Announced at AWS re:Invent, Amazon Omics is designed to help healthcare providers and life sciences organizations store, query and analyze genomic, transcriptomic and other kinds of “omics” data, then generate insights that can help to improve health and advance scientific discovery.
In a blog post, AWS Principal Developer Advocate Channy Yun explained that healthcare and life sciences firms typically collect myriad kinds of biological data, with the aim being to leverage that information to improve patient care and advance scientific research. It’s a study that’s referred to by those in the know as “omics.”
“These organizations map an individual’s genetic predisposition to disease, identify new drug targets based on protein structure and function, profile tumors based on what genes are expressed in a specific cell, or investigate how gut bacteria can influence human health,” Yun explained.
The whole point of omics is that by collecting genetic data from thousands of individuals, comparing and analyzing it, researchers can generate new insights for predicting disease as well as the efficacy of various different drugs and treatments. Omics is therefore vital for advancing medical research and drug discovery.
The big problem with omics research is that, by necessity, it must be done at a vast scale. That can cause problems for healthcare firms and life sciences organizations that aren’t equipped to handle it.
“This type of data has so many complexities to it,” Taha Kass-Hout, AWS chief medical officer and vice president of technology health AI, told SiliconANGLE in an interview. “This explosion of data around the biology of the cell is outpacing the human ability to understand.”
Omics research involves juggling petabytes of data, and researchers therefore need a cost-effective way to store that information and a simple way to access it. “You need to scale compute across millions of biological samples while preserving accuracy and reliability,” Yun said. “You also need specialized tools to analyze genetic patterns across populations and train machine learning models to predict diseases.”
That’s where AWS believes it can make a difference with Amazon Omics, which is designed to support large-scale analysis and collaborative research on omics data. Not only does it provide an efficient way to store such information, but researchers can easily tap into other AWS services to analyze genome data for entire populations. Amazon Omics also automates the provisioning and scaling of bioinformatics workflows, enabling researchers to run analysis pipelines at scale.
The service, aimed at bioinformaticians, researchers and scientists, has three primary components. It offers omics-optimized object storage for storing and sharing data efficiently at lower cost; managed compute for bioinformatics workflows, making it simple to perform data analytics; and optimized data stores to enable population-scale variant analysis.
Amazon Omics is really all about enabling analysis, and to that end it’s compatible with services such as Amazon SageMaker, which can be used to train machine learning models for very specific purposes. For instance, users can train machine learning models to analyze omics data and predict if certain individuals might be predisposed to certain kinds of diseases. It’s also possible to combine an individual’s genome data with their medical history in Amazon HealthLake, Amazon said.
Amazon Omics is available now in AWS’s US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Europe (Frankfurt), Europe (Ireland) and Europe (London) Regions.
With reporting from Robert Hof
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