TetraScience, the Scientific Data Cloud company, announced today that DeepLife, a next-generation systems biology company, has joined the Tetra Partner Network to scale multi-omic workflows and accelerate AI-driven drug discovery through the Tetra Scientific Data Cloud(™)
“We applaud DeepLife’s powerful solutions for multi-omic research,” said Simon Meffan-Main, Ph.D., VP, Tetra Partner Network. “Multi-omic data integration and analysis considerably improves confidence in detecting cellular pathway responses, however the sheer volume and diversity of the datasets can easily limit throughput and the use of advanced analytics. Our partnership with DeepLife will allow customers to generate and integrate even more scientific data, thus saving time, accelerating insights, and capitalizing on the power of AI in drug discovery research.”
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Multi-omic research provides deep insights into disease initiation, development, diagnosis, and therapy. DeepLife combines omics data from instruments and public sources to model cell types and efficiently decipher underlying mechanisms of actions of various perturbations like drugs, gene editing, viruses, et al. The DeepLife Discovery Platform utilizes Deep Learning and software engineering to ingest millions of single cell data that can then be leveraged to create curated, harmonized, and annotated single cell data atlases across various tissues and disease indications or simply used to treat proprietary multi-omic datasets at scale. The platform also provides Virtual Cells, a next generation system biology digital capability that uses AI to simulate cell behavior in normal and diseased states; thus streamlining identification of novel targets or biomarkers and providing biologists with actionable insights for prioritization of their biological assets.
The Tetra Scientific Data Cloud(™) is designed to ingest and engineer scientific data, making it liquid and actionable. For the first time, customers can maximize the full value of their scientific data – from automating workflows to applying advanced analytics to utilizing AI/ML. When deployed to support multi-omic research, scientific outcomes can be accelerated and aggregated for AI-based discovery. This allows researchers to predict cell reactions to drugs thus identifying much more rapidly the most appropriate therapy.
“We are excited to partner with TetraScience, who shares our goal of helping researchers utilize all of their scientific data,” said Jonathan Baptista, Co-Founder and CEO, DeepLife. “Our partnership will allow scientists to combine TetraScience’s strengths in powerfully managing and harmonizing all types of scientific data with DeepLife’s analysis and modeling capabilities to improve the speed and efficiency of their discovery research activities.”