tooluniverse-drug-research

# 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
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

---

## Critical Workflow Requirements

### 1. Report-First Approach (MANDATORY)

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

1. **Create the report file FIRST** - Before any data collection, create a markdown file:
   - File name: `[DRUG]_drug_report.md` (e.g., `metformin_drug_report.md`)
   - Initialize with all 11 section headers from the template
   - Add placeholder text: `[Researching...]` in each section

2. **Progressively update the report** - As you gather data:
   - Update each section with findings immediately after retrieving data
   - Replace `[Researching...]` with actual content
   - The user sees the report growing, not the search process

3. **Use ALL relevant tools** - For comprehensive coverage:
   - Query multiple databases for each data type
   - Cross-reference information across sources
   - Use fallback tools when primary tools return limited data

### 2. Citation Requirements (MANDATORY)

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

```markdown
## 3. Mechanism & Targets

### 3.1 Primary Mechanism
Metformin activates AMP-activated protein kinase (AMPK), reducing hepatic glucose 
production and increasing insulin sensitivity in peripheral tissues.

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

### 3.2 Primary Target(s)
| Target | UniProt | Activity | Potency | Source |
|--------|---------|----------|---------|--------|
| AMPK (PRKAA1) | Q13131 | Activator | EC50 ~10 µM | ChEMBL |
| Mitochondrial Complex I | - | Inhibitor | IC50 ~1 mM | Literature |

*Source: ChEMBL via `ChEMBL_get_target_by_chemblid` (CHEMBL1431)*
```

### Citation Format

For each data section, include at the end:

```markdown
---
**Data Sources for this section:**
- PubChem: `PubChem_get_compound_properties_by_CID` (CID: 4091)
- ChEMBL: `ChEMBL_get_bioactivity_by_chemblid` (CHEMBL1431)
- DGIdb: `DGIdb_get_drug_info` (metformin)
---
```

### 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 activities + DGIdb → Update Section 3 (Mechanism & Targets)
        ↓
Step 5: Query ADMET-AI tools → Update Section 4 (ADMET)
        ↓
Step 6: Query ClinicalTrials.gov → Update Section 5 (Clinical Development)
        ↓
Step 7: Query FAERS/DailyMed → Update Section 6 (Safety)
        ↓
Step 8: Query PharmGKB → Update Section 7 (Pharmacogenomics)
        ↓
Step 9: Query DailyMed → 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)
```

### 4. Report Detail Requirements

Each section must be **comprehensive and detailed**:

- **Tables**: Use tables for structured data (targets, trials, adverse events)
- **Lists**: Use bullet points for features, findings, key points
- **Paragraphs**: Include narrative summaries that synthesize findings
- **Numbers**: Include specific values, counts, percentages (not vague terms)
- **Context**: Explain what the data means, not just what it is

**BAD** (too brief):
```markdown
### Clinical Trials
Multiple trials completed. Approved for diabetes.
```

**GOOD** (detailed with sources):
```markdown
### 5.2 Clinical Trial Landscape

| Phase | Total | Completed | Recruiting | Status |
|-------|-------|-----------|------------|--------|
| Phase 4 | 89 | 72 | 12 | Post-marketing |
| Phase 3 | 156 | 134 | 15 | Pivotal |
| Phase 2 | 203 | 178 | 18 | Dose-finding |
| Phase 1 | 67 | 61 | 4 | Safety |

*Source: ClinicalTrials.gov via `search_clinical_trials` (intervention="metformin")*

**Total Registered Trials**: 515 (as of 2026-02-04)
**Primary Indications Under Investigation**: Type 2 diabetes (312), PCOS (87), Cancer (45), Obesity (38), NAFLD (33)

### Trial Outcomes Summary
- **Glycemic Control**: Mean HbA1c reduction of 1.0-1.5% in monotherapy [★★★: NCT00123456]
- **Cardiovascular**: UKPDS showed 39% reduction in MI risk [★★★: PMID:9742976]
- **Cancer Prevention**: Mixed results; ongoing investigation [★★☆: NCT02019979]

*Source: `extract_clinical_trial_outcomes` for NCT IDs listed*
```

---

## Initial Report Template (Create This First)

When starting research, **immediately create this file** before any tool calls:

**File**: `[DRUG]_drug_report.md`

```markdown
# Drug Research Report: [DRUG NAME]

**Generated**: [Date] | **Query**: [Original query] | **Status**: In Progress

---

## Executive Summary
[Researching...]

---

## 1. Compound Identity
### 1.1 Database Identifiers
[Researching...]
### 1.2 Structural Information
[Researching...]
### 1.3 Names & Synonyms
[Researching...]

---

## 2. Chemical Properties
### 2.1 Physicochemical Profile
[Researching...]
### 2.2 Drug-Likeness Assessment
[Researching...]
### 2.3 Solubility & Permeability
[Researching...]
### 2.4 Salt Forms & Polymorphs
[Researching...]
### 2.5 Structure Visualization
[Researching...]

---

## 3. Mechanism & Targets
### 3.1 Primary Mechanism of Action
[Researching...]
### 3.2 Primary Target(s)
[Researching...]
### 3.3 Target Selectivity & Off-Targets
[Researching...]
### 3.4 Bioactivity Profile (ChEMBL)
[Researching...]

---

## 4. ADMET Properties
### 4.1 Absorption
[Researching...]
### 4.2 Distribution
[Researching...]
### 4.3 Metabolism
[Researching...]
### 4.4 Excretion
[Researching...]
### 4.5 Toxicity Predictions
[Researching...]

---

## 5. Clinical Development
### 5.1 Development Status
[Researching...]
### 5.2 Clinical Trial Landscape
[Researching...]
### 5.3 Approved Indications
[Researching...]
### 5.4 Investigational Indications
[Researching...]
### 5.5 Key Efficacy Data
[Researching...]
### 5.6 Biomarkers & Companion Diagnostics
[Researching...]

---

## 6. Safety Profile
### 6.1 Clinical Adverse Events
[Researching...]
### 6.2 Post-Marketing Safety (FAERS)
[Researching...]
### 6.3 Black Box Warnings
[Researching...]
### 6.4 Contraindications
[Researching...]
### 6.5 Drug-Drug Interactions
[Researching...]
### 6.5.2 Drug-Food Interactions
[Researching...]
### 6.6 Dose Modification Guidance
[Researching...]
### 6.7 Drug Combinations & Regimens
[Researching...]

---

## 7. Pharmacogenomics
### 7.1 Relevant Pharmacogenes
[Researching...]
### 7.2 Clinical Annotations
[Researching...]
### 7.3 Dosing Guidelines (CPIC/DPWG)
[Researching...]
### 7.4 Actionable Variants
[Researching...]

---

## 8. Regulatory & Labeling
### 8.1 Approval Status
[Researching...]
### 8.2 Label Highlights
[Researching...]
### 8.3 Patents & Exclusivity
[Researching...]
### 8.4 Label Changes & Warnings
[Researching...]
### 8.5 Special Populations
[Researching...]
### 8.6 Regulatory Timeline & History
[Researching...]

---

## 9. Literature & Research Landscape
### 9.1 Publication Metrics
[Researching...]
### 9.2 Research Themes
[Researching...]
### 9.3 Recent Key Publications
[Researching...]
### 9.4 Real-World Evidence
[Researching...]

---

## 10. Conclusions & Assessment
### 10.1 Drug Profile Scorecard
[Researching...]
### 10.2 Key Strengths
[Researching...]
### 10.3 Key Concerns/Limitations
[Researching...]
### 10.4 Research Gaps
[Researching...]
### 10.5 Comparative Analysis
[Researching...]

---

## 11. Data Sources & Methodology
### 11.1 Primary Data Sources
[Researching...]
### 11.2 Tool Call Summary
[Researching...]
### 11.3 Quality Control Metrics
[Researching...]
```

Then progressively replace `[Researching...]` with actual findings as you query each tool.

---

## FDA Label Core Fields Bundle

**For approved drugs, ALWAYS retrieve these FDA label sections early** (after getting set_id from `DailyMed_search_spls`):

### Critical Label Sections

Call `DailyMed_get_spl_sections_by_setid(setid=set_id, sections=[...])` with these sections:

**Phase 1 (Mechanism & Chemistry)**:
- `mechanism_of_action` → Section 3.1
- `pharmacodynamics` → Section 3.1
- `chemistry` → Section 2.4

**Phase 2 (ADMET & PK)**:
- `clinical_pharmacology` → Section 4
- `pharmacokinetics` → Section 4.1-4.4
- `drug_interactions` → Section 4.3, 6.5

**Phase 3 (Safety & Dosing)**:
- `warnings_and_cautions` → Section 6.3
- `adverse_reactions` → Section 6.1
- `dosage_and_administration` → Section 6.6, 8.2

**Phase 4 (PGx & Clinical)**:
- `pharmacogenomics` → Section 7
- `clinical_studies` → Section 5.5
- `description` → Section 2.5 (formulation)
- `inactive_ingredients` → Section 2.5

### Label Extraction Strategy

```
1. Get set_id: DailyMed_search_spls(drug_name)
   
2. Batch call for all core sections (or 3-4 calls with 4-5 sections each):
   DailyMed_get_spl_sections_by_setid(setid=set_id, sections=["mechanism_of_action", "pharmacodynamics", ...])
   
3. Extract and populate report sections as you retrieve data
```

This ensures you have authoritative FDA-approved information even if prediction tools fail.

---

## 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 |

---

## Key Tools by Report Section

| Report Section | Primary Tools | Fallback |
|----------------|--------------|----------|
| 1. Identity | `PubChem_get_CID_by_compound_name`, `ChEMBL_search_compounds`, `DailyMed_search_spls` | `PharmGKB_search_drugs` |
| 2. Chemistry | `PubChem_get_compound_properties_by_CID`, `ADMETAI_predict_physicochemical_properties` | `DailyMed_get_spl_sections_by_setid` (sections=["chemistry"]) |
| 3. Mechanism | `DailyMed_get_spl_sections_by_setid` (sections=["mechanism_of_action"]), `OpenTargets_get_drug_mechanisms_of_action_by_chemblId` | `DGIdb_get_drug_gene_interactions`, `CTD_get_chemical_gene_interactions` |
| 4. ADMET | `ADMETAI_predict_absorption`, `ADMETAI_predict_distribution`, `ADMETAI_predict_metabolism`, `ADMETAI_predict_excretion`, `ADMETAI_predict_toxicity` | `DailyMed_get_spl_sections_by_setid` (sections=["pharmacokinetics"]) |
| 5. Clinical | `search_clinical_trials` (query_term REQUIRED), `extract_clinical_trial_outcomes` | `OpenTargets_get_drug_indications_by_chemblId` |
| 6. Safety | `FAERS_calculate_disproportionality`, `FAERS_count_reactions_by_drug`, `DailyMed_get_spl_sections_by_setid` (sections=["warnings_and_cautions", "adverse_reactions"]) | `OpenTargets_get_drug_adverse_events_by_chemblId` |
| 7. PGx | `PharmGKB_get_clinical_annotations`, `PharmGKB_get_drug_label_info` | `DailyMed_get_spl_sections_by_setid` (sections=["pharmacogenomics"]) |
| 8. Regulatory | `DailyMed_search_spls`, `FDA_get_warnings_and_cautions_by_drug_name` | `OpenTargets_get_drug_warnings_by_chemblId` |
| 9. Literature | `PubMed_search_articles` (returns plain list), `EuropePMC_search_articles` | `OpenTargets_get_publications_by_drug_chemblId` |

**Key API notes**:
- FAERS analytics: ALL require `operation` parameter
- FAERS count tools: use `medicinalproduct` NOT `drug_name`
- DrugBank tools: ALL require `query`, `case_sensitive`, `exact_match`, `limit` (4 params)
- ADMETAI tools: `smiles` must be a list `[smiles_string]`
- PubMed: returns plain list, NOT `{articles: [...]}`
- DailyMed: get set_id first via `DailyMed_search_spls`, then call section tools

---

## Common Use Cases

- **Approved drug profile**: Full 11-section report (emphasize clinical, FAERS, PGx)
- **Investigational compound**: Emphasize preclinical, mechanism, early trials; safety sparse
- **Safety review**: Deep dive FAERS + warnings + interactions + PGx
- **ADMET assessment**: Focus Sections 2 & 4; other sections brief
- **Clinical landscape**: Heavy Section 5; trial tables with phases/indications

---

> **Extended Reference**: Full tool chain examples with exact parameter types, response parsing, evidence grading system, and quality improvement tips from real-world testing are in `REFERENCE.md`.