VAST recently unveiled a game-changing development: an AI agent that connects, understands, and reasons across all enterprise data — unifying everything from product roadmaps and go-to-market plans to financials and sales activity. This enterprise-level reasoning framework, introduced by VAST’s VP of Architecture Sagi Grimberg, redefines how organizations tap into their full knowledge base.
This same underlying platform — powered by VAST InsightEngine — is now enabling intelligent agents in one of the most critical domains imaginable: pediatric precision medicine. These agents don’t just retrieve and summarize - they reason over variant data, clinical trial registries, therapy evidence, and discovery literature in real time. Built on VAST’s scalable DASE architecture, they bring structure and speed to lifesaving decisions.
A Race Against Time
Pediatric cancer isn’t just a disease - it’s an emergency. Behind every diagnosis is a child whose life can change in a matter of days. For high-risk cases like neuroblastoma, rare genomic drivers demand a response that is not only precise but immediate.
Traditional genomic workflows are too slow. It’s no longer enough to identify mutations — we must interpret them in real time, derive personalized therapies, and explore novel molecules from a single molecular snapshot.
This is what VAST is built to solve. With agentic automation, unified data infrastructure, and intelligent orchestration, VAST transforms the discovery lifecycle from fragmented pipelines into a continuous process of precision medicine.
Edge-Accelerated Secondary Genomic Analysis
The process begins with sequencing — often conducted at the edge using portable, long-read technology. These platforms generate comprehensive views of structural variants, gene fusions, and epigenetic markers that short-read workflows miss.
Raw signal files are transformed into FASTQ format and processed using containerized tools like BWA-MEM, SAMtools, GATK, and BCFtools, producing high-quality VCF files locally. On-site compute or GPU-accelerated workstations drive this workflow. With VAST DataEngine, orchestration is seamless — automating quality control, pipeline execution, and version tracking — accelerating insights even in constrained environments.
Unifying Genomic Intelligence Across the Ecosystem
Once created, the VCF files — often between 100 and 250 MB — are transferred through LEO satellite networks, eliminating reliance on conventional infrastructure. Within the VAST DataStore these files are ingested into a unified namespace. VAST DataSpace ensures federated access and synchronization across clinical and research collaborators.
At this stage:
VAST DataBase parses, indexes, and queries metadata, functional annotations, and longitudinal variant patterns.
VAST DataEngine enriches each object using ClinVar, COSMIC, and internal overlays, structural interpretation logic, and therapy relevance algorithms.
This transforms a static file into a live genomic object, enabling real-time decision support.
From Genomic Object to Therapeutic Insight
At the heart of the agentic architecture is VAST InsightEngine — a system of real-time reasoning powered by Retrieval-Augmented Generation (RAG).
As new VCFs are ingested:
VAST InsightEngine embeds the data into vector space for semantic search.
It retrieves context across structured and unstructured domains, including clinical trials, research papers, compound databases, and therapy registries.
It synthesizes treatment pathways, ranks therapy options, and generates clinician-ready reports.
This isn’t automation for automation’s sake. It’s the transformation of a week-long, multi-disciplinary effort into an on-demand decision-making engine — with traceable outputs, explainable logic, and source attribution.
When No Match Exists: Discovery Begins
In cases where existing therapies don’t align, VAST InsightEngine initiates de novo discovery:
It maps structural and functional mutations to affected biological pathways.
It explores ligand and synthetic compound libraries.
It proposes molecular structures using generative AI workflows integrated through inference microservices.
This enables:
Drug repurposing for rare pediatric variants.
Real-time screening for target-compound binding compatibility.
Iterative in silico molecular design based on biological need.
The VAST DataBase, with vector search and compute proximity, supports the exploration and validation of new compounds across petabytes of multimodal data.
The Agentic Workflow: Clarity Through Architecture
This is not an opaque system. Each step in the agentic process is clearly defined and fully observable:
Sequencing at the Edge: Raw reads processed into VCFs on-site.
Automated Ingestion: Event triggers pipeline execution via the DataEngine and the DataSpace.
Parsing and Annotation: Public and private overlays are applied within the DataBase.
Vector Embedding and Search: VAST InsightEngine transforms objects for rapid, intelligent retrieval.
Inference and Reasoning: Inference microservices and InsightEngine collaborate to produce therapy insights.
Actionable Output: Results presented in clinician-ready format, with transparency and auditability.
This closed-loop system ensures that every recommendation is timely, trusted, and backed by evidence.
The Path Forward
The VAST Data Platform wasn’t imagined in isolation. It was built from the ground up to solve previously unsolvable problems and to address life’s most critical issues, like real-world pediatric genomics. And it’s designed to expand. Beyond neuroblastoma, this approach can support any rare or complex disease where data-driven therapies are urgently needed.
From Genomes to Action
Precision medicine was once an aspiration. Today, it’s an intelligent, end-to-end system.
With VAST, the question isn’t whether real-time, AI-guided genomics is possible. It’s how quickly we can make it real - for every patient, everywhere.
How do you see real-time AI transforming pediatric medicine? Join the conversation on Cosmos and share your perspective on the future of precision genomics.
