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name: tooluniverse-drug-research description: "Comprehensive drug profiling — mechanism, primary/secondary targets, drug interactions, clinical-trial status, adverse events (FAERS), pharmacogenomics, and approval history. Use for full drug investigation reports, 'tell me about drug X' queries, and assembling drug profiles for clinicians, researchers, or regulatory work."

Drug Research Strategy

Comprehensive drug investigation using 50+ ToolUniverse tools across chemical databases, clinical trials, adverse events, pharmacogenomics, and literature.

KEY PRINCIPLES:

1. Report-first approach - Create report file FIRST, then populate progressively
2. Compound disambiguation FIRST - Resolve identifiers before research
3. Citation requirements - Every fact must have inline source attribution
4. Evidence grading - Grade claims by evidence strength (T1-T4)
5. Mandatory completeness - All sections must exist, even if "data unavailable"
6. English-first queries - Always use English drug/compound names in tool calls, even if the user writes in another language. Only try original-language terms as a fallback. Respond in the user's language

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LOOK UP, DON'T GUESS

When asked about a drug, query ChEMBL/PubChem/DailyMed FIRST. Don't guess at mechanism, targets, or side effects — look them up. When you're not sure about a fact, your first instinct should be to SEARCH for it using tools, not to reason harder from memory.

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Drug Mechanism Reasoning

When investigating a drug's mechanism of action, trace the full causal chain:

1. Target engagement - Which protein(s) does the drug bind, and with what affinity/selectivity?
2. Molecular effect - Does binding inhibit, activate, or modulate the target's function?
3. Pathway consequence - Which signaling or metabolic pathway is altered downstream?
4. Cellular phenotype - What changes occur at the cell level (proliferation, apoptosis, secretion)?
5. Physiological outcome - How does the cellular effect translate to the therapeutic benefit in the patient?

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Workflow Overview

1. Report-First Approach (MANDATORY)

DO NOT show the search process or tool outputs to the user. Instead:

1. Create the report file FIRST - [DRUG]_drug_report.md with all 11 section headers and [Researching...] placeholders. See REPORT_TEMPLATE.md for the full template.
2. Progressively update the report - Replace placeholders with findings as you query each tool.
3. Use ALL relevant tools - Query multiple databases for each data type; cross-reference across sources.

2. Citation Requirements (MANDATORY)

Every piece of information MUST include its source. Use inline citations:

*Source: PubChem via `PubChem_get_compound_properties_by_CID` (CID: 4091)*

3. Progressive Writing Workflow

Step 1:  Create report file with all section headers
Step 2:  Resolve compound identifiers -> Update Section 1
Step 3:  Query PubChem/ADMET-AI/DailyMed SPL -> Update Section 2 (Chemistry)
Step 4:  Query FDA Label MOA + ChEMBL + DGIdb -> Update Section 3 (Mechanism)
Step 5:  Query ADMET-AI tools -> Update Section 4 (ADMET)
Step 6:  Query ClinicalTrials.gov -> Update Section 5 (Clinical)
Step 7:  Query FAERS/DailyMed -> Update Section 6 (Safety)
Step 8:  Query PharmGKB -> Update Section 7 (Pharmacogenomics)
Step 9:  Query DailyMed/Orange Book -> Update Section 8 (Regulatory)
Step 10: Query PubMed/literature -> Update Section 9 (Literature)
Step 11: Synthesize findings -> Update Executive Summary & Section 10
Step 12: Document all sources -> Update Section 11 (Data Sources)

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Compound Disambiguation (Phase 1)

CRITICAL: Establish compound identity before any research.

Identifier Resolution Chain

1. PubChem_get_CID_by_compound_name(compound_name)
   -> Extract: CID, canonical SMILES, formula

2. ChEMBL_search_molecules(query=drug_name)
   -> Extract: ChEMBL ID, pref_name

3. DailyMed_search_spls(drug_name)
   -> Extract: Set ID, NDC codes (if approved)

4. PharmGKB_search_drugs(query=drug_name)
   -> Extract: PharmGKB ID (PA...)

5. DrugCentral_search(query=drug_name, size=...)
   -> Extract: InChIKey, CAS number, canonical SMILES, cross-referenced FDA/EMA/PMDA approval status in one call

DrugCentral (live-verified: DrugCentral_search, DrugCentral_get_drug, DrugCentral_get_targets) is a useful fifth disambiguation source and a fast Path 2 (Mechanism & Targets) shortcut — DrugCentral_get_targets(chem_id=<InChIKey or ChEMBL ID>) returns target names/classes directly, which can cross-check (not replace) the ChEMBL-activities-derived target table this skill's Path 2 already builds. Real example: DrugCentral_search(query="metformin") returns InChIKey XZWYZXLIPXDOLR-UHFFFAOYSA-N; DrugCentral_get_targets on that InChIKey returns 5'-AMP-activated protein kinase among its targets.

Dietary supplements are not in PubChem/ChEMBL/DailyMed/DrugCentral as prescription drugs — check the NIH DSLD instead. If the query resolves to zero hits in the chain above (or the user is clearly asking about an OTC vitamin/herbal/supplement product, e.g. "vitamin D gummies" or a specific brand), use NIHDSLD_search_products(query=<name or brand>) -> NIHDSLD_get_label(product_id=...) for the full per-serving ingredient list with amounts and %daily value. Live-verified: NIHDSLD_search_products(query="vitamin d") returns real product 20581 ("Vitamin D Gummy Vitamins", Nutrition Now); NIHDSLD_get_label(20581) returns its full label (2000 IU Vitamin D at 500% daily value per 2-gummy serving, plus calories/carbs/sugar) and an off_market flag. This complements rather than replaces the prescription-drug paths above — supplements have no FDA approval/mechanism-of-action data, so most other report sections legitimately stay "not applicable" for a supplement query.

Handle Naming Ambiguity

Issue	Example	Resolution
Salt forms	metformin vs metformin HCl	Note all CIDs; use parent compound
Isomers	omeprazole vs esomeprazole	Verify SMILES; separate entries if distinct
Prodrugs	enalapril vs enalaprilat	Document both; note conversion
Brand confusion	Different products same name	Clarify with user

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Research Paths Summary

Each path has detailed tool chains and output examples in REPORT_GUIDELINES.md.

PATH 1: Chemical Properties & CMC

Tools: PubChem properties -> ADMET-AI physicochemical -> ADMET-AI solubility -> DailyMed chemistry/description Output: Physicochemical table, Lipinski assessment, QED score, salt forms, formulation comparison

PATH 2: Mechanism & Targets

Tools: DailyMed MOA -> ChEMBL activities (NOT ChEMBL_get_molecule_targets) -> ChEMBL target details -> DGIdb -> PubChem bioactivity Critical: Derive targets from activities filtered to pChEMBL >= 6.0. Avoid ChEMBL_get_molecule_targets. Output: FDA MOA text, target table with UniProt/potency, selectivity profile

PATH 3: ADMET Properties

Tools: ADMET-AI (bioavailability, BBB, CYP, clearance, toxicity) Fallback: DailyMed clinical_pharmacology + pharmacokinetics + drug_interactions Critical: If ADMET-AI fails, automatically use fallback. Never leave Section 4 empty.

PATH 4: Clinical Trials

Tools: search_clinical_trials -> compute phase counts -> extract outcomes/AEs -> fda_pharmacogenomic_biomarkers Critical: Section 5.2 must show actual counts by phase/status in table format.

PATH 5: Post-Marketing Safety

Tools: FAERS (reactions, seriousness, outcomes, deaths, age) + DailyMed (DDI, dosing, warnings) Critical: Include FAERS date window, seriousness breakdown, and limitations paragraph.

PATH 6: Pharmacogenomics

Tools: PharmGKB (search -> details -> annotations -> guidelines) Fallback: DailyMed pharmacogenomics section + PubMed literature

PATH 7: Regulatory & Patents

Tools: FDA Orange Book (search, approval history, exclusivity, patents, generics) + DailyMed (special populations via LOINC codes) Note: US-only data; document EMA/PMDA limitation.

PATH 8: Real-World Evidence

Tools: ClinicalTrials.gov (OBSERVATIONAL studies) + PubMed (real-world, registry, surveillance)

PATH 9: Comparative Analysis

Tools: Abbreviated tool chains for each comparator + head-to-head trial search + PubMed meta-analyses

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FDA Label Core Fields

For approved drugs, retrieve these DailyMed sections early (after getting set_id):

Batch	Sections	Maps to Report
Phase 1	mechanism_of_action, pharmacodynamics, chemistry	Sections 2-3
Phase 2	clinical_pharmacology, pharmacokinetics, drug_interactions	Sections 4, 6.5
Phase 3	warnings_and_cautions, adverse_reactions, dosage_and_administration	Sections 6, 8.2
Phase 4	pharmacogenomics, clinical_studies, description, inactive_ingredients	Sections 5, 7

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Fallback Chains

Primary Tool	Fallback	Use When
PubChem_get_CID_by_compound_name	ChEMBL_search_drugs	Name not in PubChem
ChEMBL_get_molecule_targets	Use ChEMBL_search_activities instead	Always avoid this tool
ChEMBL_get_activity	PubChemBioAssay_get_assay_summary	No ChEMBL ID
DailyMed_search_spls	PubChemTox_get_acute_effects	DailyMed timeout
PharmGKB_search_drugs	DailyMed PGx sections + PubMed	PharmGKB unavailable
PharmGKB_get_dosing_guidelines	DailyMed pharmacogenomics section	PharmGKB API error
FAERS_count_reactions_by_drug_event	Document "FAERS unavailable" + use label AEs	API error
ADMETAI_* (all tools)	DailyMed clinical_pharmacology + pharmacokinetics	Invalid SMILES or API error

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Quick Reference: Tools by Use Case

Use Case	Primary Tool	Fallback	Evidence
Name -> CID	PubChem_get_CID_by_compound_name	ChEMBL_search_drugs	T1
Properties	PubChem_get_compound_properties_by_CID	ADMET-AI physicochemical	T1/T2
FDA MOA	DailyMed_parse_clinical_pharmacology (mechanism_of_action)	-	T1
Targets	ChEMBL_search_activities -> ChEMBL_get_target	DGIdb_get_drug_info	T1
ADMET	ADMETAI_predict_* (5 tools)	DailyMed PK sections	T2/T1
Trials	search_clinical_trials	-	T1
Trial outcomes	extract_clinical_trial_outcomes	-	T1
FAERS	FAERS_count_reactions_by_drug_event	Label adverse_reactions	T1
Dose mods	DailyMed_parse_clinical_pharmacology (dosage, warnings)	-	T1
PGx	PharmGKB_search_drugs	DailyMed PGx + PubMed	T2/T1
Label	DailyMed_search_spls	PubChemTox_get_acute_effects	T1
Literature	PubMed_search_articles	EuropePMC_search_articles	Varies
Regulatory	FDA_OrangeBook_* tools	DailyMed label data	T1

See TOOLS_REFERENCE.md for the complete tool listing with parameters and input format requirements.

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Type Normalization

Many tools require string inputs. Always convert IDs before API calls:

• ChEMBL IDs, PubMed IDs, NCT IDs: convert int -> str
• SMILES for ADMET-AI: pass as list ["SMILES_STRING"]
• FAERS drug names: use UPPERCASE (e.g., "METFORMIN")
• ChEMBL IDs: full format "CHEMBL1431" not "1431"
• PharmGKB IDs: PA prefix "PA450657" not "450657"

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Common Use Cases

Use Case	Primary Sections	Light Sections
Approved Drug Profile	All 11 sections	None
Investigational Compound	1, 2, 3, 4, 9	5, 6, 7, 8
Safety Review	1, 5, 6, 7, 9	2, 3, 4, 8
ADMET Assessment	1, 2, 4	3, 5, 6, 7, 8, 9
Clinical Development Landscape	1, 5, 9	2, 3, 4, 6, 7, 8

Always maintain all section headers but adjust depth based on query focus and data availability.

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When NOT to Use This Skill

• Target research -> Use target-intelligence-gatherer skill
• Disease research -> Use disease-research skill
• Literature-only -> Use literature-deep-research skill
• Single property lookup -> Call tool directly
• Structure similarity search -> Use PubChem_search_compounds_by_similarity directly

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Cross-Skill References

For drug interaction checking, run: python3 skills/tooluniverse-drug-drug-interaction/scripts/pharmacology_ref.py --type interaction --drug1 X --drug2 Y

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Additional Resources

• Report template: REPORT_TEMPLATE.md - Initial file template, citation format, evidence grading, scorecard, audit template
• Report guidelines: REPORT_GUIDELINES.md - Detailed section-by-section instructions with output examples
• Tool reference: TOOLS_REFERENCE.md - Complete tool listing with parameters and input formats
• Verification checklist: CHECKLIST.md - Section-by-section pre-delivery verification
• Examples: EXAMPLES.md - Detailed workflow examples for different use cases