Implementing tokenization in clinical research to expand real-world insights

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.

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Publication Details

Journal
Frontiers in Drug Safety and Regulation
Published
2025-02-13
DOI
https://doi.org/10.3389/fdsfr.2025.1519307
Citations
1
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
2.63
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Implementing tokenization in clinical research to expand real-world insights

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article

Implementing tokenization in clinical research to expand real-world insights

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article en
1 citations

Abstract

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.

Frontiers in Drug Safety and RegulationVol. 5
University of California, San Francisco (US), IQVIA (United States) (US), IQ Solutions (US)
Openalex Percentile: Top 14%
Advanced Causal Inference Techniques
2.63
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