The analysis of large and complex data sets is key to developing the life sciences insights that will impact drug discovery and therapy development. At the same time, the speed at which these data sets can be analyzed directly affects how quickly new discoveries can be brought to market.
Artificial intelligence and genomics
Artificial intelligence (AI) is enabling scientists to extract the full value of underlaying data in their research and discovery for better, faster insights. Within genomics, AI has many uses that can contribute to the development of new therapies, including gene editing and variant analysis. The ability to work with and integrate the large volume of biological and clinical data involved in sequencing technologies is critical to successful AI initiatives in life sciences.
In addition to accelerating the time it takes to move from information to insight, AI can help scientists better understand the biology related to genetic variation for more personalized treatment. Most recently, we saw how genomics leveraged AI for COVID-19 vaccine development as scientists sought to understand how the virus spreads and affects the immune system.
By both generating new insights from large-scale datasets and streamlining analytical problems in genomics exploration, AI is helping life sciences organizations better understand genomic variation to guide approaches and areas to focus on for health and disease.
WWT, NVIDIA and Dell speed time to market for genomics use cases
WWT has joined together with NVIDIA and Dell Technologies to develop a reference architecture that supports the complex research datasets required for genomics use cases. Leveraging WWT's Advanced Technology Center (ATC), the team is facilitating and accelerating the analysis of genomic data with a reference architecture that incorporates best practices for computing, networking, storage, power, cooling and more in an integrated AI infrastructure design.
The ATC's high-performance reference architecture environment includes:
- NVIDIA Clara™ Parabricks. From DNA to RNA, NVIDIA Clara Parabricks delivers powerful acceleration to primary, secondary and tertiary analyses of genomic data. It does this with turnkey software designed for high-throughput labs, on-premises or in the cloud, and a technology stack that gives developers the ability to build powerful compute tools for genomics.
- Dell EMC PowerScale. Dell's All-Flash scale-out network-attached storage (NAS) delivers the analytics performance and extreme concurrency at scale to consistently feed the most data-hungry analytic algorithms.
Life sciences organizations can take advantage of the joint WWT, NVIDIA and Dell reference architecture in WWT's ATC to prove out concept models for genomic workloads before scaling the environment on-premises. This approach minimizes risk by reducing the initial financial and resource investments required to run models prior to scaling. It also speeds time to market with an environment ready-designed for genomic workloads.
