Healthcare & Life Sciences¶

Medical-grade translation accuracy. Clinical trials, patient records, pharmaceutical documentation with full regulatory compliance and patient safety focus.

Patient Data Protection

All healthcare translations are processed in EU only, with GDPR Article 9 (special category data) compliance. PII detection and redaction available.

EuroVoc Domains Covered¶

Domain	Coverage
28 Social Questions	Healthcare systems, patient care
36 Science	Medical research, clinical trials
60 Agri-Foodstuffs	Food safety, nutrition
52 Environment	Environmental health
12 Law	Healthcare regulations

Document Types¶

Clinical Trial Documents¶

from pauhu import Pauhu

pauhu = Pauhu(
    api_key="pk_live_...",
    domain="36-science",
    compliance=["gdpr-article-9", "ich-gcp"]
)

# Translate informed consent form
result = pauhu.translate_document(
    file="informed-consent-form.docx",
    source="en",
    target=["fi", "sv", "de"],
    document_type="clinical_trial",
    regulatory={
        "ich_gcp": True,          # ICH-GCP compliant
        "ema_requirements": True,  # EMA format
        "preserve_formatting": True
    }
)

# Includes:
# - Medical terminology verified
# - Risk/benefit language preserved
# - Patient-friendly language maintained

Patient Records (EHR)¶

# Translate with PII protection
result = pauhu.translate(
    text="Patient: John Doe, DOB: 1985-03-15...",
    source="en",
    target="fi",
    pii_handling={
        "detect": True,        # Detect PII automatically
        "redact": False,       # Or redact before translation
        "pseudonymize": True,  # Replace with tokens
        "audit_log": True      # Log all PII handling
    }
)

# PII detected and handled:
# - Names → [PATIENT_NAME]
# - DOB → [DATE_OF_BIRTH]
# - SSN → [NATIONAL_ID]

Pharmaceutical Documentation¶

# Translate product information leaflet
result = pauhu.translate_document(
    file="patient-information-leaflet.pdf",
    source="en",
    target="fi",
    document_type="pharmaceutical",
    regulatory={
        "ema_pil": True,       # EMA PIL format
        "qrd_template": True,  # QRD template compliance
        "drug_names": "preserve"  # Keep INN names
    },
    term_base="pharma-ema"
)

# Drug name handling:
# - INN names preserved (paracetamol → parasetamoli)
# - Brand names marked
# - Dosage forms standardized

Medical Terminology¶

Pre-Loaded Term Bases¶

Term Base	Terms	Specialty
`medical-general`	100K+	General medicine
`medical-oncology`	25K+	Cancer treatment
`medical-cardiology`	20K+	Heart/cardiovascular
`medical-neurology`	18K+	Nervous system
`pharma-ema`	50K+	EMA terminology
`snomed-ct`	350K+	SNOMED CT concepts
`icd-11`	55K+	ICD-11 codes

# Configure medical terminology
pauhu.set_term_bases([
    "medical-general",
    "medical-oncology",
    "pharma-ema",
    "snomed-ct"
])

# Example translations:
# "myocardial infarction" → "sydäninfarkti"
# "dyspnea" → "hengenahdistus"
# "benign neoplasm" → "hyvänlaatuinen kasvain"

Custom Hospital Terminology¶

# Upload hospital-specific terminology
pauhu.term_base.upload(
    name="hus-terminology",  # HUS (Helsinki University Hospital)
    file="hus-medical-terms.tbx",
    domain="28-social",
    specialty="hospital",
    visibility="organization"
)

Compliance Features¶

# Special category data handling
pauhu = Pauhu(
    api_key="pk_live_...",
    compliance={
        "gdpr_article_9": True,
        "legal_basis": "explicit_consent",  # Or "vital_interests"
        "data_minimization": True,
        "encryption": "protected",
        "retention": "session_only"  # Delete after translation
    }
)

HIPAA Alignment (US Operations)¶

# For US healthcare clients
pauhu = Pauhu(
    api_key="pk_live_...",
    compliance={
        "hipaa_alignment": True,
        "phi_detection": True,
        "baa_available": True  # Business Associate Agreement
    }
)

Clinical Trial Regulations¶

Regulation	Pauhu Compliance
ICH-GCP	Audit trails, version control
EU CTR	Multi-language support, EMA format
FDA 21 CFR Part 11	Electronic records compliance
EMA Guidelines	QRD templates, XEVMPD

PII Detection & Protection¶

Automatic PII Detection¶

# Detect medical PII automatically
result = pauhu.analyze_pii(
    text="Patient John Smith, SSN 123-45-6789, diagnosed with...",
    categories=["medical", "personal"]
)

# Detected PII:
# [
#   {"type": "PERSON_NAME", "value": "John Smith", "position": [8, 18]},
#   {"type": "SSN", "value": "123-45-6789", "position": [25, 36]},
# ]

PII Redaction Options¶

# Option 1: Redact before translation
result = pauhu.translate(
    text="Patient John Smith...",
    target="fi",
    pii_handling="redact"
)
# Result: "Potilas [NIMI]..."

# Option 2: Pseudonymize (reversible)
result = pauhu.translate(
    text="Patient John Smith...",
    target="fi",
    pii_handling="pseudonymize"
)
# Result: "Potilas P_001..."
# Mapping stored securely for restoration

# Option 3: Encrypt in place
result = pauhu.translate(
    text="Patient John Smith...",
    target="fi",
    pii_handling="encrypt"
)
# PII encrypted, translation preserved

Quality Assurance¶

Medical QA Rules¶

Check	Description
Drug names	INN names verified against EMA list
Dosages	Numeric values preserved exactly
Units	Medical units correct (mg, mL, etc.)
Warnings	Safety warnings translated accurately
Contraindications	Contraindication terms verified

# Enable strict medical QA
result = pauhu.translate(
    text="Take 500mg paracetamol every 6 hours...",
    target="fi",
    qa_rules=[
        "medical-drug-names",
        "medical-dosages",
        "medical-units",
        "medical-warnings"
    ],
    fail_on_qa_error=True
)

# QA checks:
# ✓ "500mg" preserved exactly
# ✓ "paracetamol" → "parasetamoli" (verified INN)
# ✓ "every 6 hours" → "6 tunnin välein" (correct interval)

Integration Patterns¶

EHR Integration (Epic, Cerner)¶

# Epic FHIR integration
from fhir.resources import Patient, DocumentReference

@app.route("/fhir/translate", methods=["POST"])
def translate_fhir_document():
    doc_ref = DocumentReference.parse_raw(request.data)

    # Get document content
    content = doc_ref.content[0].attachment.data

    # Translate with PII protection
    translation = pauhu.translate(
        text=content,
        source="en",
        target="fi",
        domain="28-social",
        pii_handling="pseudonymize"
    )

    # Create translated DocumentReference
    translated_ref = doc_ref.copy()
    translated_ref.content[0].attachment.data = translation["text"]
    translated_ref.content[0].attachment.language = "fi"

    return translated_ref.json()

Clinical Trial Management¶

# Translate trial documents with version control
from pauhu import Pauhu

pauhu = Pauhu(api_key="pk_live_...")

def translate_trial_document(doc, target_languages: list):
    """Translate clinical trial document to multiple languages."""

    translations = {}
    for lang in target_languages:
        result = pauhu.translate_document(
            file=doc.content,
            source="en",
            target=lang,
            document_type="clinical_trial",
            version=doc.version,  # Track version
            audit={
                "trial_id": doc.trial_id,
                "document_type": doc.type,
                "version": doc.version
            }
        )

        translations[lang] = {
            "content": result["translation"],
            "audit_id": result["audit_id"],
            "qa_score": result["qa_score"]
        }

    return translations

Pricing for Healthcare¶

Hospital/Health System¶

Size	Monthly	Features
Small Hospital	€900	10 users, 500K words
Regional System	€2,500	50 users, 2M words
National System	€9,000	Unlimited

Pharmaceutical¶

Tier	Monthly	Features
Biotech	€2,500	20 users, EMA terminology
Mid Pharma	€4,500	100 users, clinical trial support
Big Pharma	Custom	Enterprise, all specialties

Included: - ✅ GDPR Article 9 compliance - ✅ PII detection/redaction - ✅ Medical term bases - ✅ EMA/FDA formats - ✅ Audit trails - ✅ Version control

Case Study: Nordic Pharma Company¶

Clinical Trial Documentation (Phase III)¶

Before Pauhu: - Translation agency: €800K/year - 23 EU languages required - 6-week turnaround per language - Terminology inconsistencies

After Pauhu: - Pauhu Enterprise: €108K/year - Same-week turnaround - 99.2% terminology consistency - Savings: €692K/year (87%)

Regulatory Compliance: - EMA submission accepted - ICH-GCP audit passed - 21 CFR Part 11 compliant

Quick Start¶

1. Configure for Healthcare¶

from pauhu import Pauhu

pauhu = Pauhu(
    api_key="pk_live_...",
    domain="28-social",
    compliance=["gdpr-article-9"],
    pii_protection=True
)

2. Set Medical Term Bases¶

pauhu.set_term_bases([
    "medical-general",
    "pharma-ema",
    "snomed-ct"
])

3. Translate with PII Protection¶

result = pauhu.translate(
    text="Patient presents with acute symptoms...",
    target="fi",
    pii_handling="pseudonymize"
)

Regulatory-Ready

Pauhu supports EMA, FDA, and ICH-GCP requirements. Clinical trial document translation with full audit trail.