Chemical safety and toxicology assessment integrating ADMET-AI predictions, CTD toxicogenomics, PubChemTox experimental data, GHS/IARC hazard classification, and exposure-context analysis. Use for chemical hazard identification, occupational/consumer-product toxicity, dose-response evaluation, and a

Chemical Safety & Toxicology Assessment Toxicity assessment : identify the chemical, check known hazards (GHS, IARC), then look for ADMET predictions. Dose makes the poison — always consider exposure level, as a compound that is toxic at high doses may be safe at relevant exposures. Distinguish between acute toxicity (LD50, GHS category) and chronic hazards (carcinogenicity, endocrine disruption) — they require different risk management approaches. Computational predictions (ADMETAI) are T3 evidence and must be anchored by experimental data from PubChemTox or FDA labels wherever available. When evidence conflicts between prediction and experiment, always defer to the experimental finding. LOOK UP DON'T GUESS : never assume GHS categories, IARC classification, or CTD disease links — always call PubChemTox and CTD tools to retrieve current classifications before reporting. Comprehensive chemical safety analysis integrating predictive AI models, curated toxicogenomics databases, regulatory safety data, and chemical biological interaction networks. When to Use This Skill Triggers : "Is this chemical toxic?" / "Assess the safety profile of [drug/chemical]" "What are the ADMET properties of [SMILES]?" "What genes does [chemical] interact with?" / "What diseases are linked to [chemical] exposure?" "Drug safety assessment" / "Environmental health risk" / "Chemical hazard profiling" Use Cases : 1. Predictive Toxicology : AI predicted endpoints (AMES, DILI, LD50, carcinogenicity, hERG) via SMILES 2. ADMET Profiling : Absorption, distribution, metabolism, excretion, toxicity 3. Toxicogenomics : Chemical gene disease mapping from CTD 4. Regulatory Safety : FDA label warnings, contraindications, adverse reactions 5. Drug Safety : DrugBank safety + FDA labels combined 6. Chemical Protein Interactions : STITCH based interaction networks 7. Environmental Toxicology : Chemical disease associations for contaminants COMPUTE, DON'T DESCRIBE When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it. KEY PRINCIPLES 1. Report first approach Create report file FIRST, then populate progressively 2. Tool parameter verification Verify params via get tool info before calling unfamiliar tools 3. Evidence grading Grade all safety claims by evidence strength (T1 T4) 4. Citation requirements Every toxicity finding must have inline source attribution 5. Mandatory completeness All sections must exist with data or explicit "No data" notes 6. Disambiguation first Resolve compound identity (name SMILES, CID, ChEMBL ID) before analysis 7. Negative results documented "No toxicity signals found" is data; empty sections are failures 8. Conservative risk assessment When evidence is ambiguous, flag as "requires further investigation" 9. English first queries Always use English chemical/drug names in tool calls Evidence Grading System (MANDATORY) Tier Symbol Criteria Examples T1 [T1] Direct human evidence, regulatory finding FDA boxed warning, clinical trial toxicity T2 [T2] Animal studies, validated in vitro Nonclinical toxicology, AMES positive, animal LD50 T3 [T3] Computational prediction, association data ADMET AI prediction, CTD association T4 [T4] Database annotation, text mined Literature mention, unvalidated database entry Evidence grades MUST appear in: Executive Summary, Toxicity Predictions, Regulatory Safety, Chemical Gene Interactions, Risk Assessment. Core Strategy: 8 Research Phases See phase procedures detailed.md for complete tool parameters, decision logic, output templates, and fallback strategies for each phase. Tool Summary by Phase Phase 0: Compound Disambiguation PubChem get CID by compound name ( name : str) PubChem get compound properties by CID ( cid : int) ChEMBL get molecule (if ChEMBL ID available) Phase 1: Predictive Toxicology Dependency : ADMET AI tools require pip install tooluniverse[ml] . If unavailable, skip to Phase 3 and use CTD + PubChemTox as alternatives. ADMETAI predict toxicity ( smiles : list[str]) AMES, DILI, ClinTox, LD50, hERG, etc. ADMETAI predict stress response ( smiles : list[str]) ADMETAI predict nuclear receptor activity ( smiles : list[str]) Phase 2: ADMET Properties ADMETAI predict BBB penetrance / bioavailability / clearance distribution / CYP interactions / physicochemical properties / solubility lipophilicity hydration (all take smiles : list[str]) Phase 3: Toxicogenomics CTD get chemical gene interactions ( input terms : str) — chemical name, returns gene interactions across species CTD get chemical diseases ( input terms : str) — chemical disease associations with evidence type Phase 3.5: PubChem Toxicity Data PubChemTox get toxicity values ( cid : int) — LD50, LC50, NOAEL reference values PubChemTox get ghs classification ( cid : int) — GHS hazard classification and pictograms PubChemTox get carcinogen classification ( cid : int) — NTP/IARC carcinogenicity assessments PubChemTox get acute effects ( cid : int) — acute toxicity by route/species PubChemTox get toxicity summary ( cid : int) — integrated toxicity overview Phase 3.6: Adverse Outcome Pathways AOPWiki list aops ( keyword : str) — search for relevant AOPs by chemical/mechanism AOPWiki get aop ( aop id : int) — full AOP detail: MIE, key events, adverse outcome Phase 3.7: Environmental Exposure Context (US facilities) Use for exposure/environmental justice screening — locate regulated facilities near a community before assessing population level exposure. EPA search tri facilities ( state , city , limit ) — Toxics Release Inventory facilities reporting toxic chemical releases EPA search frs facilities ( state , city , limit ) — Facility Registry Service (all EPA regulated facilities) for broader siting/permitting context Phase 4: Regulatory Safety (for pharmaceuticals only) Environmental chemicals : Skip Phases 4 5 (no FDA labels/DrugBank). Use CTD + PubChemTox + AOPWiki instead. FDA get boxed warning info by drug name / contraindications / adverse reactions / warnings (all take drug name : str) Phase 5: Drug Safety (for pharmaceuticals only) drugbank get safety by drug name or drugbank id ( query , case sensitive , exact match , limit all 4 required) Phase 6: Chemical Protein Interactions STITCH get chemical protein interactions ( identifiers : list[str], species : int) Fallback (if STITCH fails for industrial chemicals): STRING get interaction partners for key target genes (e.g., ESR1 for endocrine disruptors) DGIdb get drug gene interactions ( genes : list[str]) — for target druggability context Phase 7: Structural Alerts ChEMBL search compound structural alerts ( molecule chembl id : str) Risk Classification Matrix Risk Level Criteria CRITICAL FDA boxed warning OR multiple [T1] toxicity findings OR active DILI + active hERG HIGH FDA warnings OR [T2] animal toxicity OR multiple active ADMET endpoints MEDIUM Some [T3] predictions positive OR CTD disease associations OR structural alerts LOW All ADMET endpoints negative AND no FDA/DrugBank flags AND no CTD concerns INSUFFICIENT DATA Fewer than 3 phases returned data Report Structure See report templates.md for full section templates with example tables. Mandatory Completeness Checklist [ ] Phase 0: Compound disambiguated (SMILES + CID minimum) [ ] Phase 1: At least 5 toxicity endpoints or "prediction unavailable" [ ] Phase 2: ADMET A/D/M/E sections or "not available" [ ] Phase 3: CTD queried; results or "no data in CTD" [ ] Phase 4: FDA labels queried; results or "not FDA approved" [ ] Phase 5: DrugBank queried; results or "not found" [ ] Phase 6: STITCH queried; results or "no data available" [ ] Phase 7: Structural alerts checked or "ChEMBL ID not available" [ ] Synthesis: Risk classification with evidence summary [ ] Evidence Grading: All findings have [T1] [T4] annotations [ ] Data Gaps: Explicitly listed Common Use Patterns 1. Novel Compound : SMILES Phase 0 (resolve) Phase 1 (toxicity) Phase 2 (ADMET) Phase 7 (structural alerts) Synthesis 2. Approved Drug Review : Drug name All phases (0 7) Complete safety dossier 3. Environmental Chemical : Chemical name Phase 0 Phase 1 2 Phase 3 (CTD, key) Phase 6 (STITCH) Synthesis 4. Batch Screening : Multiple SMILES Phase 0 Phase 1 2 (batch) Comparative table Synthesis 5. Toxicogenomic Deep Dive : Chemical + gene/disease interest Phase 0 Phase 3 (expanded CTD) Literature Synthesis Limitations ADMET AI : Computational [T3]; should not replace experimental testing CTD : May lag behind latest literature by 6 12 months FDA : Only covers FDA approved drugs; not applicable to environmental chemicals DrugBank : Primarily drugs; limited industrial chemical coverage STITCH : Lower score thresholds increase false positives ChEMBL : Structural alerts require ChEMBL ID; not all compounds have one Novel compounds : May only have ADMET AI predictions (no database evidence) SMILES validity : Invalid SMILES cause ADMET AI failures Reference Files phase procedures detailed.md Complete tool parameters, decision logic, output templates, fallback strategies per phase evidence grading.md Evidence grading details and examples report templates.md Full report section templates with example tables phase details.md Additional phase context test skill.py Test suite Summary Total tools integrated : 25+ tools across 6 databases (ADMET AI, CTD, FDA, DrugBank, STITCH, ChEMBL) Best for : Drug safety assessment, chemical hazard profiling, environmental toxicology, ADMET characterization, toxicogenomic analysis Outputs : Structured markdown report with risk classification (Critical/High/Medium/Low), evidence grading [T1 T4], and actionable recommendations

tooluniverse-chemical-safety