Hospital to develop diagnostics for the Ion Torrent sequencing platform. With these moves, both companies continue their march on the clinical market — giving us even more certainty about the need for sequence analysis and interpretation tools that will fit the requirements of users in clinical labs. These downstream users will be best served with simple but highly customized tools that match their specific environment, tasks, confidentiality mandates, and other attributes.

In general trends, the focus on big data was inescapable at JP Morgan, and served as a particular highlight of a breakfast panel hosted by FierceBiotech. No longer just the concern of chief information officers, big data is seen as equal parts opportunity and pitfall in the biomedical and healthcare field. Lon Cardon from GlaxoSmithKline encouraged people to think of it as good science rather than just “big data.” Meanwhile, John Reynders from AstraZeneca noted that the value of big data lies in the human element — that is, how we query it and what we’re looking for.

Back at DNAnexus headquarters, where we’re putting the finishing touches on our new platform to enable people to make the most of big data, the observations from JP Morgan offer nice validation of the path we’ve been planning. Our new platform has been designed for flexibility, giving users control over which algorithms best fit their data — whether those data sets are small or large in size, based on short-read or long-read sequence, and more. And with the growing use of sequencing in the clinical realm, we have worked hard to make sure the new platform will be a good fit for users who must comply with HIPAA and other regulatory requirements. Check back with us often, and we’ll keep you posted as we get the new platform ready for its debut!

Relationships for Innovation

This week we announced new agreements with two premier healthcare institutions: Geisinger Health Systems (GHS) and the University of California, San Francisco (UCSF). We also announced, with Complete Genomics, our participation in its Genomics Discovery Partners program.

Each of these relationships opens exciting new opportunities. NGS technology generates terabytes of data requiring enormous storage capacities and supercomputing processing power to extract meaningful information. Academic research centers, university hospitals, and commercial organizations risk being overwhelmed by this rapidly growing amount of data. As researchers and clinicians seek to integrate these datasets into their work, industry leaders are increasingly investing to meet this data management analysis challenge.

We are excited to enable these industry leaders to innovate solutions with us on our cloud-based platform. GHS is integrating its genomic data assets with clinical applications, including parent-child trio studies for disease characterization and prevention. UCSF is uploading, managing, and analyzing sequencing data for large-scale genome sequencing research applications. Complete Genomics is offering our data management and visualization services to customers of their human genome sequencing service.

These relationships exemplify ways we help organizations to capitalize on opportunities created by the growing ubiquity of low-cost genomics data. Together we are applying these experiences to create new services and capabilities that support their customers, researchers, and clinicians.

Check back often for updates on these and other collaborations in the works.

Sequence Data: The View from JP Morgan

Last week, Andrew Lee, Vice President of Strategic Operations, and I attended the JP Morgan Healthcare Conference, an annual investor conference here in San Francisco that brings some 25,000 people to the city. The big news this year came from Life Technologies and Illumina, which both announced platforms that will be capable of sequencing an entire human genome in a day. Life Tech in particular noted that its same-day genome sequence will cost $1,000 in reagents — effectively putting an end to a race that began 10 years ago, when scientists first started seriously competing to achieve the $1,000 genome.

With this price point achieved, we expect people to sequence genomes at a much faster clip than ever before. Indeed, a survey from GenomeWeb and Mizuho Securities found that scientists anticipate that sequencing data will increase 32 percent this year over 2011, and increase another 38 percent next year compared to this year. That’s exciting on the data analysis front: As the volume of DNA data grows exponentially, it’s even more important to have a scalable platform to manage, store, and analyze that data securely and efficiently. The GenomeWeb/Mizuho survey also found that people expect to spend more on informatics in 2012 than they did in 2011.

After all, mainstream genome sequencing won’t be possible until the analysis costs come down by orders of magnitude. Even with so much attention on cutting the price tag for sequencing technologies, that didn’t translate to matching improvements for data costs. The race to the $1,000 genome may be over, but as it turns out, that was just the first leg of a relay. Now the baton has been passed to the data management and analysis folks, and it’s our turn to run as fast as we can.