Target and mechanism safety
Investigate the potential safety implications of a molecular target or mechanism of action before committing further resources to a development program.
Metisox Models
Predictive models for drug safety, powered by proprietary knowledge
Analyze your data. Predict potential risks. Integrate into your workflow.
Metisox develops predictive models for toxicology and mechanistic interpretation, built on a proprietary knowledge graph curated by experts over decades. Our technology connects chemical structures, molecular targets, genes, proteins, biological pathways, diseases and toxicological outcomes to help identify potential safety risks and understand the mechanisms behind them, at any stage of drug development.
Your data stays with you
Work within your own infrastructure and security environment.
Easy integration
Connect to your existing AI tools and internal systems.
Powerful predictive models
Built on a proprietary knowledge graph curated by experts over decades.
More than data retrieval. Mechanistic insight.
AI can summarize scientific literature, but finding the right evidence is only part of the problem. Reliable predictions also depend on what information is available, how biological relationships are represented and whether the evidence is relevant to the question.
Metisox adds a specialized, persistent knowledge layer to this process. Our models work with structured relationships curated from scientific literature and proprietary data, rather than relying on a language model to reconstruct every relationship from raw text.
The result is a foundation for more consistent, traceable and scientifically informed analysis.
Capabilities
Assess safety risks throughout drug development
Metisox models can support scientific investigations from early target selection through preclinical development, clinical development and post-approval assessment.
Compound and off-target assessment
Explore known and potential safety liabilities associated with a compound, its molecular targets, related compounds and biological interactions.
Toxicity and pathway prediction
Identify candidate toxicological endpoints and pathways that may help explain an observed effect or prioritize further investigation.
Omics interpretation
Connect dysregulated genes and other molecular findings to toxicological processes, biological pathways and pathology.
Cross-species interpretation
Investigate relevant molecular and biological differences between experimental species and humans when interpreting nonclinical findings.
New indications and patient stratification
Explore connections between mechanisms, diseases, phenotypes and biomarkers to support the investigation of new therapeutic opportunities and patient subgroups.
Metisox models help teams identify relevant relationships, generate hypotheses and focus follow-up work. The appropriate application and interpretation depend on the specific model, data and scientific question.
FDA · March 18, 2026
“NAMs can identify toxicities, demonstrate how the investigational drug works, improve predictivity of nonclinical studies, and enhance the safety of future clinical trials.”
The technology behind the predictions
A proprietary knowledge graph built for toxicology
At the core of Metisox is a specialized knowledge graph that connects molecular biology with toxicological effects and pathology.
Unlike a conventional collection of documents, the graph represents scientific knowledge as explicit relationships between entities. Each relationship can retain its type, direction, confidence and supporting publications, making it possible to investigate not only what is connected, but also why.
Chemical structures and compounds
Drugs, bioactive molecules, metabolites and their reported molecular targets.
Genes and proteins
Human genes and proteins, molecular interactions, isoforms and relationships across species.
Omics and experimental data
Molecular changes and findings from different experimental systems, tissues and species.
Biological pathways
Signaling pathways, metabolic processes and connected molecular mechanisms.
Toxicological endpoints
Organ toxicities, adverse effects and other safety-related outcomes associated with compounds, targets and biological processes.
Pathology and phenotypes
Histopathological findings, disease-related phenotypes and observed biological effects.
How it works
Trusted proprietary scientific data in your AI workflow.
Metisox is expanding access to its proprietary toxicology knowledge base into the AI environments experts already use. Through the MCP Connector, teams can integrate curated, structured scientific evidence into their existing workflows, supporting evidence-based decisions across drug discovery, development and safety assessment.
Connect your AI workflow to Metisox scientific intelligence.- MCP Connector
- Proprietary Knowledge Base
- Decision-ready insights
- Liver toxicity evidence
- Pathway analysis
- Chemical structure context
- Relevant literature
Evidence-based answers
Get reliable, context-rich information from a trusted scientific source.
Traceable scientific sources
Explore the evidence behind each finding and follow relevant relationships across the knowledge graph.
Toxicology and safety insights
Assess potential risks and safety liabilities with specialized toxicology data and endpoints.
Better-informed R&D decisions
Reduce uncertainty and accelerate your path from signal to decision.
What can you explore?
Ask better safety questions.
Use Metisox scientific knowledge in your existing AI workflow to explore toxicology questions, connect evidence and identify what is still unknown.
Target safety
“Compare these targets by potential safety risk.”
Compare safety profiles and identify evidence gaps.
Toxicity mechanisms
“What could explain this toxicity finding?”
Connect observed effects with potential mechanisms and relevant evidence.
Evidence assessment
“What do we know about this asset’s safety?”
Bring together relevant findings, references and unanswered questions.
For decisions with regulatory implications, Metisox experts can provide additional review.
Request expert reviewDesigned to work with your AI infrastructure
Add toxicology-specific knowledge to the AI tools you already use
Your organization may already have language models, internal AI assistants and established data pipelines. Metisox is designed to complement these systems, not replace them.
Through an MCP connector and other integration options, Metisox knowledge and model capabilities can be made accessible to compatible AI environments and computational workflows.
Instead of asking a general-purpose model to reconstruct specialized biological relationships from raw literature for every query, an integrated workflow can retrieve relevant, pre-structured relationships from the Metisox knowledge graph.
This adds a persistent, domain-specific evidence layer to the reasoning capabilities of your existing AI systems.
Analyze your data. Predict potential risks.
Integrate Metisox predictive models into your workflow.
Discuss an integration