Critical Risks of AI Translation for Medical and Pharmaceutical Companies

In our previous article, we explored how biased datasets in AI translation systems pose significant risks across the language services industry. We concluded that for a profession built on linguistic nuance, cultural intelligence, and client trust, the implications are profound.

Now, let’s examine how these risks become even more critical in the medical and pharmaceutical sector—one of the most heavily regulated industries, where translation errors don’t just damage reputations, they threaten patient safety. Here’s why human expertise remains non-negotiable in medical translation.

When a multinational pharmaceutical company deployed AI translation for patient information leaflets across 15 European markets, quality assurance reviewers identified a disturbing pattern. The system consistently rendered “nurse” in feminine grammatical forms and “doctor” in masculine forms across Romance languages—regardless of actual context. More critically, it mishandled low-frequency pharmacological terminology, occasionally creating ambiguity in dosage instructions that could have led to medication errors.

The company immediately halted the rollout, reverting to human-expert translation at significant cost and timeline impact.

This incident illustrates a growing challenge facing medical and pharmaceutical organisations: AI translation tools trained on biased datasets don’t just compromise linguistic quality—they create patient safety risks, regulatory non-compliance, and litigation exposure.

If your organisation produces patient-facing materials, clinical documentation, regulatory submissions, or pharmaceutical labelling in multiple languages, understanding AI bias isn’t a technical consideration. It’s a critical risk management imperative.

Understanding Dataset Bias in Medical AI Translation

Machine translation systems learn patterns from massive collections of previously translated text. When these training datasets are imbalanced—skewed by limited medical terminology exposure, Western-centric clinical perspectives, or inadequate representation of patient demographics—the AI replicates and amplifies those limitations.

For healthcare and pharmaceutical organisations operating under stringent regulatory frameworks, this creates four distinct risk categories.

Risk 1: Patient Safety Compromised by Culturally Inappropriate Medical Translation

The Clinical Risk:

AI systems trained predominantly on Western medical datasets often fail to account for:

• Cultural variations in symptom description and health belief systems
• Gender-neutral language requirements in patient communications
• Culturally sensitive terminology for mental health, reproductive health, and end-of-life care
• Traditional medicine concepts that coexist with Western medical practice in many markets

Case Study: Mental Health Patient Materials

A European hospital network translated mental health screening questionnaires for Arabic-speaking immigrant communities using an AI-powered tool. The system selected clinically accurate Arabic psychiatric terminology that, unknown to the AI, carries severe social stigma in many Arab cultures. Patients avoided completing the forms or provided inaccurate responses to avoid being associated with the stigmatized language.

A human medical translator familiar with both clinical Arabic and cultural context would have immediately selected alternative phrasing that maintains clinical precision while respecting cultural sensitivities.

Patient Impact: Reduced screening participation, inaccurate self-reporting, delayed diagnosis, and barriers to treatment adherence.

Organisational Impact: Compromised clinical outcomes data, potential litigation for inadequate informed consent, and damage to community trust.

Mitigation Requirement: All patient-facing materials require review by medical translators with clinical knowledge and cultural competence in the target population, not just linguistic fluency.

Risk 2: Pharmaceutical Regulatory Compliance Failures

The Regulatory Risk:

Pharmaceutical translation demands absolute precision in technical and regulatory language. AI systems face particular challenges with:

• Low-frequency but critical pharmacological nomenclature (active ingredients, excipients, chemical compounds)
• Regulatory terminology specific to different authorities (EMA, FDA, PMDA, Health Canada)
• Legally mandated warning language that must meet jurisdiction-specific requirements
• Clinical trial protocol terminology where minor mistranslations can invalidate submissions

Case Study: Clinical Trial Protocol Mistranslation

A biotech company used AI-assisted translation for a Phase III clinical trial protocol from English to German. The AI tool, trained primarily on general medical content rather than clinical research documentation, confused “Prüfzentrum” (trial site/location) with “Prüfzeitraum” (trial period/duration) in multiple instances.

The error wasn’t identified until the German ethics committee (Ethikkommission) flagged inconsistencies during regulatory review. The protocol required retranslation and resubmission, delaying trial initiation by seven weeks and affecting patient recruitment timelines.

Financial Impact: Estimated €180,000 in direct costs (retranslation, regulatory resubmission fees, extended site preparation) plus significant opportunity cost from delayed market entry.

Regulatory Impact: Ethics committee questioning of overall quality management systems, additional scrutiny on subsequent submissions.

Mitigation Requirement: Domain-specific translation memory systems built from validated pharmaceutical corpora, terminology databases curated by pharmaceutical linguists, and mandatory human review by subject matter experts for all regulatory submissions.

Risk 3: Patient Information and Labelling Errors

The Compliance and Safety Risk:

Pharmaceutical labelling, patient information leaflets, and instructions for use are among the most highly regulated translation deliverables. Errors can result in:

• Medication administration mistakes
• Failure to recognise contraindications or drug interactions
• Inadequate adverse event reporting
• Non-compliance with labelling regulations in different markets

Case Study: Dosage Instruction Ambiguity

An AI tool translated “take one tablet twice daily” from English to Spanish as “tomar una tableta dos veces diarias“, instead of “tome un comprimido dos veces al día“. The former may be grammatically correct but translated too literally, and potentially ambiguous. In some Spanish-speaking regions it could be interpreted as “take one or two tablets daily.”

The ambiguity was identified during pharmacovigilance review after three patients contacted the medical information helpline for clarification.

Patient Safety Impact: Potential for both underdosing (reduced therapeutic efficacy) and overdosing (increased adverse event risk).

Regulatory Impact: Potential for regulatory action, mandatory labelling corrections across markets, and enhanced post-market surveillance requirements.

Quality Management Impact: CAPA (Corrective and Preventive Action) investigation, revision of translation vendor qualification criteria.

Mitigation Requirement: Pharmaceutical labelling requires specialist medical translators with regulatory expertise, back-translation verification, and independent linguistic quality control before regulatory submission.

Risk 4: Clinical Communication Barriers with Underrepresented Patient Populations

The Health Equity Risk:

AI translation systems demonstrate measurably lower accuracy for:

• Minority languages and regional dialects
• Non-standard accents in speech-to-text medical interpreting applications
• Patient populations underrepresented in training datasets

This creates health equity concerns and accessibility barriers for vulnerable populations.

Case Study: Telehealth Interpreting Accuracy Gap

A multi-site healthcare system implemented AI-powered real-time interpreting for telehealth consultations. Internal quality audits revealed that patients speaking South Asian English varieties (in India, Pakistan, Bangladesh, Sri Lanka, and Nepal) experienced 34% more transcription errors than patients speaking British, American or Australian English varieties.

For medical consultations, this translated to:

• Missed or misrecorded symptom descriptions
• Incorrect medication names captured in electronic health records
• Misunderstood patient questions requiring repeat clarification

Clinical Impact: Diagnostic delays, inappropriate treatment plans, and reduced patient satisfaction scores among minority communities.

Risk Management Impact: Potential discrimination claims, health equity compliance concerns, and failure to meet meaningful access standards.

Mitigation Requirement: Human medical interpreters for clinical consultations, particularly for diagnostically complex cases, and continuous quality monitoring of AI interpreting systems with demographic disaggregation.

Risk 5: Clinical Trial Diversity and Informed Consent

The Research Ethics Risk:

Regulatory authorities worldwide are demanding greater diversity in clinical trial populations. This requires:

• Informed consent documents in multiple languages and literacy levels
• Patient-reported outcome (PRO) measures validated across cultures
• Recruitment materials that resonate with diverse communities

AI translation bias can undermine trial diversity by:

• Producing consent forms that are technically accurate but incomprehensible to patients with limited health literacy
• Failing to adapt PRO instruments appropriately for cultural context
• Creating recruitment materials that don’t resonate with target communities

Case Study: Informed Consent Readability

A pharmaceutical company translated informed consent documents for a rare disease trial targeting both university hospital populations and community clinics serving immigrant populations. The AI-generated translations maintained scientific precision but produced text at a reading level inappropriate for patients with limited formal education in the target language.

Community clinic investigators reported that potential participants were intimidated by the complex language and declined participation at higher rates than anticipated.

Trial Impact: Slower than projected recruitment, reduced population diversity, and potential questions about generalisability of trial results.

Ethical Impact: Barriers to informed consent for vulnerable populations, raising questions about research ethics compliance.

Mitigation Requirement: Informed consent translation requires not just linguistic accuracy but readability testing and cultural adaptation by medical translators with health literacy expertise.

The Evolving Regulatory Landscape for AI in Medical Translation

Healthcare and pharmaceutical organisations face increasing scrutiny around AI deployment:

EU AI Act (2024-2025 Implementation):

• Medical devices incorporating AI (including translation functions) face enhanced requirements
• High-risk AI systems require conformity assessments and quality management documentation
• Transparency obligations regarding AI training data and bias mitigation

FDA Guidance on AI/ML in Medical Devices:

• Software as a Medical Device (SaMD) that includes translation or communication functions must demonstrate validation
• Predetermined change control plans must address translation quality degradation

ISO Standards Evolution:

• ISO 17100:2015 (Translation Services) requires human translation for content where errors could cause harm
• ISO 18587:2017 (Post-editing of MT) specifies full human review for high-risk content
• Emerging standards for AI in healthcare will likely include translation quality requirements

Your Compliance Obligations:

When AI-assisted translation is used in your organisation, regulatory authorities and auditors may require:

1. Documentation of AI Tool Validation: Evidence that MT systems have been tested for accuracy in your specific medical/pharmaceutical domain
2. Training Data Provenance: Transparency about what datasets power your AI translation tools and whether they include appropriate medical content
3. Human Oversight Protocols: Clearly defined processes specifying when and how human experts review AI output
4. Quality Metrics: Demonstrable quality assurance processes with defined acceptance criteria
5. Bias Assessment: Evidence of bias testing across your language pairs and patient populations
6. Accountability Frameworks: Clear assignment of responsibility when AI-generated translations cause patient harm or regulatory non-compliance

Strategic Questions for Medical and Pharmaceutical Organisation

For Quality Assurance and Regulatory Affairs:

• Can we demonstrate to auditors that our translation processes meet ISO 17100 requirements for medical content?
• Do we have documented evidence of AI tool validation for our therapeutic areas and document types?
• Are our translation vendors contractually liable for AI-assisted translation errors in regulatory submissions?

For Patient Safety and Pharmacovigilance:

• How do we ensure that AI-translated patient materials don’t create medication error risks?
• What processes verify that adverse event reporting in multiple languages isn’t compromised by AI translation bias?
• Have we assessed AI translation accuracy for our priority patient populations, including underrepresented groups?

For Clinical Operations:

• Are informed consent documents translated with appropriate attention to health literacy and cultural context?
• Do our clinical trial translations support diverse patient recruitment or create unintended barriers?
• What quality controls exist for patient-reported outcome measures used across multiple language versions?

For Procurement and Vendor Management:

• What questions should we ask language service providers about their AI deployment and bias mitigation?
• How do we evaluate whether a vendor’s AI tools are appropriate for pharmaceutical regulatory content?
• What service level agreements and liability provisions should we require for high-risk medical translation?

If you cannot confidently answer these questions, your organisation may have gaps in translation risk management.

Our Approach to Medical and Pharmaceutical Translation

We recognise that for healthcare and pharmaceutical organisations, translation is inseparable from patient safety, regulatory compliance, and research integrity.

Our pharmaceutical and medical translation services combine:

Specialist Expertise:

• Medical translators with clinical backgrounds (physicians, pharmacists, nurses, medical researchers)
• Pharmaceutical regulatory specialists familiar with EMA, FDA, and global authority requirements
• Subject matter experts in specific therapeutic areas

Domain-Specific Infrastructure:

• Validated terminology databases built specifically for pharmaceutical and medical content
• Translation memory systems curated from regulatory-approved documentation
• Quality assurance workflows that meet ISO 17100 and ISO 18587 standards

Responsible AI Integration:

• AI tools deployed only for appropriate content types (not for patient-safety critical materials)
• Continuous quality monitoring with statistical analysis of AI output accuracy
• Mandatory human expert review for all regulatory submissions, patient-facing materials, and clinical documentation
• Transparent documentation of AI tool capabilities and limitations

Cultural and Linguistic Intelligence:

• Cultural adaptation that goes beyond literal translation to ensure patient comprehension
• Health literacy assessment and plain language expertise for patient materials
• Demographic representation testing to identify potential bias in patient communications

Regulatory Compliance Support:

• Documentation packages for regulatory submissions and audits
• Change control processes for translation updates
• Traceability and version control meeting GxP requirements

Take Action: Assess Your Translation Risk Profile

If your organisation develops pharmaceuticals, medical devices, or healthcare services with global reach, we invite you to evaluate your current translation processes.

My Language Hub: Specialist medical and pharmaceutical translation services for organisations that prioritise patient safety, regulatory compliance, and clinical excellence.

ISO 17100 Certified | Medical Translation Experts | Regulatory Submission Specialists