Why site selection is failing rare disease trials and what to do differently

Rare disease trials operate under structural constraints that make site selection more important than in common disease programs. Patient populations are small, diagnosis often depends on genomic testing, and protocols frequently require specialized assessments and long-term follow-up.

Despite this, many sponsors still begin feasibility by identifying sites and estimating potential patient pools based on epidemiology or investigator-reported counts. When feasibility starts this way, sponsors inherit uncertainty about whether eligible patients can actually be identified, screened correctly, and retained through the study.

In rare disease trials, that uncertainty quickly becomes operational risk. A single underperforming site can delay enrollment timelines, introduce variability in endpoint assessments, and reduce the effective sample size available for analysis.

A more reliable approach begins with patient-first feasibility. Instead of starting with sites and estimating potential patients, this model begins with identified individuals who meet genotype and phenotype criteria and then maps the operational capacity of sites to support those patients.

This shift changes how sponsors evaluate trial sites. Instead of relying primarily on feasibility questionnaires, sponsors must assess whether sites can support the full pathway from patient identification through long-term follow-up.

The following criteria illustrate what this patient-first approach requires sponsors to evaluate when selecting clinical trial sites for rare and genetic disease studies.

Verified patient access and diagnostic confirmation

The most important factor in rare disease trial feasibility is access to confirmed patients who match the protocol’s inclusion criteria.

Many sponsors rely on epidemiology estimates or site-reported patient counts when planning enrollment. This often leads to an overestimation of the number of patients who are currently reachable and eligible.

A more reliable approach is patient-first feasibility. This model begins with identified individuals who meet genotype and phenotype criteria and then maps the operational capacity of sites to support those patients.

Sponsors should confirm that potential sites can:

• Actively manage the target patient population
• Identify patients that meet genetic or phenotypic inclusion criteria
• Coordinate genomic testing and variant interpretation
• Manage referrals across regional or national networks

Investigator expertise and operational stability

Patient-first feasibility also requires evaluating whether sites can deliver the specialized care coordination rare disease trials demand. Rare disease trials often require nuanced clinical assessments and specialized care coordination. Investigator expertise in the disease area strongly influences trial performance.

Sponsors should evaluate whether investigators have:

• Direct experience leading interventional trials in the disease area
• Familiarity with disease progression markers and clinical endpoints
• Access to multidisciplinary specialists involved in routine patient care

Operational stability is also critical. Rare disease trials can extend over several years, particularly for gene therapy programs that require long term safety monitoring.

Sites should demonstrate:

• Stable coordinator staffing
• Cross trained teams to prevent disruption during turnover
• Experience managing high burden visit schedules

These factors influence both retention and data continuity.

Endpoint execution and data integrity

When patient populations are small, variability across sites has a disproportionate impact on statistical power.

If endpoint assessments are inconsistent, the resulting variability can weaken the estimated treatment effect and require additional cohorts or longer trials.

A patient-first site strategy therefore requires evaluating operational endpoint fidelity before activation. Key questions include:

• Are clinicians experienced with the protocol required assessments?
• Is there backup coverage if key staff are unavailable?
• Does imaging infrastructure meet protocol standards?
• Are specialized procedures routinely performed at the site?

Data governance also plays an important role. Sites with strong documentation systems, reliable EMR access, and predictable data entry timelines reduce the risk of delays and protocol deviations.

Therapy specific infrastructure for advanced therapies and gene therapy

Advanced therapies introduce additional operational requirements for trial sites. Gene therapy trials in particular require infrastructure that goes beyond traditional clinical research operations. Investigational product handling must meet strict chain of custody and temperature control standards. Administration may require specialized infusion facilities and emergency response capabilities.

Sites must also support long-term follow-up obligations.

This includes the ability to:

• Maintain long term contact with participants
• Coordinate periodic safety assessments
• Track delayed adverse events
• Manage care transitions if participants relocate

These capabilities should be evaluated during feasibility rather than after site activation.

Patient burden, access equity, and retention

Participants in rare disease trials often travel long distances and depend on caregiver support. Visit intensity and logistical complexity can affect retention. Sites with experience coordinating complex care pathways are better positioned to maintain engagement throughout the study.

High performing sites typically provide:

• Coordinated scheduling that consolidates assessments into single visits
• Flexible appointment options
• Communication support for patients and families

Hybrid or decentralized components can reduce travel burden when implemented with appropriate oversight. Retention planning should be considered a core design parameter in rare disease trials.

Regulatory and study start up performance

Genetic trials often involve complex consent processes that include genetic testing, data sharing, biospecimen storage, and recontact permissions.

Sites must demonstrate experience managing these requirements, including pediatric assent and genetic counseling where relevant.

Sponsors should also evaluate operational metrics such as:

• Ethics review timelines
• Contract negotiation cycle time
• Historical start up performance

A site that activates slowly may not contribute meaningfully to enrollment if recruitment timelines are compressed. Historical performance is usually a better predictor than projected timelines.

How patient first feasibility improves site strategy

Site selection in rare and genetic trials should be treated as the execution layer of a precision patient strategy.

When feasibility begins with site reported patient counts, sponsors inherit uncertainty that can affect enrollment and endpoint quality. When feasibility begins with identified patients defined by genotype and phenotype, site activation becomes a deployment decision based on operational capability. This approach improves predictability across the development lifecycle and supports stronger evidence generation in small populations.

See how Sano's site enablement model puts patient identification before operational feasibility here.