TGen Case Study
The 2020 outbreak of the COVID-19 (SARS-CoV-2) pandemic has united the world in a common fight, at the forefront of which are medical workers, researchers, and scientists. As an organization dedicated to “conducting groundbreaking research with life-changing results,” the Translational Genomics Research Institute (TGen), an affiliate of City of Hope, is a part of the global medical community that actively seeks ways to treat and eliminate COVID-19.
TGen is an Arizona-based research institute that has been conducting research on numerous human diseases and forms of cancer since 2002. To help the global fight against COVID-19, TGen is working to develop a centralized, aggregated dataset that can automatically pull COVID-19 sequenced genomes and other related data from multiple sources. This dataset can help improve research, data analysis, and increase understanding of the viral genome.
- Lack of a shared data repository of SARS CoV-2 genome and related metadata
- Time-consuming data analysis processes
- Difficulties in sharing knowledge between researchers globally
- Limited infrastructure capabilities to execute diverse computational workkflows
phoenixNAP’s custom Hardware-as-a-Service solutions powered by Intel Xeon Dual Gold 6258R CPUs, Intel NVMe’s (P4610) using Intel VROC, Intel NICs, and Intel Optane persistent memory, expanding memory capacity (128Gb DRAM + 1536GB Intel PMem); Intel® Tofino™ Programmable Ethernet Switch Products.
- Fast data processing with Intel PMem compared to traditional RAM
- Centralized platform for global data access and analysis
- Integrated database for more efficient research on a global scale
- Optimized infrastructure for compute-heavy workloads
“Sifting through genetic data for useful information is crucial in helping bring treatments to patients faster, and we are thrilled to work with Intel utilizing technologies such as Persistent Memory to accelerate not just the pace of discovery, but our ability to find answers in the data. TGen is Looking forward to leveraging Intel Persistent Memory to accelerate genomics DB performance.“