The infrastructure gaps biopharma misses in rare and genetic trials
Rare and genetic programs increasingly depend on healthcare systems that are still adapting to the demands of precision medicine. Many of the constraints that affect feasibility, enrollment, and access originate upstream of recruitment and outside traditional trial operations. However, these are often neglected during trial planning and therefore cause late-stage and post-market challenges. Most enrollment and feasibility risk in rare and genetic trials is locked in well before recruitment begins.
This blog outlines common infrastructure gaps that biopharma sponsors frequently underestimate and explores practical strategies to address them.
Patient identification relies on provider-led processes
Patient identification in rare and genetic trials is driven by clinical recognition, diagnostic decision-making, and referral pathways. These processes vary widely across sites and specialties.
Many providers encounter potentially eligible patients but lack structured guidance on eligibility signals, the timing of genetic testing, or pathways into research. As a result, identification is inconsistent and often delayed. This contributes to the gap sponsors frequently observe between theoretical feasibility estimates and real-world enrollment once studies begin.
Diagnostic capacity requires workflow integration
Patient identification challenges are further compounded by uneven use of genetic testing across healthcare settings. Testing decisions are influenced by provider familiarity with rare diseases and access to technology.
When diagnostic workflows are not clearly integrated into clinical care and trial pathways, testing may occur late or not at all. This affects eligibility confirmation, increases screen failures, and shifts enrollment timelines. Diagnostic readiness depends not only on availability, but on clarity around how testing fits into routine care and research participation.
Provider confidence shapes trial participation
After identification and diagnosis have been completed, access to treatment is also heavily dependent on healthcare providers. Provider perceptions of cell and gene therapies (CGTs) influence whether patients are referred, tested, and enrolled in research. Recent data shows that 65% of surveyed oncologists viewed CGTs as “largely unproven” modalities. In parallel, 66% of clinicians reported their patients viewed these therapies as “too experimental.”
Confidence in innovative modalities develops through experience, clear expectations, and practical understanding of how therapies and trials fit within care delivery. When uncertainty persists, referral and enrollment behavior becomes more conservative, even in settings where patients may be eligible. This can directly reduce the pool of eligible patients who are willing and motivated to participate in trials or receive approved CGTs.
Access constraints influence clinical behavior
Coverage complexity and reimbursement uncertainty affect how providers approach referrals for CGTs. When access pathways are unclear, referral behavior becomes conservative.
In a survey, 72% of physicians reported that insurance coverage was the primary reason patients did not receive CGTs after referral. These experiences influence upstream identification and trial participation, reinforcing caution in patient selection and referral decisions.
Experience with CGTs remains concentrated
Physician experience with CGTs is increasing, with average treatment numbers rising year over year. However, this experience is concentrated within a limited number of centers and clinicians.
Many sites remain early in their learning curve, leading to uneven readiness across geographies and populations. This concentration creates logistical and geographic barriers to access and limits the diversity of trial participation.
Practical strategies sponsors can apply to address gaps
The gaps outlined above affect feasibility accuracy, enrollment reliability, and access outcomes across rare and genetic programs. Addressing them requires treating infrastructure readiness as an operational variable that can be actively shaped, rather than a fixed external constraint.
1. Validate real-world patient identification early
Sponsors benefit from assessing not only how many patients a site sees, but how patients are identified in practice. Early engagement with sites and providers helps clarify whether eligibility signals are recognized, referrals are triggered consistently, and identification aligns with protocol assumptions. This reduces the gap between theoretical prevalence and executable enrollment.
2. Integrate diagnostics into trial pathways
Genetic testing functions most effectively when it is embedded within clinical and trial workflows. Sponsors can support clarity around when testing should occur, how it is ordered, and how results translate into trial action. Aligning diagnostics with trial pathways reduces delays in eligibility confirmation and improves enrollment predictability.
3. Support provider confidence through practical enablement
Provider confidence is shaped by clarity on clinical application, durability expectations, and operational pathways. Sponsors can support more consistent participation by ensuring providers understand how trials and therapies fit within real-world care delivery, rather than relying solely on scientific messaging.
4. Account for access and reimbursement realities
Coverage complexity and reimbursement uncertainty influence referral behavior upstream. Sponsors that incorporate access considerations into trial planning, site engagement, and provider support enable clearer decision-making and reduce conservative referral patterns that limit participation.
5. Broaden readiness beyond established centers
Reliance on a small number of high-experience centers concentrates risk and limits access. Expanding readiness across a broader network of sites supports geographic coverage, improves equity in trial participation, and reduces overdependence on a limited set of centers.
6. Actively plan for infrastructure readiness
While infrastructure readiness may evolve throughout a program, sponsors should plan ways to overcome infrastructure gaps early on. This can help prevent late-stage surprises once a trial is already running. In parallel, sponsors that monitor patient identification patterns, diagnostic use, site capability, and access barriers over time are better positioned to adapt execution strategies in response to demands.
Conclusion
Infrastructure gaps in rare and genetic trials become visible when programs move from design into real-world execution. Patient identification, diagnostics, provider confidence, access pathways, and site experience all influence whether feasibility assumptions translate into reliable enrollment and delivery.
Sponsors that address these elements early and systematically reduce uncertainty across feasibility, enrollment, and access. Treating infrastructure readiness as a core operational input improves alignment between scientific intent and real-world execution, supporting more consistent trial performance and broader patient impact.