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AWS jumps into precision medicine with genomics data cloud service

The new Amazon Omics service will support large-scale, cloud-based genomics data analytics for life science firms and healthcare providers.
By admin
Dec 12, 2022, 4:20 PM

Amazon Web Services (AWS) is aiming to accelerate the development of precision medicine with a new cloud-based genomics data service targeted to scientists from across the clinical and life sciences research communities.

The new Amazon Omics service will allow users to combine more traditional clinical data sets with an emerging category of “multiomic” data, including genomics, transcriptomics, epigenomics, and other types of information.

“Our life sciences customers want to accelerate drug discovery and development to create cures for patients,” said Tehsin Syed, general manager of health AI, and Taha Kass-Hout, VP and chief medical officer at AWS, in a company announcement. “Our healthcare customers want to transform care by identifying the best treatment or prevention for their patients.”

“A great example is how genomic data is being leveraged to profile individual patients’ tumors or circulating markers in blood to help clinicians make decisions at the point of care. This has generated a fourfold increase in personalized treatment options for cancer patients over the past decade.”

Related article: Clinical genomic sequencing evolving at life-saving speed

The progress could be even faster, however, if researchers had access to appropriately large volumes of fit-for-purpose data—and the analytics engines to extract actionable insights from these assets.

Currently, there are multiple barriers to doing so.

“The size, rapid accumulation, complexity, and heterogeneity of -omics data pose difficulties for our customers in tapping them with existing tools and systems,” acknowledged Syed and Kass-Hout.

“Customers must efficiently store, index, and secure petabytes of raw sequence data. Next, they must provision, manage, and operate the compute infrastructure required to process this data into analytics and interoperability-ready formats with reproducible and scalable pipelines. As part of their analysis workflow, customers often need to combine an individual’s genome data with other data such as their medical records or reference genome datasets, which requires significant manual data processing. This data processing consumes engineering resources and is error-prone and hard to implement for omics data at petabyte scale.”

Genomics data treasure hunt

AWS is among several entities trying to tackle that challenge by breaking down technical siloes, leveraging modern technologies like APIs, and reducing the costs involved. Other big names in the cloud services business, including Google, Microsoft and Oracle, have also stood up dedicated genomics infrastructure to support precision medicine.

Similar to their competitors, AWS’s take on the solution is to shift the burdens away from provider and life science organizations to a cloud partner wholly dedicated to stewarding and storing the data while automating the analytics workflow.

“Customers can bring their own bioinformatics workflows, and Amazon Omics manages the infrastructure to run it” AWS explained. “This further reduces undifferentiated heavy lifting, enables customers to operate in a secure environment with built-in access control, logging and audit trails, while still complying with HIPAA, GDPR, and other regulations.”

For many organizations, this may be a more efficient strategy with lower barriers to entry. But just like any other cloud services partnership, customers cannot completely offload all responsibility to their cloud vendor, especially when dealing with data as sensitive as genomics.  Ultimately, the originating organization must ensure that their partner adheres to the healthcare industry’s strict regulations around privacy, security, and patient consent for the specific use of their personal information.

Cloud privacy concerns

That last component will be tricky to navigate as precision medicine evolves and personal health data becomes more fluid and easily transferable. At the moment, patients are still relatively wary of donating their genetic information for research purposes, with close to 40 percent of participants in one survey expressing unwillingness to share their data with researchers under any circumstances.

The constant barrage of high-profile cyberattacks, combined with underlying mistrust of the healthcare and life sciences systems, may make it difficult for researchers to convince patients that their data is safe in the cloud, let alone that researchers should be granted the right to use the information for novel research efforts.

However, as high-profile names in the cloud ecosystem continue to devote resources to precision medicine development, patients may start to become more comfortable with the idea of contributing their data to help researchers better understand human biology.

Alongside the ongoing reductions in the cost of big data management and growing competency with deep-dive omics research, the industry is likely to continue the acceleration of precision medicine and unlock significant new insights into personalized care for a wide variety of diseases.

Jennifer Bresnick is a journalist and freelance content creator with a decade of experience in the health IT industry. Her work has focused on leveraging innovative technology tools to create value, improve health equity, and achieve the promises of the learning health system.

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