Clinical operations realities shaping success in rare disease clinical trials

Rare diseases have become a central pillar of global drug development. Over the past decade, sponsor investment has accelerated steadily, driven by high unmet need, regulatory incentives, and scientific advances that make targeting small populations increasingly viable.

• 35% of the global R&D pipeline now targets rare disease indications, up from 31% in 20181,2

• 58% of drug and biologic approvals in 2018 were for rare diseases, compared with 26% a decade earlier2

Yet this momentum masks a harder operational truth: rare disease trials are fundamentally less forgiving than studies in larger populations. Small misalignments between planning assumptions and on‑the‑ground reality can cascade into outsized delays, cost overruns, or stalled enrollment.

Multiple industry analyses point to the same conclusion: rare disease development is more resource‑intensive, takes longer to execute, and carries higher execution risk than non‑rare disease programs.

• Phase II–III rare disease trials involve 30% more planned visits, 23% longer start-up timelines, and 19% longer treatment durations1

• Overall development timelines from IND to regulatory decision are 4 years longer than in non-rare disease programs2

• Rare disease trials demand more sites for fewer patients: up to 6× more sites in early phase to recruit ~25% of patients, and 50–60% of sites in Phase II–III to enroll just 15% of participants2

• 81% screen failure rates and 56% randomization failure rates far exceed those seen in non-rare indications (compared to 57% and 36%, respectively for non-rare diseases)2

There are bright spots. Once enrolled, rare disease patients are less likely to drop out, and regulatory review timelines are often shorter due to accelerated and fast‑track pathways. But these advantages do not offset the operational fragility that defines rare disease feasibility.

Across therapeutic areas and modalities, three recurring planning challenges consistently shape rare disease trial outcomes.

1. Small populations require intelligent prioritization, not broad expansion

Rare diseases are defined by scarcity. Patient populations are small, geographically uneven, and often concentrated in specific care centers. In this environment, expanding feasibility assumptions by adding countries or sites rarely delivers proportional enrollment gains.

Broad geographic expansion often increases complexity without improving access to patients. More countries mean more regulatory submissions, more start‑up variability, and more operational overhead—without solving the underlying problem of where patients can realistically be identified and enrolled.

Effective rare disease feasibility focuses on precision: prioritizing countries and regions where patients have historically been diagnosed, treated, and successfully enrolled. In the current landscape, competitive saturation matters just as much as prevalence. Regions that appear attractive on paper may already be oversubscribed by overlapping trials targeting the same limited population. When feasibility relies too heavily on prevalence estimates or high‑level historic enrollment figures, these dynamics are easy to miss until enrollment stalls.

2. Investigator and site capacity is the true bottleneck

Rare disease trials are constrained less by the number of sites available and more by the number of qualified sites with real capacity. Many rare conditions rely on a small network of experienced investigators who are repeatedly approached by multiple sponsors.

To compensate, early‑phase rare disease trials often engage a higher number of investigative sites, each enrolling only a handful of patients. This approach increases operational burden while amplifying competition for the same limited investigator bandwidth.

What looks feasible during planning can quickly unravel when sites are already committed to competing protocols, lack staffing capacity, or cannot meet projected enrollment rates. Static site lists and assumptions about investigator availability fail to capture this reality.

This makes investigator and site capacity the true bottleneck in rare disease feasibility. Planning must account for current investigator workload, site experience, and active trial commitments, not just historical participation.

3. Competitive timing and overlap matter more than ever

Rare diseases were once viewed as relatively insulated from competition. That assumption no longer holds. By the end of 2024, most large pharmaceutical companies had pipelines dominated by rare or ultra‑rare disease programs.

As pipelines crowd, competition intensifies, even within narrowly defined patient populations. When multiple trials recruit from the same limited pool, enrollment can be cannibalized rapidly. This “silent competition” often becomes visible only after timelines slip.

Overlapping trial windows place additional strain on sites, which may be asked to support multiple complex protocols for the same condition. Without visibility into current and upcoming competitive activity, feasibility plans risk being locked in just as pressure peaks.

Additional complexity: design and regulatory evolution

Beyond operational constraints, rare disease trials carry added complexity at the level of trial design and regulation. Endpoint selection is often challenging when validated measures do not exist, requiring reliance on surrogate endpoints, digital measures, or natural history data. While adaptive designs and master protocols offer flexibility, they also introduce assumptions that must be tested early to avoid downstream risk.

Regulatory agencies have expanded flexibility for rare disease development, enabling smaller or alternative study designs when traditional randomized trials are not feasible. In parallel, sponsors are piloting AI- and machine learning–enabled analytics, shared-infrastructure protocol models, risk-based approaches, and remote or virtual trial technologies to reduce burden and extend reach. Together, these advances offer real opportunities—but only when design choices are grounded in feasibility insights that reflect operational reality.

Why precision matters more than expansion

In rare disease planning, the default response to scarcity - add more countries, add more sites - often makes plans more brittle, not more resilient. When patient pools are small and assumptions fragile, precision becomes essential.

What consistently matters most is:

• Where qualified patients can realistically be reached

• Which sites and investigators have capacity now

• How competitive activity overlaps in time and geography

• How protocol design affects accessibility and burden

Feasibility is no longer about proving that patients exist. It is about demonstrating that patients can be recruited under real‑world constraints.

How TA Scan supports rare disease feasibility

TA Scan is designed to support this shift from expansion to precision. By integrating real‑time trial activity, investigator experience, site capacity, and competitive landscape intelligence, TA Scan helps teams align feasibility assumptions with operational reality.

Across rare disease programs, teams use TA Scan to:

• Prioritize countries and regions based on proven enrollment success

• Identify experienced investigators through their scientific and clinical footprint

• Assess site and investigator capacity using current activity signals

• Detect competitive pressure early, before plans are finalized

In practice, teams repeatedly see that rare disease feasibility based only on prevalence or historic enrollment overlooks both competitive saturation and unrealized opportunity. These blind spots often emerge only after enrollment slows. In TA Scan, sponsors have identified a significant number of additional viable rare disease sites—including sites neither they nor their CROs had previously considered—strengthening feasibility strategies without unnecessary geographic expansion.

This combination of depth, accuracy, and rare-disease-specific coverage has led clinical teams to rely on TA Scan as a high-quality intelligence source in some of the most operationally constrained trial environments.

Bottom line for clinical operations

Rare disease trials leave little room for error. Rising development costs, longer timelines, and declining average R&D returns place increasing pressure on execution quality. In this environment, insight quality matters more than data volume.

Precision determines whether a rare disease feasibility plan holds up under pressure. And feasibility done well is no longer a checkbox exercise; it is a strategic capability.

For clinical operations teams, success starts with asking not whether patients exist—but whether plans reflect the reality of enrolling them.

References:

1)      Ken Getz. (2025) The Hard Truth About Rare Disease and Gene Therapy Drug Development. Applied Clinical Trials

2)      Ken Getz. (2019) Proliferation of Rare Disease R&D Necessitating Novel Strategies. Applied Clinical Trials