tooluniverse-pharmacovigilance

Pharmacovigilance Safety Analyzer

Systematic drug safety analysis using FAERS adverse event data, FDA labeling, PharmGKB pharmacogenomics, and clinical trial safety signals.

KEY PRINCIPLES:

1. Report-first approach - Create report file FIRST, update progressively
2. Signal quantification - Use disproportionality measures (PRR, ROR)
3. Severity stratification - Prioritize serious/fatal events
4. Multi-source triangulation - FAERS, labels, trials, literature
5. Pharmacogenomic context - Include genetic risk factors
6. Actionable output - Risk-benefit summary with recommendations
7. English-first queries - Always use English drug names and search terms 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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When to Use

Apply when user asks:

• "What are the safety concerns for [drug]?"
• "What adverse events are associated with [drug]?"
• "Is [drug] safe? What are the risks?"
• "Should I be concerned about [specific adverse event] with [drug]?"
• "Compare safety profiles of [drug A] vs [drug B]"
• "Pharmacovigilance analysis for [drug]"

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Critical Workflow Requirements

1. Report-First Approach (MANDATORY)

1. Create the report file FIRST:

   • File name: [DRUG]_safety_report.md
   • Initialize with all section headers
   • Add placeholder text: [Researching...]

2. Progressively update as you gather data

3. Output separate data files:

   • [DRUG]_adverse_events.csv - Ranked AEs with counts/signals
   • [DRUG]_pharmacogenomics.csv - PGx variants and recommendations

2. Citation Requirements (MANDATORY)

Every safety signal MUST include source:

### Signal: Hepatotoxicity
- **PRR**: 3.2 (95% CI: 2.8-3.7)
- **Cases**: 1,247 reports
- **Serious**: 892 (71.5%)
- **Fatal**: 23

*Source: FAERS via `FAERS_count_reactions_by_drug_event` (Q1 2020 - Q4 2025)*

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Phase 0: Tool Verification

CRITICAL: Verify tool parameters before calling.

Known Parameter Corrections

Tool	WRONG Parameter	CORRECT Parameter
FAERS_count_reactions_by_drug_event	drug	drug_name
DailyMed_search_spls	name	drug_name
PharmGKB_search_drug	drug	query
OpenFDA_get_drug_events	drug_name	search

---

Workflow Overview

Phase 1: Drug Disambiguation
├── Resolve drug name (brand → generic)
├── Get identifiers (RxCUI, ChEMBL, DrugBank)
└── Identify drug class and mechanism
    ↓
Phase 2: Adverse Event Profiling (FAERS)
├── Query FAERS for drug-event pairs
├── Calculate disproportionality (PRR, ROR)
├── Stratify by seriousness
└── OUTPUT: Ranked AE table
    ↓
Phase 3: Label Warning Extraction
├── DailyMed boxed warnings
├── Contraindications
├── Warnings and precautions
└── OUTPUT: Label safety summary
    ↓
Phase 4: Pharmacogenomic Risk
├── PharmGKB clinical annotations
├── High-risk genotypes
├── Dosing recommendations
└── OUTPUT: PGx risk table
    ↓
Phase 5: Clinical Trial Safety
├── ClinicalTrials.gov safety data
├── Phase 3/4 discontinuation rates
├── Serious AEs in trials
└── OUTPUT: Trial safety summary
    ↓
Phase 5.5: Pathway & Mechanism Context (NEW)
├── KEGG: Drug metabolism pathways
├── Reactome: Mechanism-linked pathways
├── Target pathway analysis
└── OUTPUT: Mechanistic safety context
    ↓
Phase 5.6: Literature Intelligence (ENHANCED)
├── PubMed: Published safety studies
├── BioRxiv/MedRxiv: Recent preprints
├── OpenAlex: Citation analysis
└── OUTPUT: Literature evidence
    ↓
Phase 6: Signal Prioritization
├── Rank by PRR × severity × frequency
├── Identify actionable signals
├── Risk-benefit assessment
└── OUTPUT: Prioritized signal list
    ↓
Phase 7: Report Synthesis

---

Phase 1: Drug Disambiguation

1.1 Resolve Drug Identity

def resolve_drug(tu, drug_query):
    """Resolve drug name to standardized identifiers."""
    identifiers = {}
    
    # DailyMed for NDC and SPL
    dailymed = tu.tools.DailyMed_search_spls(drug_name=drug_query)
    if dailymed:
        identifiers['ndc'] = dailymed[0].get('ndc')
        identifiers['setid'] = dailymed[0].get('setid')
        identifiers['generic_name'] = dailymed[0].get('generic_name')
    
    # ChEMBL for molecule data
    chembl = tu.tools.ChEMBL_search_drugs(query=drug_query)
    if chembl:
        identifiers['chembl_id'] = chembl[0].get('molecule_chembl_id')
        identifiers['max_phase'] = chembl[0].get('max_phase')
    
    return identifiers

1.2 Output for Report

## 1. Drug Identification

| Property | Value |
|----------|-------|
| **Generic Name** | Metformin |
| **Brand Names** | Glucophage, Fortamet, Glumetza |
| **Drug Class** | Biguanide antidiabetic |
| **ChEMBL ID** | CHEMBL1431 |
| **Mechanism** | AMPK activator, hepatic gluconeogenesis inhibitor |
| **First Approved** | 1994 (US) |

*Source: DailyMed via `DailyMed_search_spls`, ChEMBL*

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Phase 2: Adverse Event Profiling

2.1 FAERS Query Strategy

def get_faers_events(tu, drug_name, top_n=50):
    """Query FAERS for adverse events."""
    
    # Get event counts
    events = tu.tools.FAERS_count_reactions_by_drug_event(
        drug_name=drug_name,
        limit=top_n
    )
    
    # For each event, get detailed breakdown
    detailed_events = []
    for event in events:
        detail = tu.tools.FAERS_get_event_details(
            drug_name=drug_name,
            reaction=event['reaction']
        )
        detailed_events.append({
            'reaction': event['reaction'],
            'count': event['count'],
            'serious': detail.get('serious_count', 0),
            'fatal': detail.get('death_count', 0),
            'hospitalization': detail.get('hospitalization_count', 0)
        })
    
    return detailed_events

2.2 Disproportionality Analysis

Proportional Reporting Ratio (PRR):

PRR = (A/B) / (C/D)

Where:
A = Reports of drug X with event Y
B = Reports of drug X with any event
C = Reports of event Y with any drug (excluding X)
D = Total reports (excluding drug X)

Signal Thresholds:

Measure	Signal Threshold	Strong Signal
PRR	>2.0	>3.0
Chi-squared	>4.0	>10.0
N (case count)	≥3	≥10

2.3 Severity Classification

Category	Definition	Priority
Fatal	Death outcome	Highest
Life-threatening	Immediate death risk	Very High
Hospitalization	Required/prolonged hospitalization	High
Disability	Persistent impairment	High
Congenital anomaly	Birth defect	High
Other serious	Medical intervention required	Medium
Non-serious	No serious criteria	Low

2.4 Output for Report

## 2. Adverse Event Profile (FAERS)

**Data Period**: Q1 2020 - Q4 2025
**Total Reports for Drug**: 45,234

### 2.1 Top Adverse Events by Frequency

| Rank | Adverse Event | Reports | PRR | 95% CI | Serious (%) | Fatal |
|------|---------------|---------|-----|--------|-------------|-------|
| 1 | Diarrhea | 8,234 | 2.3 | 2.1-2.5 | 12% | 3 |
| 2 | Nausea | 6,892 | 1.8 | 1.6-2.0 | 8% | 0 |
| 3 | Lactic acidosis | 1,247 | 15.2 | 12.8-17.9 | 89% ⚠️ | 156 ⚠️ |
| 4 | Hypoglycemia | 2,341 | 2.1 | 1.9-2.4 | 34% | 8 |
| 5 | Vitamin B12 deficiency | 892 | 8.4 | 7.2-9.8 | 23% | 0 |

### 2.2 Serious Adverse Events Only

| Adverse Event | Serious Reports | Fatal | PRR | Signal |
|---------------|-----------------|-------|-----|--------|
| Lactic acidosis | 1,110 | 156 | 15.2 | **STRONG** ⚠️ |
| Acute kidney injury | 678 | 34 | 4.2 | Moderate |
| Hepatotoxicity | 234 | 12 | 3.1 | Moderate |

### 2.3 Signal Interpretation

**Strong Signal: Lactic Acidosis** ⚠️
- PRR of 15.2 indicates 15x higher reporting rate than expected
- 89% classified as serious
- 156 fatalities (12.5% case fatality)
- **Known class effect of biguanides**
- Risk factors: renal impairment, hypoxia, contrast agents

*Source: FAERS via `FAERS_count_reactions_by_drug_event`*

---

Phase 3: Label Warning Extraction

3.1 DailyMed Query

def extract_label_warnings(tu, setid):
    """Extract safety sections from FDA label."""
    
    label = tu.tools.DailyMed_get_spl_by_set_id(setid=setid)
    
    warnings = {
        'boxed_warning': label.get('boxed_warning'),
        'contraindications': label.get('contraindications'),
        'warnings_precautions': label.get('warnings_and_precautions'),
        'adverse_reactions': label.get('adverse_reactions'),
        'drug_interactions': label.get('drug_interactions')
    }
    
    return warnings

3.2 Warning Severity Categories

Category	Symbol	Description
Boxed Warning	⬛	Most serious, life-threatening
Contraindication	🔴	Must not use
Warning	🟠	Significant risk
Precaution	🟡	Use caution

3.3 Output for Report

## 3. FDA Label Safety Information

### 3.1 Boxed Warning ⬛

**LACTIC ACIDOSIS**
> Metformin can cause lactic acidosis, a rare but serious complication. 
> Risk increases with renal impairment, sepsis, dehydration, excessive 
> alcohol intake, hepatic impairment, and acute heart failure.
> 
> **Contraindicated in patients with eGFR <30 mL/min/1.73m²**

### 3.2 Contraindications 🔴

| Contraindication | Rationale |
|------------------|-----------|
| eGFR <30 mL/min/1.73m² | Lactic acidosis risk |
| Acute/chronic metabolic acidosis | May worsen acidosis |
| Hypersensitivity to metformin | Allergic reaction |

### 3.3 Warnings and Precautions 🟠

| Warning | Clinical Action |
|---------|-----------------|
| Vitamin B12 deficiency | Monitor B12 levels annually |
| Hypoglycemia with insulin | Reduce insulin dose |
| Radiologic contrast | Hold 48h around procedure |
| Surgical procedures | Hold day of surgery

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