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Databricks Helps Turn Clinical and Genomic Big Data into Insights to Improve Patient LivesDatabricks, the leader in unified analytics and founded by the original creators of Apache Spark™, today introduced the Databricks Unified Analytics Platform for Genomics to help accelerate the discovery of critical medical treatments. With a single platform for genomic data processing, tertiary analytics and artificial intelligence (AI) at massive scale, healthcare and life sciences organizations can make advancements in personalized diagnoses and the discovery and development of potential new treatments. The Unified Analytics Platform for Genomics enables healthcare and life sciences organizations to process and analyze large-scale genomics data up to 100X faster than existing solutions, helping to accelerate critical research. The Databricks Unified Analytics Platform for Genomics was launched today at Spark + AI Summit, an annual gathering of 4,000 data scientists, engineers and analytics leaders. Watch the live keynote now. The first human genome took 13 years and over $3 billion to sequence. Today, a human genome can be sequenced in a couple days for less than the price of the latest iPhone (News - Alert). The rate at which sequencing technology is improving has exceeded Moore's Law, enabling healthcare and life sciences organizations to generate petabytes and, in the future exabytes, of genomic data for millions of patients. This data, when paired with additional preclinical research and clinical data, offers huge potential to help in the development of new medicines and improve patient outcomes. However, the tools and systems used by genomic researchers today struggle to contend with these massive volumes of data. Data processing and downstream analytics are the key bottleneck choking potentially life-saving research. "The opportunity to save lives with AI is enormous. By unifying data and AI, health and life sciences organizations are better equipped to develop personalized treatments and possibly even predict medical emergencies before they occur," said Ion Stoica, Executive Chairman and co-founder of Databricks. "Significant advancements in genomic sequencing have enabled healthcare and life sciences organizations to generate petabytes of data around medical research, but few organizations can fully leverage their genomic data for meaningful insights because the data is 'messy' and they lack access to analytics at scale."
Genomics Platform Builds on Databricks' Work in Healthcare and Life
Sciences According to Jeffrey Reid, PhD, Head of Genome Informatics (News - Alert) at Regeneron, "As this dataset has grown rapidly, we encountered significant barriers in simple tasks, like gathering all of the data for a given analysis, and querying the 10s of billions of results from our studies. Not only has the Databricks Unified Analytics Platform solved these big data problems, but it is enabling everyone in our integrated drug development process - from physician-scientists to computational biologists - to easily access, analyze, and extract insights from all of our data. Drug development is still a long and difficult process rife with failure, but we have already significantly reduced the amount of time it takes to generate important early insights." Through working with companies across the health ecosystem, Databricks has identified common genomic data formats and analytics used in many popular healthcare and life sciences use cases and optimized them to achieve orders-of-magnitude performance improvements at unprecedented scale. These insights have played a critical role in the development of the Unified Analytics Platform for Genomics.
Genomic Data Processing and Interactive Analytics at Petabyte-scale The Unified Analytics Platform for Genomics enables healthcare and life sciences organizations to:
To learn more, please visit booth #401 at Spark + AI Summit or visit our website at www.databricks.com/genomics. Additional Resources
About Databricks Apache, Apache Spark and Spark are trademarks of the Apache Software Foundation.
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