January 22, 2018 | Written by: Yael Shani
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Advancements in medical science and technology continue to reduce the time and cost of genomics sequencing, bridging the gap between research and clinical decision support.
If your IT infrastructure cannot meet your analytical and data demands – or worse, is slowing research and collaboration and minimizing your ability to take the most informed decisions – there are some efficient ways to address this.
Adopting the right approach to storage, compute and network will allow your organization to analyze massive amounts of genomics data and easily achieve faster insights and cost savings.
The rise of genomics
The completion of the Human Genome Project in 2003 led to an expansion of research on the contributions of genomics in disease diagnosis, treatment, and prevention.
Today, genomics data is perceived in the industry as a very useful source which is becoming an increasingly integral part of the healthcare equation.
While genomics sequencing has the potential to significantly accelerate precision medicine, it requires the ability to store, access, secure, manage, share and analyze large volumes of data very fast. The ability to quickly access patient’s genomics data and provide real-time analytics-based treatment relies on a data architecture that is based on flexible, scalable and cost-effective high-performance systems. These systems will ensure the highest levels of data availability and reliability.
Most of the organizations already recognize the importance of genomics data and analytics, but have not necessarily made all the required changes to their infrastructure to support it.
IBM’s integrated solution for genomics (https://www.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=TSS03239USEN&dd=yes&) is based on composable infrastructure that disaggregates the underlying compute, storage and network resources. This software-defined solution creates a single, cohesive infrastructure for genomics that can scale each individual resource independently based on actual needs. Leading healthcare and life sciences institutions that have based their genomics workloads on IBM technologies are benefiting from optimized performance, cost and time for final analysis.
Your infrastructure can do more
Organizations dealing with genomics workloads need a powerful foundation to support the acceleration of discoveries, the advance of personalized care and the optimization of services.
When you explore the capabilities of IT solutions that are available in the market and their ability to fulfil the needs of your most demanding workloads – don’t compromise on:
- Speed: Efficiently locate genomics data and applications in the optimal storage tier based on performance and cost objectives using policy engines and analytics-driven data management. This will improve performance, agility, flexibility and scalability to support intense workloads and demanding application requirements.
- Price-Performance: Avoid silos by moving to a shared compute and storage infrastructure based on advanced software to consolidate and transform static, siloed systems into a dynamic, integrated, and intelligent infrastructure, resulting in faster analytics and greater resource utility.
- Collaboration: Provide researchers and physicians with greater ability to perform discovery, diagnosis and treatment by allowing anytime, anywhere collaboration across geographic boundaries.
- Simplicity: Choose a solution that has been fully tested and allows your IT architects and IT administrators to easily design, install and manage deployment in a timely manner without being overwhelmed
Genomics deployments: how to get it right with software-defined infrastructure – Wednesday February 14 at 11:00 am EST
Register Now: http://bit.ly/2rbGXJP
Join us to learn how healthcare and life science organizations dealing with data-intensive genomics workloads can benefit from scalable, flexible, high-performance compute and storage solutions that can make genome sequencing faster and less expensive.