TetraScience Builds on AWS to Make Life Sciences R&D Data Accessible and Actionable for Scientists

Siloed and fragmented research and development (R&D) data creates a bottleneck for researchers and data scientists who spend more time wrangling and unifying data rather than analyzing it.

TetraScience is an R&D data cloud platform that acts as a vendor-neutral third-party focused on connecting data sources to data targets to provide greater access and usability. Scientists can spend more than 1 million hours and $125 million per year on data wrangling instead of actual analysis. TetraScience cultivates strong relationships with an ever-growing network of customers, such as lab instrument and software companies, integrating with their tools to funnel data into its cloud-based data lake via data connectors. Once data is in the data lake, TetraScience centralizes and harmonizes it before pushing it through data pipelines to a variety of on-premises and cloud-based targets. The result is automated, centralized, and harmonized R&D data, prepared for advanced analytics and data science.

“All in” on Amazon Web Services (AWS), TetraScience utilizes AWS solutions across its platform, including in its data standardization process. “We really try to take full advantage of AWS offerings, and we’ve found it to be a tremendous accelerant in delivering our product,” says Punya Biswal, chief technology officer at TetraScience. The company’s data lake is powered by Amazon Simple Storage Service (Amazon S3) and provides data insights using tools such as Amazon Elasticsearch and Amazon Athena. “By leveraging these service offerings, we’re able to take advantage of a lot of flexibility, we’re able to minimize cost, and we’re able to get to market as fast as possible,” says Biswal.