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Adverse drug event detection, safety signal mining, and drug monitoring
Passed 20 of 22 test cases with the skill, and 16 of 22 without it.
and 2 more in the full report
4 fixed16 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
Which Standardized MedDRA Query (SMQ) standard incorporates Hy's Law criteria for evaluating potential liver toxicity signals in pharmacovigilance?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies Drug-induced liver injury as the SMQ associated with Hy's Law | Missed | Passed |
The instructions your model reads when the skill loads.
A skill for computational pharmacovigilance research, covering adverse drug event (ADE) databases, signal detection algorithms, disproportionality analysis, and safety surveillance methods used in post-market drug monitoring.
| Database | Operator | Coverage | Access |
|---|---|---|---|
| FAERS (FDA Adverse Event Reporting System) | FDA | US spontaneous reports | Free quarterly downloads |
| EudraVigilance | EMA | European reports | Research access via application |
| VigiBase | WHO-UMC | Global (150+ countries) | Research license |
| VAERS | CDC/FDA | US vaccine adverse events | Free download |
| MAUDE | FDA | Medical device reports | Free download |
import pandas as pd
import zipfile
import os
def load_faers_quarter(data_dir: str, year: int, quarter: int) -> dict:
"""
Load FAERS quarterly data files into DataFrames.
Downloads available from: fis.fda.gov/extensions/FPD-QDE-FAERS/FPD-QDE-FAERS.html
Returns dict of DataFrames for each file type.
"""
prefix = f"faers_ascii_{year}Q{quarter}"
tables = {}
file_map = {
"DEMO": "demographics", # Patient demographics
"DRUG": "drugs", # Drug information
"REAC": "reactions", # Adverse reactions (MedDRA terms)
"OUTC": "outcomes", # Patient outcomes
"INDI": "indications", # Drug indications
"THER": "therapy", # Therapy dates
"RPSR": "report_sources", # Report source
test cases passed, vs 16 / 22 without
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