Faers Analytics Tools

Configuration File: faers_analytics_tools.json Tool Type: Local Tools Count: 6

This page contains all tools defined in the faers_analytics_tools.json configuration file.

Available Tools

FAERS_calculate_disproportionality (Type: FAERSAnalyticsTool)

Calculate statistical disproportionality measures (ROR, PRR, IC) with 95% CI for drug-event pairs…

FAERS_calculate_disproportionality tool specification

Tool Information:

  • Name: FAERS_calculate_disproportionality

  • Type: FAERSAnalyticsTool

  • Description: Calculate statistical disproportionality measures (ROR, PRR, IC) with 95% CI for drug-event pairs. Returns signal strength classification. Example: drug=’ibuprofen’, event=’hepatotoxicity’ → ROR=2.3 [1.8-2.9]. Use for pharmacovigilance signal detection.

Parameters:

  • operation (unknown) (required) Operation type (fixed)

  • drug_name (string) (required) Generic drug name (e.g., ‘IBUPROFEN’, ‘ATORVASTATIN’)

  • adverse_event (string) (required) MedDRA Preferred Term (e.g., ‘Hepatotoxicity’, ‘Myopathy’)

Example Usage:

query = {
    "name": "FAERS_calculate_disproportionality",
    "arguments": {
        "operation": "example_value",
        "drug_name": "example_value",
        "adverse_event": "example_value"
    }
}
result = tu.run(query)

FAERS_compare_drugs (Type: FAERSAnalyticsTool)

Compare safety signals for two drugs with the same adverse event. Returns ROR/PRR/IC for both dru…

FAERS_compare_drugs tool specification

Tool Information:

  • Name: FAERS_compare_drugs

  • Type: FAERSAnalyticsTool

  • Description: Compare safety signals for two drugs with the same adverse event. Returns ROR/PRR/IC for both drugs with comparative analysis. Example: compare fulvestrant vs tamoxifen for hepatotoxicity. Use for safety benchmarking.

Parameters:

  • operation (unknown) (required) Operation type (fixed)

  • drug1 (string) (required) First drug name (generic)

  • drug2 (string) (required) Second drug name (generic)

  • adverse_event (string) (required) MedDRA Preferred Term to compare

Example Usage:

query = {
    "name": "FAERS_compare_drugs",
    "arguments": {
        "operation": "example_value",
        "drug1": "example_value",
        "drug2": "example_value",
        "adverse_event": "example_value"
    }
}
result = tu.run(query)

FAERS_filter_serious_events (Type: FAERSAnalyticsTool)

Filter for serious adverse events (death, hospitalization, disability, life-threatening). Returns…

FAERS_filter_serious_events tool specification

Tool Information:

  • Name: FAERS_filter_serious_events

  • Type: FAERSAnalyticsTool

  • Description: Filter for serious adverse events (death, hospitalization, disability, life-threatening). Returns top reactions meeting seriousness criteria. Example: fulvestrant serious events → Death: 150 cases, Hospitalization: 500 cases. Use for risk-benefit assessment.

Parameters:

  • operation (unknown) (required) Operation type (fixed)

  • drug_name (string) (required) Generic drug name

  • seriousness_type (string) (optional) Type of serious event to filter

Example Usage:

query = {
    "name": "FAERS_filter_serious_events",
    "arguments": {
        "operation": "example_value",
        "drug_name": "example_value"
    }
}
result = tu.run(query)

FAERS_rollup_meddra_hierarchy (Type: FAERSAnalyticsTool)

Aggregate adverse events by MedDRA hierarchy (Preferred Term level). Returns top 50 PTs with coun…

FAERS_rollup_meddra_hierarchy tool specification

Tool Information:

  • Name: FAERS_rollup_meddra_hierarchy

  • Type: FAERSAnalyticsTool

  • Description: Aggregate adverse events by MedDRA hierarchy (Preferred Term level). Returns top 50 PTs with counts. Note: Full HLT/SOC hierarchy requires MedDRA license. Use for adverse event profile overview.

Parameters:

  • operation (unknown) (required) Operation type (fixed)

  • drug_name (string) (required) Generic drug name

Example Usage:

query = {
    "name": "FAERS_rollup_meddra_hierarchy",
    "arguments": {
        "operation": "example_value",
        "drug_name": "example_value"
    }
}
result = tu.run(query)

FAERS_stratify_by_demographics (Type: FAERSAnalyticsTool)

Stratify adverse event reports by demographics (sex, age group, country). Returns counts and perc…

FAERS_stratify_by_demographics tool specification

Tool Information:

  • Name: FAERS_stratify_by_demographics

  • Type: FAERSAnalyticsTool

  • Description: Stratify adverse event reports by demographics (sex, age group, country). Returns counts and percentages by demographic group. Example: ibuprofen + GI bleeding stratified by sex → Female: 60%, Male: 40%. Use for subpopulation risk assessment.

Parameters:

  • operation (unknown) (required) Operation type (fixed)

  • drug_name (string) (required) Generic drug name

  • adverse_event (string) (required) MedDRA Preferred Term

  • stratify_by (string) (optional) Demographic dimension to stratify by

Example Usage:

query = {
    "name": "FAERS_stratify_by_demographics",
    "arguments": {
        "operation": "example_value",
        "drug_name": "example_value",
        "adverse_event": "example_value"
    }
}
result = tu.run(query)