High Performance Computing in Today’s Personalized Medicine Environment

The goal of personalized medicine is to shift from a population-based treatment approach (i.e. all people with the same type of cancer are treated in the same way) to an approach where the care pathway with the best possible prognosis is selected based on attributes specific to a patient, including their genomic profile.

After a patient’s genome is sequenced, it is reconstructed from the read information, compared against a reference genome, and the variants are mapped; this determines what’s different about the patient as an individual or how their tumor genome differs from their normal DNA.  This process is often called downstream analytics (because it is downstream from the sequencing process).

Although the cost of sequencing has come down dramatically over the years (faster than Moore’s law in fact), the cost of delivering personalized medicine in a clinical setting “to the masses” is still quite high. While not all barriers are technical in nature, Intel is working closely with the industry to remove some of the key technical barriers in an effort to accelerate this vision:

  • Software Optimization/Performance: While the industry is doing genomics analytics on x86 architecture, much of the software has not been optimized to take advantage of parallelization and instruction enhancements inherent with this platform
  • Storing Large Data Repositories: As you might imagine, genomic data is large, and with each new generation of sequencers, the amount of data captured increases significantly.  Intel is working with the industry to apply the Lustre (highly redundant/highly scalable) file system in this domain
  • Moving Vast Repositories of Data: Although (relatively) new technologies like Hadoop help the situation by “moving compute to the data”, sometimes you can’t get around the need to move a large amount of data from point A to point B. As it turns out, FTP isn’t the most optimal way to move data when you are talking Terabytes

I’ll leave you with this final thought: Genomics is not just for research organizations. It is accelerating quickly into the provider environment. Cancer research and treatment is leading the way in this area, and in a more generalized setting, there are more than 3,000 genomic tests already approved for clinical use. Today, this represents a great opportunity for healthcare providers to differentiate themselves from their competition… but in the not too distant future, providers who don’t have this capability will be left behind.

Have you started integrating genomics into your organization? Feel free to share your observations and experiences below.

Chris Gough is a lead solutions architect in the Intel Health & Life Sciences Group and a frequent blog contributor.

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