“Lunch & Learn” to Explore the Growing Applications of Genomic Analytics

By Vineeth Ram, VP, HPC and AI Segment & Data Center Experience Marketing, DCIG Marketing, Hewlett Packard Enterprise

October 10, 2017

In the digital age of medicine, healthcare providers are rapidly transforming their approach to patient care. Traditional technologies are no longer sufficient to process vast quantities of medical data (including patient histories, treatment plans, diagnostic reports, and more), challenging organizations to invest in a new style of IT to enable faster and higher-quality care. High performance computing (HPC) technologies are empowering healthcare professionals with the compute resources needed to fuel scientific discoveries and take on the health challenges of today and tomorrow.

Genomics—the study of the human genome—allows medical professionals to analyze a patient’s unique genetic makeup in order to deliver more effective and personalized care. Genomic sequencing analytics is driving major advancements in precision medicine, from identifying genetic conditions and predispositions to disease, to enhancing pharmacogenomics and much more. The ability to quickly analyze and derive insight from genomic datasets is key to surviving in this evolving marketplace, providing patient-centric care, and improving clinical outcomes.

REVOLUTIONIZING PATIENT CARE

Next-generation sequencing (NGS) technologies are driving rapid innovation in the life sciences. According to a report in the PLoS Biology Journal, between 100 million and 2 billion human genomes could be sequenced by 2025, leading to major breakthroughs in our knowledge of the human body. Backed by powerful HPC solutions, healthcare organizations are using NGS capabilities to advance bioinformatics, accelerate medical research, and enhance patient diagnosis and treatment.

Genomic applications are fueling several other important trends in the life sciences:

  • Integration of research and clinical diagnosis and treatment
  • Rise of pharmacogenomics, the study of how genetics contributes to a patient’s response to drugs
  • Advanced genome editing techniques
  • Noninvasive cancer screening
  • Direct-to-customer genetics, letting patients explore their genetic makeup
  • Growth of newborn genetic screening programs
  • Harnessing new data streams, such as mobile applications and biometric devices

Hewlett Packard Enterprise (HPE) offers powerful solutions that are optimized for genomic analytics. The HPE NGS solution features unified compute and storage to deliver the performance, scalability, and reliability required to process data-intensive workloads. Backed by robust HPC servers, the HPE NGS solution is architected with flexibility in mind to support evolving IT requirements, equipping scientists to accelerate insights and harness the growing applications of genome assembly and analytics.

According to Peter Longreen of the Center for Biological Sequence Analysis, Systems Biology, Technical University of Denmark, high performance architectures designed for data-intensive applications are dramatically enhancing data analytics and enabling scientists to process multiple workloads at once, accelerating time to insight. Their research teams can now complete 41 genome assemblies in the time it previously took to complete just five assemblies.

TRANSFORMING THE FUTURE OF HEALTHCARE

HPE is striving to accelerate genomics research with leading-edge technologies designed to optimize a variety of complex workloads and derive genetic intelligence at lightning speeds.

Coming to select cities: “Lunch and Learn” events with HPE, Intel, and a leading IDC analyst, where you will hear about what HPE and our partners are doing to enable business innovation, achieve breakthrough results, and revolutionize genomics. Attendance is limited – register today!

To learn more about the future of healthcare as well as the exciting applications for HPC genomic sequencing, visit HPE on Twitter at @HPE_HPC. And for the latest news and updates in HPC innovation, I invite you to follow me at @VineethRam.

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