Barriers to long-term follow-up in cell and gene therapy

Cell and gene therapy (CGT) programs are committing to 10-15 years of follow-up – often without the infrastructure to support it. FDA guidance for certain gene therapy products recommends long-term follow-up to monitor delayed adverse events and persistent biological activity.

These timelines exceed the traditional operational footprint of most clinical trials and introduce a sustained data collection obligation that must be planned from the outset. The scale and duration of this responsibility expose clear infrastructure gaps across sites and sponsors. This blog explores key barriers to LTFU and how these can be addressed.

Clinical sites are not built for multi-year monitoring

Clinical sites are optimized for active protocol execution. Staffing, budgets, and data systems are typically structured around screening, dosing, and the defined follow-up windows tied to primary and secondary endpoints. Once those milestones are complete, site resources shift toward the next enrolling study.

LTFU requires a fundamentally different operating model. Participants must be tracked across geographies and healthcare systems, contact information must remain current, and safety or health status updates must be captured consistently over many years. Most sites do not have dedicated infrastructure for sustained outreach, engagement continuity, or longitudinal coordination at this scale.

These challenges are amplified in rare and genetically stratified populations, where cohorts are small. In these settings, even a single missed contact can represent a significant loss of clinical insight.

Fragmented workflows undermine data integrity

Even when sites attempt to support LTFU, the operational workflows are often loosely structured. Staff may rely on spreadsheets, manual trackers, email threads, and phone logs. These tools were not designed for regulatory-grade data collection across a 10 to 15 year horizon.

Manual systems create fragmentation. Engagement status may sit in one file, clinical updates in another, and safety reports in separate databases. Reconciling these data streams requires repeated manual intervention. Over time, this increases the risk of incomplete records, inconsistent documentation, and delayed reporting.

From an operational standpoint, this translates into higher administrative burden, increased monitoring costs, and substantial time spent validating datasets before submission or inspection.

Retention risk increases over time

Retention is a longitudinal problem. Patients may relocate, change providers, or no longer be able to commit to follow-up visits. The longer the required follow-up period, the higher the probability of attrition.

In CGT programs, this risk carries disproportionate weight because treated populations are often small. Maintaining engagement cannot rely solely on periodic site visits. Follow-up models that depend entirely on physical attendance introduce friction that compounds over time.

Effective long-term follow-up must integrate decentralized engagement pathways and low-burden participation methods that fit into participants’ daily lives.

Decentralized and patient-centered infrastructure is a requirement

LTFU in CGT requires systems that centralize tracking while decentralizing and simplifying participation in a way that is genuinely patient-centered. Sponsors need structured participant management, standardized communication, and consistent outcome capture that do not depend on manual site-level processes or repeated site visits.

A patient-centered approach recognizes that long-term follow-up is not only a regulatory obligation, but also an experience that patients must be able to sustain over many years. Technology that enables remote check-ins, streamlined data capture, and persistent engagement reduces attrition risk by fitting into patients’ daily lives, not disrupting them. Without this kind of infrastructure, the administrative overhead of long-term monitoring scales faster than the treated population itself, and retention becomes increasingly difficult to maintain.

How Sano addresses long-term follow-up challenges in CGT

Sano Genetics supports precision medicine programs from patient identification through sustained engagement, creating a structured framework that addresses the operational pressure points of LTFU. In addition to reducing site burden, this results in a durable longitudinal dataset.

Sano replaces fragmented spreadsheets and ad hoc outreach with a unified participant management system. Outreach history, testing workflows, counseling interactions, referral status, and engagement metrics are tracked centrally.

Participants who enter a Sano-supported program are onboarded into a persistent engagement environment through the Virtual Waiting Room. This system delivers tailored communications, educational materials, study updates, and personal DNA reports, maintaining connection beyond protocol visits.

In an ultra-rare disease program, Sano maintained engagement with 84% of individuals who tested negative for the targeted gene variant by providing tailored educational content and ongoing updates. Retained individuals represent an additional longitudinal patient data source and a pool of willing, engaged participants who can be re-contacted for future trial opportunities.

Conclusion

Long-term follow-up in CGT is not an administrative afterthought. It is a portfolio-level infrastructure decision and a sustained operational commitment that must align regulatory expectations, data quality standards, and participant experience. Building that infrastructure early determines whether long-term evidence generation remains stable over a decade or becomes progressively more fragile.