Monitor and summarize competitor clinical trial status changes from ClinicalTrials.gov. Trigger: When user asks to track clinical trials, monitor trial status changes, get updates on specific trials, or analyze competitor trial activities. Use cases: Pharma competitive intelligence, trial monitoring, status tracking, recruitment updates, completion alerts.
Monitor and summarize competitor clinical trial status changes from ClinicalTrials.gov.
| Parameter | Type | Default | Required | Description |
|---|---|---|---|---|
--sponsor | string | - | No | Trial sponsor name |
--condition | string | - | No | Medical condition/disease |
--status | string | - | No |
| Trial status (Recruiting, Completed, etc.) |
--trials | string | - | No | Comma-separated trial IDs (NCT numbers) |
--output | string | json | No | Output format (json, csv) |
--days | int | 30 | No | Number of days for monitoring |
from scripts.main import ClinicalTrialsMonitor
# Initialize monitor
monitor = ClinicalTrialsMonitor()
# Search for trials
trials = monitor.search_trials(
sponsor="Pfizer",
condition="Diabetes",
status="Recruiting"
)
# Get trial details
trial = monitor.get_trial("NCT05108922")
# Check for status changes
changes = monitor.check_status_changes(trial_ids=["NCT05108922"])
# Search trials
python scripts/main.py search --sponsor "Pfizer" --condition "Diabetes"
# Get trial details
python scripts/main.py get NCT05108922
# Monitor status changes
python scripts/main.py monitor --trials NCT05108922,NCT05108923 --output json
# Generate summary report
python scripts/main.py report --sponsor "Pfizer" --days 30
| Method | Description |
|---|---|
search_trials() | Search trials with filters |
get_trial(nct_id) | Get detailed trial information |
check_status_changes() | Check for status updates |
get_recruitment_status() | Get enrollment updates |
generate_summary() | Generate competitor summary |
references/api-docs.md for API documentationreferences/status-codes.md for trial status definitionsreferences/examples.md for usage examples| Risk Indicator | Assessment | Level |
|---|---|---|
| Code Execution | Python scripts with tools | High |
| Network Access | External API calls | High |
| File System Access | Read/write data | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Data handled securely | Medium |
# Python dependencies
pip install -r requirements.txt