Target safety with DISQOVER

USE CASE

Accelerate target safety assessment with DISQOVER

Unifying fragmented safety data is a key strategic approach to help avoid costly late-stage surprises.

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.

Unifying fragmented safety data is a key strategic approach to help avoid costly late-stage surprises.

 
 

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.

How DISQOVER helps

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.

A unified safety & toxicology intelligence layer

INLINE-network-ICON-55px-Java@2x

Ontology-based knowledge graph

  • 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

home-dashboard ONTOFORCE DISQOVER

Visual data ingestion

  • Rapidly map, harmonize, and transform external + internal datasets

  • Reusable, modular pipelines with minimal coding

  • Transparency and versioning across the ingestion lifecycle

INLINE-idea-ICON-55px-Java@2x

NLP enrichment

  • Extracts genes, diseases, phenotypes, AEs, mechanisms, PICOS elements

  • Adds new edges and entities from clinical trials, labels, reports, publications

  • Boosts mechanistic explainability and coverage

Open architecture ONTOFORCE DISQOVER

AI/ML-ready architecture

  • 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

What DISQOVER enables for safety & toxicology

1. One pane of glass for toxicology intelligence

Explore targets assays pathways phenotypes adverse events.

Spanning:
Tox21, DrugBank, PubChem, FAERS/VigiBase, OFF-X, Internal toxicology reports - All harmonized into one navigable environment.

2. Faster, evidence-rich target safety triage

  • 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

3. Actionable outputs for decision making

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



Get in touch with our team to schedule a personalized demo.

Book a meeting