PALO ALTO, Calif., June 06, 2017 --Cloudera, Inc., (NYSE: CLDR), the leading provider of the modern platform for machine learning and advanced analytics built on the latest open source technologies, announced that Inova Translational Medicine Institute (ITMI), a global leading medical research institute, has deployed Cloudera Enterprise to securely analyze massive collections of clinical and genomic data at unprecedented speeds and scale for faster innovations in translational medicine research. As part of the Inova Center for Personalized Health (ICPH), ITMI's team of leading scientists, researchers, analysts and collaborators use machine learning algorithms on terabytes of clinical and genomic information to identify the genetic links to diseases. They make discoveries from the data insights and, in collaboration with the treating physician, develop personalized treatment plans for patients. This approach is also known as precision medicine and has the power to help patients live longer, healthier lives. Genetics plays a role in the majority of leading causes of death in the United States, including heart disease, cancer and diabetes.
The same four chemical building blocks behind almost all life on earth could one day be used replace traditional computer storage. Genomics England is using a relational database to power the data science behind its ambitious 100,000 Genomics Project. The organisation, which is owned by the UK's Department of Health and Social Care, runs the project, which is sequencing 100,000 whole genomes from patients with rare diseases, along with their families, and also patients with common cancers. The project has now reached its halfway point, with over 50,000 genomes sequenced. By the end of 2018, the 100,000 genomes project will be complete, with more than 20 petabytes of data stored on the project's infrastructure.
A genome is the body's instruction manual. It's made of DNA and there is a copy in almost every cell. Through genome sequencing and genomics, clinicians can better understand how cancer cells might evolve and what treatments will be most responsive, known as precision and personalised medicine. Furthermore, genomics combined with technologies such as machine-learning and artificial intelligence (AI) has huge, as yet untapped, potential for determining a healthy person's future risk of cancer. To sequence the first genome cost $3 billion and took 13 years.
As our ability to sequence genomes has skyrocketed, allowing us to churn out A's, C's, G's, and T's at breakneck speed, our capacity to decipher the sequences has not kept up. This issue was discussed at a recent meeting organized by Advances in Genome Biology and Technology. "We have well exceeded our ability as humans to deal with data," said Eric Topol, MD, founder and director of the Scripps Research Translational Institute, professor, molecular medicine, and executive vice president of Scripps Research. "We need help from machines." To have high-performance medicine, he asserted, "we need high-performance computing."