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) (optional) Operation type (fixed)

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

  • adverse_event (string) (optional) MedDRA Preferred Term (e.g., ‘Hepatotoxicity’, ‘Myopathy’). Use exact MedDRA Preferred Term capitalization (e.g., “Haemorrhage” not “hemorrhage”).

  • reaction (string) (optional) Alias for adverse_event. MedDRA Preferred Term for the adverse drug reaction.

  • drug (string) (optional) Alias for drug_name. Generic drug name.

Example Usage:

query = {
    "name": "FAERS_calculate_disproportionality",
    "arguments": {
    }
}
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) (optional) Operation type (fixed)

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

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

  • adverse_event (string) (optional) MedDRA Preferred Term to compare. Use exact MedDRA Preferred Term capitalization (e.g., “Haemorrhage” not “hemorrhage”).

  • reaction (string) (optional) Alias for adverse_event. MedDRA Preferred Term for the adverse drug reaction.

  • drugs (array) (optional) Alias for drug1/drug2. List of two drug names to compare, e.g., [“tofacitinib”, “baricitinib”].

Example Usage:

query = {
    "name": "FAERS_compare_drugs",
    "arguments": {
    }
}
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) (optional) Operation type (fixed)

  • drug_name (string) (optional) Generic drug name

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

  • drug (string) (optional) Alias for drug_name. Generic drug name.

  • event_type (string) (optional) Alias for seriousness_type. Type of serious event (e.g., hospitalization, death, life_threatening).

  • adverse_event (string) (optional) Specific adverse event MedDRA term to filter within serious events (e.g., MYOCARDIAL INFARCTION, DEATH). Use uppercase MedDRA PT terms.

Example Usage:

query = {
    "name": "FAERS_filter_serious_events",
    "arguments": {
    }
}
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) (optional) Operation type (fixed)

  • drug_name (string) (optional) Generic drug name

  • drug (string) (optional) Alias for drug_name. Generic drug name.

Example Usage:

query = {
    "name": "FAERS_rollup_meddra_hierarchy",
    "arguments": {
    }
}
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) (optional) Operation type (fixed)

  • drug_name (string) (optional) Generic drug name

  • adverse_event (string) (optional) MedDRA Preferred Term. Use exact MedDRA Preferred Term capitalization (e.g., “Haemorrhage” not “hemorrhage”).

  • stratify_by (string) (optional) Demographic dimension to stratify by. Use “sex”, “age”, or “country” (“age_group” is also accepted as alias for “age”).

  • reaction (string) (optional) Alias for adverse_event. MedDRA Preferred Term for the adverse drug reaction (e.g., “hemorrhage”, “nausea”).

  • demographic (string) (optional) Alias for stratify_by. Demographic dimension to stratify by (sex, age, or country).

  • drug (string) (optional) Alias for drug_name. Generic drug name.

Example Usage:

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