Drug Research Strategy
Comprehensive drug investigation using 50+ ToolUniverse tools across chemical databases, clinical trials, adverse events, pharmacogenomics, and literature.
KEY PRINCIPLES:
- Report-first approach - Create report file FIRST, then populate progressively
- Compound disambiguation FIRST - Resolve identifiers before research
- Citation requirements - Every fact must have inline source attribution
- Evidence grading - Grade claims by evidence strength (T1-T4)
- Mandatory completeness - All sections must exist, even if "data unavailable"
- 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
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.
Drug Mechanism Reasoning
When investigating a drug's mechanism of action, trace the full causal chain:
- Target engagement - Which protein(s) does the drug bind, and with what affinity/selectivity?
- Molecular effect - Does binding inhibit, activate, or modulate the target's function?
- Pathway consequence - Which signaling or metabolic pathway is altered downstream?
- Cellular phenotype - What changes occur at the cell level (proliferation, apoptosis, secretion)?
- Physiological outcome - How does the cellular effect translate to the therapeutic benefit in the patient?
Workflow Overview
1. Report-First Approach (MANDATORY)
DO NOT show the search process or tool outputs to the user. Instead:
- Create the report file FIRST -
[DRUG]_drug_report.mdwith all 11 section headers and[Researching...]placeholders. See REPORT_TEMPLATE.md for the full template. - Progressively update the report - Replace placeholders with findings as you query each tool.
- 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)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_compounds(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...)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 |
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
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 |
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 |
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.
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"
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.
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_similaritydirectly
Cross-Skill References
For drug interaction checking, run: python3 skills/tooluniverse-drug-drug-interaction/scripts/pharmacology_ref.py --type interaction --drug1 X --drug2 Y
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