Polly Knowledge Graph (Polly KG) is a data-centric, Platform-as-a-Service offering that co-builds an AI-ready, evidence-backed graph by integrating curated public datasets with your proprietary multi-modal data for target identification and validation.
Unlike one-size-fits-all SaaS tools, Polly KG evolves with each customer’s biology and questions—prioritizing customization, interpretability, and traceable insights over generic, literature-only associations.
The co-build framework starts with Base-KG—a ready-from-day-one layer with natural-language querying—and extends it using accelerators to add custom nodes, relationships, and scoring frameworks across 30+ data modalities.
Base-KG brings immediate scale and semantic consistency (≈13.7M nodes; ≈20.4M relationships), enabling rich, multi-dimensional queries over genes, diseases, drugs, pathways, phenotypes, and more.
By emphasizing molecular and experimental evidence (with literature layered on top), Polly KG delivers deeper, auditable biology than literature-centric graphs.
A featured cross-species case study shows the approach end-to-end: harmonized non-model omics were integrated with human datasets, a custom scoring framework (phase, traceability, novelty/safety, relevance) was embedded, and within six months the KG surfaced five high-value targets—also highlighting PDE4 inhibitors as a repurposing opportunity.
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