Many advances in modern medicine have happened with the help of cutting-edge technology. Cloud-based infrastructures are now adding to those advancements, specifically the area of cancer research.
Even with modern medicine, sometimes corners need to be cut in order to move research forward in the name of the “greater good.” However a New York City-based biotechnology and pharmaceutical research software company wanted to stop taking shortcuts and ensure greater accuracy.
The team at Schrödinger, which is led by President Ramy Farid, is working on a joint cancer research project conducted with Nimbus Discovery, which conducts computer-based drug discovery, according to a recent report by Ars Technica. The major difference is instead of using Schrödinger’s internal cluster, the company opted to build a 50,000-core supercomputer on the Amazon Elastic Compute Cloud.
The results? The supercomputer ran for three hours on the night of March 30, at a cost of $4,828.85 per hour, tapping into data centers across the world. Ultimately, the test provided critical information for future research that the company would have missed if it had utilized its in-house resources.
“Getting up to 51,132 cores required spinning up 6,742 Amazon EC2 instances running CentOS Linux,” the report said, “this virtual supercomputer spanned the globe, tapping data centers in four continents and every available Amazon region, from Tokyo, Singapore, and Sao Paolo, to Ireland, Virginia, Oregon and California.”
In essence, the virtual supercomputer allowed Schrödinger to test 21 million synthetic compounds developed by chemistry labs that can potentially be used in drugs. Using this super-speedy process – which could normally take as long as one year – the company was able to identify false negatives produced by the internal cluster, which were correctly identified as potential drug targets by the Amazon cluster, the report said.
There are other recent examples of virtualized environments helping propel scientific research forward.
Last month during the White House Big Data Summit, Amazon and the National Institutes of Health announced that they will make the full 1000 Genomes Project available as a free public data set on the company’s Simple Storage Service (S3) and Elastic Block Store (EBS) services, allowing researchers to search the data for free from Amazon’s Elastic Compute Cloud (EC2) and Elastic MapReduce (EMR) platforms, eWeek reported.
The cloud database will allow medical researchers to predict the risks of illnesses, such as diabetes, heart disease, sickle cell anemia and breast cancer.
Edited by
Jennifer Russell
