Azure Captures Viome’s 10-Quadrillion-Point RNA Dataset
When you’re operating at 10 quadrillion biomolecular data points, terms like scale and complexity almost lose their punch.
Right down the street from Microsoft, Bellevue-based Viome Life Sciences, tapped Azure to help manage one of the largest RNA datasets in existence, gathered from over one million biological samples collected across 106 countries.
The goal is take a 10-quadrillion-point RNA dataset, make it computationally tractable, and do it reliably enough to earn clinical trust.
At the heart of this infrastructure choice isn’t GPU-powered inference or flashy generative AI (isn't that kind of refreshing sometimes?). Viome just needs brute-force compute intensity to parsing through RNA sequences. This kind of bioinformatics workload lives and dies by storage performance, I/O throughput, and latency constraints, exactly the types of challenges that tend to bring traditional cloud architectures to their knees.
Azure’s Ultra Disk Storage, coupled tightly with memory-optimized virtual machines and HIPAA-compliant infrastructure, is the structural backbone here, making sure that Viome’s vast dataset stays computationally coherent.
Consider what "computationally coherent" means in practical terms because this is important here. Viome’s system captures and analyzes gene expression at a granular RNA level in real-time, continuously ingesting new sample streams. Each RNA sample is sequenced, indexed, and immediately integrated into a dynamic, continuously expanding dataset.
To turn RNA sequencing data into personalized, predictive health outcomes (think early cancer detection or tailored microbiome interventions) Viome relies on rapid-fire compute operations that test and validate millions of hypotheses simultaneously.
Infrastructure scale matters here.
Viome’s compute environment now routinely processes millions of RNA-sequence comparisons per hour, pinpointing biomarkers that can identify health conditions before symptoms appear. The payoff is already measurable: clinical outcomes showing reductions in IBS symptoms, improvements in depression and anxiety markers, and measurable decreases in diabetic biomarkers (HbA1c).
From a purely infrastructural viewpoint, the Viome-Microsoft work embodies a l trend emerging across health tech: cloud platforms adapting beyond generic compute offerings toward highly tailored architectures optimized for specific data-intensive workflows.
In choosing Azure, Viome not only gained the raw compute muscle needed for its RNA-centric bioinformatics tasks but also infrastructure aligned with the stringent regulatory requirements for handling healthcare data at scale.
