At Vivli, we recognize that sharing clinical trial data responsibly begins with protecting participants’ privacy. We’ve developed a guide that illustrates how we transform raw trial records into fully anonymized clinical trial datasets suitable for secondary research.

The guide highlights three stages:

• Source Data: Direct observations, lab results, and participant records are captured at investigative sites.
• Pseudonymized/De-Identified Data: Subject IDs replace names, and identifiers are coded, but a key is preserved.
• Anonymized Data: The link to identifiers is permanently broken, and additional safeguards, such as age banding, date shifting, and redacting sensitive narratives, are implemented to reduce the risk of re-identification.

This approach aligns with the Future of Privacy Forum’s A Visual Guide to Practical Data De-Identification, which provides an overview of data identifiability applicable to many industries, such as banking, research, and technology. Vivli’s framework is specific to the clinical trial context, showing the journey from source data to the anonymized datasets available through our platform.

Together, these resources offer complementary perspectives: one illustrating broad principles of de-identification and anonymization, the other mapping the practical pathway within clinical research. Both advance the goal of protecting privacy while enabling data reuse.