As pharmaceutical companies expand globally, litigation risk follows suit. From product liability to patent disputes, legal teams must now manage discovery across multiple jurisdictions—each with its own data laws, regulatory expectations, and litigation culture. In this landscape, London has emerged as a pivotal venue for global pharma disputes, and centralised, AI-driven review environments are becoming essential to manage the complexity.
London’s Role in Global Pharma Litigation and Discovery
The UK—particularly London—continues to be a preferred jurisdiction for resolving international pharmaceutical disputes. Its reputation for judicial independence, procedural transparency, and robust case law makes it attractive for cross-border litigation. The High Court of England and Wales regularly hears cases involving multinational pharmaceutical companies, especially those related to IP, product liability, and regulatory enforcement.Moreover, London’s legal infrastructure supports coordination with EU and US proceedings. While the UK is no longer part of the Unified Patent Court, its courts remain influential in interpreting European patent law and enforcing global IP rights.
The GDPR Challenge in Cross-Border Discovery
One of the most formidable obstacles in multi-jurisdictional discovery is data protection. The General Data Protection Regulation (GDPR) imposes strict rules on the transfer of personal data outside the European Economic Area (EEA). For pharmaceutical companies, this includes:
-
Patient Data: From clinical trials, adverse event reports, and pharmacovigilance systems.
-
Employee Communications: Emails, chat logs, and internal reports.
-
Third-Party Records: Vendor and investigator correspondence.
Transferring such data to jurisdictions with less stringent privacy laws—such as the US—requires careful legal justification, often through Standard Contractual Clauses (SCCs) or adequacy decisions. Failure to comply can result in regulatory fines, reputational damage, and litigation setbacks.
Coordinating Multi-Jurisdictional Review with GDPR-Safe Workflows
Cross-border litigation often involves simultaneous proceedings in multiple countries. This requires:
-
Jurisdictional Expertise: Understanding local discovery rules, privilege standards, and production formats.
-
Language Capabilities: Reviewing documents in multiple languages with consistent coding standards.
-
Time Zone Management: Coordinating teams across continents to meet court deadlines.
Legal teams must also navigate conflicting obligations—such as broad US discovery rules versus EU data minimisation principles. Without a unified strategy, discovery can become fragmented, inconsistent, and legally vulnerable.
Centralised, AI-Driven Review Environments: The New Standard
To meet these challenges, pharmaceutical companies are turning to centralised review platforms powered by AI. These environments offer:
- Unified Workflows: One platform for all jurisdictions, ensuring consistency in privilege, responsiveness, and confidentiality coding.
- AI-Powered Prioritisation: Machine learning models that rank documents by relevance, reducing manual review burden.
- Privacy-Aware Filters: Tools that flag personal data and apply jurisdiction-specific redactions automatically.
Such platforms also support audit trails, quality control protocols, and real-time collaboration—critical for defensibility and efficiency. In high-stakes cross-border disputes, they enable legal teams to respond swiftly, accurately, and in full compliance with global data laws.
Final Thoughts
Cross-border litigation in pharma is no longer the exception—it’s the norm. Legal leaders must embrace technology and strategy to manage discovery across jurisdictions. At TrustArray, we help pharmaceutical companies navigate multi-jurisdictional discovery with AI-driven review environments tailored to the demands of global litigation.
Sources:
Stevens & Bolton: Pharma Disputes in the UKChambers Global: Life Sciences & Pharmaceutical Sector (International & Cross-Border)
CDS Legal: Complexities of International Data Sources and Data Protection Laws