Applications
Introducing Public Life Science Knowledge Graphs
Turning pharmaceutical knowledge into explainable intelligence
- Finding trustworthy answers in life sciences has never been more critical - or more complex.
- From understanding drug–drug interactions to navigating FDA regulations, storage protocols, and biomedical literature, researchers face a growing challenge: data is abundant, but explainability is scarce.
- Despite advances in AI and digital databases, fragmentation, data silos, and black-box algorithms continue to limit reliability.
- That’s where Galaxia steps in.
A New Approach: Public Life Science Knowledge Graphs
- We’re introducing public, explainable knowledge graphs - beginning with the pharmaceutical domain.
- These graphs automatically transform raw biomedical and regulatory data into structured, connected, and traceable knowledge.
- Through Galaxia’s semantic hypergraph architecture, every entity, relationship, and source is captured with full provenance - creating a transparent reasoning space that AI systems can query, explain, and trust.
- The first graph - focusing on pharmaceutical data - is now being developed.
- It connects verified information on drug-drug interactions, active ingredients, side effects, dosage, and compliance guidelines into a unified explainable network.
- Researchers, clinicians, and regulators often spend days cross-checking fragmented sources.
- With Galaxia’s public knowledge graphs, they can ask natural-language questions and receive auditable, explainable answers, with every response linked back to its origin.
- Faster, more accurate drug-safety insights
- Traceable compliance verification
- Scalable, collaborative biomedical knowledge reuse
- And it’s not limited to life sciences - the same model applies to any domain where explainability and compliance matter.
- The first Public Life Science Knowledge Graphs will be accessible through a chat interface and API.
- Users will be able to:
- Query public graphs interactively
- Clone them for private use or domain-specific customization
- Expand them with own data for private use
- Integrate them into existing AI or decision-support systems
- This opens a path to explainable knowledge-as-a-service - where AI reasoning can be traced, trusted, and reused across industries.
Toward Federated, Explainable Intelligence
- This initiative is part of Galaxia’s broader vision: to build a federated, decentralized network of explainable knowledge graphs - what we call the Graph Swarm.
- Each domain graph - pharmaceuticals, materials science, regulatory frameworks - becomes a shard in a global, explainable knowledge architecture.
- Together, they form the foundation for Explainable Intelligence:
- AI that doesn’t just answer - it shows why.
- Galaxia - turning fragmented biomedical data into explainable, connected intelligence.
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