Amazon Web Services has been expanding its reach into genomics and continues to grow in areas like molecular diagnostics through new initiatives.
As might be expected of one of the world’s three largest commercial cloud platforms, AWS counts some well-known names in the genomics and bioinformatics world among its customers.
“Over the past 15 years, AWS has helped remove the undifferentiated heavy lifting so that customers are able to figure out what’s the differentiating value for them,” Wilson To, AWS global head of healthcare, life sciences, and genomics, said this week during AWS’s Healthcare & Life Sciences Virtual Symposium. “Genomics” is a recent addition to his title, indicating the field’s increased importance to the company.
Pat Combs, AWS worldwide technical leader for healthcare and life sciences, said that the firm’s history in genomics goes back to the launch of its cloud platform in 2006. He described himself as the “bridge” between customer-facing technical staff and AWS’ internal engineering and service teams in life sciences.
Combs said that this “heavy lifting” in genomics includes mundane, time-consuming computing tasks such as genome assembly, read alignment, and analysis of sequencing runs. “Wherever we see it, wherever we encounter it, we will build out services and solutions necessary to help relieve that from our customers so that they can focus on the very specific and really exciting work that they do,” he said.
For example, he said, Munich Leukemia Laboratory in Germany has reduced the time to process a genome sequence from 20 hours to 3 hours.
The AWS cloud has long been attractive to genomics users because the on-demand scalability is a lower-cost alternative to running high-performance computing centers. Also, the sharing and collaboration that cloud computing facilitates grew in importance last year as the COVID-19 pandemic forced so many people to work from home.
“Most of the computational work in genomics is pretty much a massively parallel task,” Combs said, “That is a central advantage of any cloud platform.”
Combs also said that genomics workflows are becoming more sophisticated as research advances.
In March, diagnostics firm Konica Minolta Precision Medicine also entered into a five-year deal with AWS for the global buildout of its integrated, multiomic diagnostic data platform. As part of the partnership, Amazon made an undisclosed investment in KMPM.
A month later, Amazon announced the next phase of its AWS Diagnostic Development Initiative, in which it plans to distribute $12 million this year to fund projects for COVID testing, as well as for other infectious disease diagnostics. The company first launched the initiative in March 2020 as a way to accelerate research, innovation, and development of diagnostics for the detection of the coronavirus.
While the initiative traces its roots to the early days of the pandemic, Combs sees potential far beyond COVID-19. “It really jumpstarted a lot of interesting diagnostic use cases on AWS that are multiomic,” including public health surveillance, early detection of diseases, and rapid test development, he said. “There’s a lot of … expanded efforts into virology and the use of genomics in virology research.”
Combs said that the pandemic has changed how customers in genomics approach the cloud. “It’s not just capability but recognition of the ease of acquiring high-powered resources,” as well as cost savings over investing in high-performance computing infrastructure, he said.
The cloud, of course, supported all the remote collaboration on “virtual desktops” necessitated by office and lab closures, but that is true across all industries that AWS serves, Combs noted.
From Amazon’s perspective, COVID-19 has also triggered decentralization of laboratories, which Combs said he expects to remain after the pandemic is over. “A lot of larger labs that had been centralized in a single location really diversified a lot of their work across smaller locations that were able to remain open and do direct work” with proper social distancing, he said. “That meant that a lot of data consolidation and analysis took place on AWS as a result.”
Another growth area is related to the Amazon Registry of Open Data, a collection of public-domain datasets across multiple industries that AWS has made available on its cloud based on requests from customers. This collection includes the Genome Aggregation Database (GnomAD), the Cancer Genome Atlas, and the Sequence Read Archive. Combs said that the number of genomics-focused data in the registry has grown tenfold in the last year.
“I think what we’re seeing now is the combination of two other things, the dramatic increase in dataset size … and the need for those to be leveraged in a lot of advanced research programs,” Combs said.
He said he expects the future to call for “greater and greater focus on aggregating larger and larger datasets and cross-utilization between research applications.”
Combs also mentioned the liquid biopsy cancer test of Grail, which Amazon has invested in. Grail is expanding to about 50 cancers through its Galleri screening test that is set to launch this year.
Going forward, users in genomics and molecular diagnostics can expect additional enhancements from AWS that are tailored to their work. “I think what you’ll begin to see are [software] tools that make AWS easier to use, more accessible in this space for researchers and clinicians alike,” Combs said, though he noted that some of these tools are several years away.
This story first appeared in our sister publication, Genomeweb.