Tooluniverse Adverse Outcome Pathway

Adverse Outcome Pathway & Regulatory Risk Assessment

Distinct from drug safety (see tooluniverse-toxicology): this skill targets environmental and industrial chemicals where the focus is AOP stressor mapping, GHS classification, LD50 hazard quantification, and IARC carcinogen status — not FAERS signals or FDA drug labels.

When to Use

Apply when researcher asks about:

• "What AOPs are associated with [pesticide/solvent/industrial chemical]?"
• "What is the GHS hazard classification for [compound]?"
• "What is the LD50 for [compound]?"
• "Is [compound] a carcinogen (IARC classification)?"
• "Which genes does [chemical] interact with (CTD)?"
• "Regulatory risk assessment for [environmental chemical]"
• "What diseases are associated with [chemical] exposure?"

Do NOT use for FDA-approved drugs with FAERS data — use tooluniverse-toxicology instead.

Key Tools

Workflow

Phase 1: Compound Identity Resolution

Resolve chemical name to PubChem CID before all PubChemTox calls.

PubChem_get_CID_by_compound_name(name="benzo[a]pyrene")
-> cid: 9153 (use for all PubChemTox calls)

Note: CTD tools accept the chemical name directly (input_terms param) — no CID needed.

Phase 2: AOP Discovery

Find relevant AOPs by searching organ targets and mechanism keywords.

AOPWiki_list_aops(keyword="lung")          # organ-level
AOPWiki_list_aops(keyword="DNA damage")    # mechanism-level
AOPWiki_list_aops(keyword="AhR")           # receptor-level

Select 2-4 candidate AOPs from results, then retrieve full details:

AOPWiki_get_aop(aop_id=58)  # returns MIE, key events, stressors, biological plausibility

Key fields in AOPWiki_get_aop response:

• stressors: list of chemicals that trigger this AOP (check if query compound is listed)
• molecular_initiating_event: the first molecular perturbation
• key_events: ordered chain of biological events
• adverse_outcome: apical regulatory endpoint

Phase 3: Hazard Quantification (PubChemTox)

Run all four hazard queries in parallel using the resolved CID:

PubChemTox_get_ghs_classification(cid=9153)        # GHS category + pictogram
PubChemTox_get_carcinogen_classification(cid=9153)  # IARC Group 1/2A/2B/3
PubChemTox_get_toxicity_values(cid=9153)            # LD50 by route/species
PubChemTox_get_acute_effects(cid=9153)              # signs/symptoms

Note: PubChemTox_get_target_organs sometimes returns no data — treat as optional.

Phase 4: Toxicogenomics (CTD)

Map chemical to gene targets and disease associations:

CTD_get_chemical_gene_interactions(input_terms="benzo[a]pyrene")
CTD_get_chemical_diseases(input_terms="benzo[a]pyrene")

Cross-reference CTD gene targets with AOP key event genes from Phase 2.

Tool Parameter Reference

Common Patterns

# Pattern: Confirm compound is a stressor in a specific AOP
aop = AOPWiki_get_aop(aop_id=58)
stressors = [s["name"] for s in aop["data"]["stressors"]]
# Check if query chemical appears in stressors list

# Pattern: Extract curated CTD disease associations only
diseases = CTD_get_chemical_diseases(input_terms="rotenone")
curated = [d for d in diseases["data"] if d.get("DirectEvidence")]

# Pattern: GHS carcinogen check
carcinogen = PubChemTox_get_carcinogen_classification(cid=9153)
iarc = [c for c in carcinogen["data"]["classifications"] if "IARC" in c.get("source", "")]

Reasoning Framework for Result Interpretation

Evidence Grading

Interpretation Guidance

• AOP weight-of-evidence assessment: OECD-endorsed AOPs have undergone expert review and represent the highest confidence mechanistic pathways. AOPs "under development" in AOPWiki may have incomplete key event relationships. Evaluate each AOP by: (1) biological plausibility of key event relationships, (2) empirical support (dose-response concordance), (3) essentiality of key events (blocking KE prevents AO).
• Key event relationship (KER) strength: Strong KERs have dose-response and temporal concordance between upstream and downstream key events. Moderate KERs have correlative evidence. Weak KERs are based on plausibility alone. The weakest KER in the chain determines the overall AOP confidence for that pathway.
• Stressor potency interpretation: LD50 values indicate acute toxicity (lower = more toxic). GHS categories: Cat 1 (LD50 <= 5 mg/kg, fatal), Cat 2 (5-50, fatal), Cat 3 (50-300, toxic), Cat 4 (300-2000, harmful), Cat 5 (2000-5000, may be harmful). IARC Group 1 = confirmed carcinogen, 2A = probable, 2B = possible, 3 = not classifiable. Always report route of exposure and species for LD50 values.
• CTD integration: CTD "direct evidence" (curated marker/mechanism) is stronger than "inferred" associations. When CTD gene targets overlap with AOP key event genes, this supports the mechanistic link between the compound and the adverse outcome.
• Regulatory context: For risk assessment, combine hazard identification (IARC, GHS) with exposure assessment. A potent carcinogen at negligible exposure may pose lower risk than a moderate toxicant at high exposure.

Synthesis Questions

1. Is the query compound explicitly listed as a stressor in the identified AOP, or is the link inferred from shared molecular targets (CTD gene overlap)?
2. Do the key event relationships in the AOP chain have sufficient empirical support (dose-response concordance, temporal sequence), or are there weak links that reduce confidence?
3. Are the hazard data (LD50, GHS, IARC) consistent across sources, and do they support the severity implied by the AOP adverse outcome?
4. Does the CTD gene-disease evidence corroborate the AOP's predicted adverse outcome, or are there discrepancies suggesting alternative pathways?
5. For regulatory decision-making, is the combined weight of evidence (AOP mechanism + hazard quantification + exposure context) sufficient to support a risk classification?

Fallback Chains