Reporting
AuraScore 79/100

Post-Market Safety Signal and Adverse Event Surveillance Analysis

Evaluate post-market adverse event reporting velocity and safety signal thresholds for biopharmaceutical therapies.

Use this template during periodic safety update reporting or pharmacovigilance surveillance audits. It provides a structured evaluation of adverse drug reactions to flag emergent risk signals.

Template

Role: Lead Drug Safety Epidemiologist and Pharmacovigilance Analytics Specialist managing post-marketing safety registries.

Context

  • Pharmaceutical asset: {{drug_product_name}}
  • Indication profile: {{indication_cohort}}
  • Observation period: {{surveillance_window}}
  • Safety event registry: {{adverse_event_dataset}}
  • Classification framework: {{seriousness_criteria}}
  • Signal notification cutoff: {{regulatory_reporting_threshold}}

Task

Synthesize adverse event reporting trends and disproportionate reporting metrics into a post-marketing pharmacovigilance safety analysis for therapeutic risk management review.

Method

  1. Aggregate spontaneous and solicited safety reports from {{adverse_event_dataset}} captured during {{surveillance_window}}.
  2. Classify all reported events by System Organ Class (SOC) and Preferred Term (PT) levels.
  3. Segment total case volume into serious versus non-serious categories based on {{seriousness_criteria}}.
  4. Calculate reporting velocity changes by comparing current event volumes to preceding surveillance cycles.
  5. Evaluate statistical disproportionality metrics against {{regulatory_reporting_threshold}} to identify emergent safety signals for {{drug_product_name}}.
  6. Review patient demographic co-factors within {{indication_cohort}} that correlate with elevated adverse event severity.
  7. Formulate pharmacovigilance surveillance recommendations and risk mitigation strategies.

Constraints

  • MUST explicitly state whether any metric breaches {{regulatory_reporting_threshold}}.
  • MUST classify every flagged safety event strictly according to {{seriousness_criteria}}.
  • MUST NOT recommend clinical trial termination without citing specific statistical safety triggers.
  • Limit final output to technical epidemiologic reporting terminology.

Output format

  1. Pharmacovigilance Surveillance Summary (max 120 words)
  2. Top Reported Adverse Events Breakdown (Markdown table: Preferred Term, SOC, Total Cases, Serious Cases %, Reporting Velocity Delta %)
  3. Disproportionality and Signal Detection Assessment (Evaluation against {{regulatory_reporting_threshold}})
  4. At-Risk Patient Subgroup Profile (Key findings within {{indication_cohort}})
  5. Risk Management Recommendations (3 specific pharmacovigilance action items)

Self-review

  • Verify that each adverse event category aligns with the definitions in {{seriousness_criteria}}.
  • Confirm that breach status regarding {{regulatory_reporting_threshold}} is unambiguously stated.
  • Check that all 6 template variables are clearly embedded in the analysis context.
AuraScore breakdown
79/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering10/12 · Adequate

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

data-analytics
data-reporting
healthcare-life-sciences
pharmacovigilance
adverse events
drug safety