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:

## 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:

---
**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):

### Clinical Trials
Multiple trials completed. Approved for diabetes.

GOOD (detailed with sources):

### 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

# 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

Key Tools by Report Section

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.