Tokenization can make a patient visible in a dataset without making that patient truly knowable over time. It gives you an outline, not the full story. And in clinical trials, the full story is the whole point.

Most pharmaceutical organizations have invested meaningfully in tokenization. That investment was rational. Tokenization solved a real problem: it connected fragmented data and made linkage possible at scale. For a time, it looked like the infrastructure question had been answered.

Unfortunately, in clinical trial follow-up, it hadn't.

What tokenization was built to do — connect records across sources — is not the same thing that clinical trial follow-up requires. Trial follow-up requires the ability to follow patients over time and capture outcomes with fidelity. Both rarely preserve the flexibility to answer questions that weren't fully defined on day one. Those are different problems. And the gap between them is where development programs quietly lose value.

The industry doesn't have a tokenization problem. It has an optionality problem that tokenization cannot solve.

‍

Where tokenization falls short — and what it really costs

Consider a scenario that is increasingly familiar across clinical development.

A sponsor completes a pivotal trial in a rare disease population. The study closes, the database is locked, and the program moves forward. Two years later, a commercial or regulatory question emerges about long-term durability. It’s exactly the kind of follow-up evidence that should be retrievable from a well-preserved cohort.

The team then runs an overlap report against a claims dataset, and ninety percent of trial patients have a match. That sounds like preserved optionality. What it actually means is that 90% of patients exist somewhere in the dataset — not that they have records from the right time period, the right clinical depth, or enough detail to actually ascertain the endpoints that matter. The linked dataset turns out to be largely unusable. Records exist, but not from the relevant time window.

This is not a failure of intent: the infrastructure did what it was designed to do. The problem is that it was designed for episodic linkage, not longevity or completeness.

"This isn't a hypothetical. The pattern is one I've seen repeatedly. By the time teams realize the cohort has effectively dissolved, the window to do anything about it has already closed,” says Dan Drozd, MD, MSc, Chief Medical Officer at PicnicHealth.

The evidence infrastructure established at the start of a trial determines what will be knowable for the life of that program. Organizations that treat this as a technical procurement decision are making a strategic mistake.

‍

What comes next: patient-anchored data 

What that scenario required and what tokenization could not provide is a persistent, patient-anchored foundation built to survive the distance between study close and the questions that come after. After you’ve invested so much in identifying and recruiting participants to your trial, why let them slip away?

The next category in trial evidence infrastructure is ThumbPrint: patient-anchored data product that secures consent for follow-up from the trial participant before the trial closes, preserving cohort integrity and program optionality over time.

"Starting with the patient is not a subtle distinction. It's the difference between an evidence foundation that holds up over time and one that quietly degrades the moment the study closes,” says Dr. Drozd.

That shift changes what is possible across four dimensions that tokenization alone consistently struggles to deliver:

• Cohort preservation. Maintains continuity with the real trial population over time, not just the subset that remains linkable as match rates degrade.
• Endpoint fidelity. Captures clinically meaningful longitudinal data with the depth and context required for robust evidence generation and greater regulatory confidence.
• Durable long-term follow-up. Builds persistent visibility beyond the initial study window without relying on episodic linkage exercises that introduce gaps when continuity matters most.
• Re-engagement and program flexibility. Preserves the ability to return to patients and extend the value of the original trial investment as new scientific and commercial questions emerge.

ThumbPrint is not a cosmetic improvement to existing data plumbing. It is a new layer of infrastructure for evidence strategy that is built for demands tokenization was never designed to meet.

‍

Why this matters now 

The pressure on pharmaceutical development programs is not easing. Trials are only getting more expensive. Timelines are tighter. Regulatory and commercial decisions increasingly depend on long-term, high-integrity evidence. And the populations that matter most strategically — rare disease cohorts, underrepresented groups, complex chronic conditions — are often the ones where fragmented, token-linked data performs the worst.

The next generation of trial design will not be defined by how many data sources can be linked. It will be defined by how well sponsors preserve patient-level continuity, evidence quality, and future adaptability from the moment a participant enters a study.

The organizations that get this right first will have a compounding advantage. Every trial becomes a more durable asset. Every enrolled patient carries more long-term optionality. Every program retains more of its original value.

The decisions that determine that advantage are not made at data lock. They are made at trial design — which means the window to get this right is earlier than most organizations assume, and narrower than most are prepared for. 

‍

A new layer, not a replacement 

Utilizing ThumbPrint does not require abandoning existing tokenization investments. Tokenization remains useful infrastructure in many contexts, and most organizations have meaningful commitments to token-based systems that are not going away.

The opportunity ThumbPrint presents is to complement those investments with a patient-anchored data layer that addresses what tokenization leaves behind: a layer that starts with consent, anchors to the real trial participant, preserves cohort integrity, protects endpoint fidelity, and keeps future evidence pathways open in ways token-linked data alone cannot guarantee.

Tokenization helped the industry connect data.

But connection is not continuity. Linkage is not fidelity. And a connected dataset is not the same thing as a durable, trial-anchored evidence asset built to answer questions that have not yet been asked.

Learn more about how ThumbPrint can preserve optionality for future evidence needs.