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PERSPECTIVE article

Front. Drug Saf. Regul.
Sec. Advanced Methods in Pharmacovigilance and Pharmacoepidemiology
Volume 5 - 2025 | doi: 10.3389/fdsfr.2025.1519307
This article is part of the Research Topic Challenges and Opportunities of Tokenization to Enhance the Benefit-Risk Assessment of Medicines View all articles

Tokenization implementation in clinical research to expand real-world insights

Provisionally accepted
Chelsea Walters Chelsea Walters 1*Crystal S Langlais Crystal S Langlais 2,3Eva E Oakkar Eva E Oakkar 4Wilhelmina E Hoogendoorn Wilhelmina E Hoogendoorn 5James Coutcher James Coutcher 4Mui Van Zandt Mui Van Zandt 6
  • 1 IQVIA, Emerging Methods and Solutions, Wayne, United States
  • 2 IQVIA, Epidemiology and Database Studies, Durham, United States
  • 3 University of California, San Francisco, San Francisco, United States
  • 4 IQVIA, Emerging Methods and Solutions, Durham, United States
  • 5 IQVIA, Epidemiology and Database Studies, Amsterdam, Netherlands
  • 6 IQVIA, VP & General Manager, Data Strategy Access and Enablement, Wayne, United States

The final, formatted version of the article will be published soon.

    Interest in leveraging real-world data (RWD) to support clinical research is increasing, including studies to further characterize safety and effectiveness of new treatments. Such studies often require a combination of primary, study-specific data, with secondary, existing RWD. So-called enriched studies are becoming more common but require tailored methodologies that facilitate linkage across data sources. Tokenization has emerged as a key tool in the United States (US) to enable the linkage of secondary data with primary data, although key considerations to operationalize tokenization are often overlooked during study set-up. This article aims to explore key aspects for implementing tokenization in the US and to define relevant terminology. Appropriate study designs and RWD sources to leverage this tool are also discussed and advantages and considerations for study stakeholders to enhance possibilities to generate real-world evidence are highlighted. The article concludes with a description of case studies where tokenization is a suitable fit to fulfill study goals.

    Keywords: tokenization, de-identification, data linkage, Data privacy, Real-world data, Real-world evidence

    Received: 29 Oct 2024; Accepted: 24 Jan 2025.

    Copyright: © 2025 Walters, Langlais, Oakkar, Hoogendoorn, Coutcher and Van Zandt. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Chelsea Walters, IQVIA, Emerging Methods and Solutions, Wayne, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.