The challenge: safety data is fragmented and hard to use
Safety and toxicity continue to be major causes of R&D failure. Life sciences organizations must strengthen how they detect, understand, and mitigate toxicity risks early.
USE CASE
Unifying fragmented safety data is a key strategic approach to help avoid costly late-stage surprises.
Safety and toxicity continue to be major causes of R&D failure. Life sciences organizations must strengthen how they detect, understand, and mitigate toxicity risks early.
Safety scientists must work across heterogeneous sources and disconnected silos:
Public sources: DrugBank, PubChem/BioAssay, Tox21, FAERS, VigiBase
Licensed translational safety content: e.g., OFF-X
Internal data: preclinical tox studies, safety pharmacology, nonclinical reports, safety narratives
Different schemas, identifiers, and taxonomies make it slow to answer fundamental questions like:
Which targets have signals of organ toxicity? Has this pathway been linked to past AEs? What mechanisms connect this assay hit to downstream phenotypes?
The result: decisions wait on integration, and critical insights surface too late.
DISQOVER connects public, licensed, and internal safety data into a single, ontology-driven knowledge graph. This creates a trusted, harmonized foundation for toxicology, target triage, and mechanistic reasoning.
Links molecular targets, assays, pathways, phenotypes, AEs, literature, and real-world evidence
Normalizes identifiers across heterogeneous sources
Supports faceted exploration and graph-based mechanistic views
Exposes everything via APIs for downstream analytics and AI/ML models
Rapidly map, harmonize, and transform external + internal datasets
Reusable, modular pipelines with minimal coding
Transparency and versioning across the ingestion lifecycle
Extracts genes, diseases, phenotypes, AEs, mechanisms, PICOS elements
Adds new edges and entities from clinical trials, labels, reports, publications
Boosts mechanistic explainability and coverage
Export clean linked data for in-silico toxicology, SAR modeling, or off-target prediction
Integrates with enterprise KGs or ML workflows
Provides explainable evidence paths for governance reviews
Explore targets ↔ assays ↔ pathways ↔ phenotypes ↔ adverse events.
Spanning:
Tox21, DrugBank, PubChem, FAERS/VigiBase, OFF-X, Internal toxicology reports - All harmonized into one navigable environment.
Filter by target family, on/off-targets, species differences
Examine prior human AEs and organ toxicity indicators
Trace exposure windows and mechanistic pathways
Drill into full provenance for trust and auditability
Generate:
Ranked risk profiles (e.g., DILI, QT prolongation, neurotoxicity)
Mechanistic evidence paths (target → pathway → phenotype → AE)
Packaged insights for program governance, due diligence, or portfolio reviews
ONTOFORCE enables life science companies to unlock hidden insights from data.
With DISQOVER, built on knowledge graph technology, we support life sciences and pharmaceutical companies with innovative data management and visualization.
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