Implementing tokenization in clinical research to expand real-world insights

Area of Science:

• Clinical Research
• Data Science
• Health Informatics

Background:

• Growing interest in using real-world data (RWD) for clinical research, particularly for treatment safety and effectiveness.
• Enriched studies combining primary and secondary RWD are increasingly common, necessitating advanced data linkage methodologies.

Purpose of the Study:

• To explore key aspects of implementing tokenization in the United States (US) for linking RWD with primary data.
• To define relevant terminology and discuss appropriate study designs and RWD sources for tokenization.
• To highlight advantages and considerations for stakeholders in generating real-world evidence using tokenization.

Main Methods:

• Exploration of tokenization as a tool for linking secondary RWD with primary study data.
• Discussion of operational considerations for implementing tokenization in study set-up.
• Review of study designs and RWD sources suitable for tokenization.

Main Results:

• Tokenization is a key enabler for linking disparate data sources in enriched studies.
• Key aspects for operationalizing tokenization in the US are identified, addressing overlooked considerations.
• Advantages and considerations for study stakeholders are highlighted to enhance real-world evidence generation.

Conclusions:

• Tokenization is a vital methodology for successful enriched studies requiring data linkage.
• Proper implementation and understanding of tokenization are essential for maximizing the value of RWD in clinical research.
• Case studies illustrate scenarios where tokenization is a suitable fit for achieving study objectives.