Blur

Blur is a standalone SaaS clinical trial transparency platform developed by Instem for de-identifying patient information and supporting regulatory compliance in life sciences research. Designed for non-programmers, it combines natural language processing, automated anonymization, role-based workflows, and simulation-based risk assessment to protect patient health information while preserving data usability. Its modular components—Blur Data, Blur Risk, and Blur CSR—enable organizations to de-identify clinical datasets, calculate re-identification risk, and anonymize Clinical Study Reports for regulatory submissions to agencies such as the FDA, EMA, Health Canada, and under GDPR requirements. The web-based interface centralizes de-identification tasks, supports bulk processing, audit logs, role assignments, and export of submission-ready reports, helping research teams improve efficiency and reduce manual effort. Customer case studies highlight its ability to process complex legacy clinical trial data with large numbers of variables while maintaining compliance and enabling secure data sharing. Users generally value its automation, strong regulatory focus, ease of adoption, and ability to streamline transparency workflows, although organizations with highly specialized workflows may require initial configuration to align with internal regulatory processes.