# Fortune 500 Case Study Validation: Pfizer
# Schema: ../../contracts/case-study-validation.schema.yaml

case_study: pfizer
industry: Healthcare/Biotech
fortune_rank: 42

jtbd: "When I design a new trial, I need data models that automatically comply with FDA CDISC requirements, so that I can accelerate submissions and reduce compliance risk."

scale_requirements:
  clinical_studies: 500
  data_domains: 50
  submissions_per_year: 20
  latency_slo: "<10min for complete trial structure"

required_commands:
  - command: "ggen ontology extract"
    purpose: "Extract entities from CDISC ontologies"
    criticality: P1
    current_support: pending
    gaps: []

  - command: "ggen graph load"
    purpose: "Load CDISC standards into graph"
    criticality: P1
    current_support: pending
    gaps: []

  - command: "ggen template generate-tree"
    purpose: "Generate complete trial data structure"
    criticality: P1
    current_support: pending
    gaps: []

  - command: "ggen ontology validate"
    purpose: "Validate CDISC compliance"
    criticality: P1
    current_support: pending
    gaps: []

validation_status: pending
validated_date: null
validator: claude-code

test_scenarios:
  - scenario: "CDISC-compliant trial structure"
    steps:
      - "ggen graph load cdisc-sdtm.ttl"
      - "ggen ontology extract --namespace http://cdisc.org/sdtm#"
      - "ggen template generate-tree --template trial-structure.tmpl"
      - "ggen ontology validate schema.json --strict"
    expected: "Complete trial structure passing FDA validation"
    actual: pending

  - scenario: "Study-specific extension handling"
    steps:
      - "ggen ontology extract cdisc-base.ttl"
      - "ggen template generate --template extension.tmpl --var study=PHASE3-001"
    expected: "Extensions cleanly separated from base CDISC"
    actual: pending

gaps: []

recommendations: []

notes: |
  Pfizer case study focuses on FDA CDISC compliance automation.
  Key concerns: regulatory compliance, traceability, data integrity.
  Industry pattern: compliance-driven with healthcare-specific requirements.
