Essential Questions for Designing an Effective Feasibility Questionnaire

Understanding the Role of Feasibility Questionnaires

Before selecting sites and investigators, sponsors and CROs must carefully evaluate a site’s ability to successfully execute a clinical trial. A feasibility questionnaire is one of the most important tools for this assessment. These documents collect structured information about a site’s resources, patient pool, regulatory experience, and infrastructure readiness. Regulatory agencies such as the FDA, EMA, and national authorities expect sponsors to document feasibility efforts as part of Good Clinical Practice (GCP) compliance. Without a robust feasibility process, sponsors risk delays, under-enrollment, and inspection findings during trial audits.

Feasibility questionnaires typically cover domains such as:

• Patient recruitment and retention potential
• Principal Investigator (PI) and sub-investigator experience
• Site infrastructure, including equipment and labs
• Previous performance in similar therapeutic areas
• Local regulatory and ethics committee processes

For example, in oncology studies, questionnaires often probe whether the site has access to pathology labs capable of immunohistochemistry testing, or whether genetic testing partnerships exist. In infectious disease studies, questions may focus on availability of biosafety level facilities. Thus, while core domains remain consistent, therapeutic area–specific tailoring is essential.

Critical Patient-Related Questions

Patient recruitment is one of the most common barriers to timely trial completion. Regulators, including the European Medicines Agency (EMA), emphasize that feasibility assessments should be realistic and data-driven. A questionnaire must therefore ask targeted questions about patient populations. Examples include:

Incorporating epidemiological data strengthens these questions. For example, if a site estimates 300 eligible patients annually but national disease burden data suggests fewer than 50 cases in the region, this discrepancy raises concerns about overestimation. Sponsors should cross-check questionnaire responses with external databases such as ClinicalTrials.gov to validate feasibility claims against trial recruitment histories.

Questions on Investigator and Staff Experience

A site’s human resources are equally critical. Regulators often highlight inadequate investigator oversight as a frequent finding in inspections. Questionnaires should evaluate whether the PI and supporting staff have the necessary experience. Key questions include:

• How many clinical trials has the PI conducted in the past five years, and in which therapeutic areas?
• Has the PI received any regulatory inspection findings related to GCP?
• What is the average turnover rate of study coordinators and research nurses?
• What GCP training and certification do staff currently hold?

For example, a PI with ten oncology trials completed but with multiple FDA Form 483 citations may be a higher risk compared to a less experienced PI with a clean regulatory record. Feasibility questionnaires should capture such nuances.

Infrastructure and Technology Questions

Infrastructure capability directly influences trial quality. For complex trials requiring bioanalytical testing, imaging, or cold-chain management, questionnaires must go beyond basic facilities inquiries. Sample questions include:

• Does the site have validated -80°C freezers with continuous temperature monitoring?
• Are backup power systems in place to safeguard sample integrity?
• Is the site equipped with validated software for electronic data capture (EDC)?
• Are laboratory instruments calibrated according to international standards (e.g., ISO 15189)?

Some questionnaires include sample validation parameters such as:

These details help sponsors differentiate between sites that claim readiness and those that are genuinely prepared for trial operations.

Regulatory and Ethics Questions

Finally, feasibility questionnaires must assess local regulatory and ethics environments. Delays in IRB/EC approvals are a common reason for missed trial timelines. Essential questions include:

• What is the average IRB/EC review timeline for clinical trials at your institution?
• Do you have prior experience submitting to regulatory authorities such as FDA, EMA, CDSCO, or PMDA?
• Are there institutional policies restricting enrollment of vulnerable populations?

For example, if a site reports an average of 45 days for ethics approvals, sponsors can plan activation timelines accordingly. Sites with extended timelines (e.g., >90 days) may not be suitable for fast-track studies.

Transition to Next Considerations

The above domains—patient recruitment, investigator experience, infrastructure, and regulatory landscape—form the backbone of feasibility questionnaires. However, sponsors must also evaluate validation of responses, data reliability, and strategies to prevent overpromising. These aspects will be explored in Part 2, with focus on case studies, pitfalls, and best practices for robust feasibility planning.

Validating Feasibility Questionnaire Responses

Feasibility questionnaires are only useful if responses are accurate. Regulators and sponsors increasingly emphasize data verification as part of trial oversight. Sponsors must apply validation strategies to ensure that sites are not inflating capabilities or patient pools to secure trial participation.

One approach is to cross-verify patient pool estimates with hospital records, referral databases, or national disease registries. For example, if a site reports 500 annual cases of Type 2 diabetes, but regional public health data suggests only 300 cases, the sponsor should investigate. Similarly, sponsors should request anonymized patient counts or ICD-10 code reports to substantiate claims.

Case Study: Inflated Patient Recruitment Claims

A multinational sponsor faced delays in an oncology trial when three sites overestimated recruitment potential. While questionnaires projected 50 patients per site annually, actual enrollment was less than 10. Upon review, it was found that sites included patients outside inclusion criteria. This case underscores the importance of rigorous validation, including review of electronic health records (EHRs) and prior recruitment histories from registries such as ISRCTN Registry.

Common Pitfalls in Questionnaire Design

Despite best intentions, poorly designed questionnaires often result in incomplete or misleading data. Common pitfalls include:

• Overly generic questions that do not capture therapeutic-specific nuances
• Yes/No questions without quantitative context (e.g., “Do you have lab facilities?” instead of “How many calibrated centrifuges are available?”)
• Failure to include data validation fields or request supporting documentation
• Excessive questionnaire length leading to incomplete responses

To avoid these issues, sponsors should pilot-test questionnaires with selected sites and adjust based on feedback. Regulatory authorities also recommend focusing on essential questions that directly impact trial feasibility, rather than exhaustive lists that burden sites unnecessarily.

Best Practices for Effective Questionnaires

Effective feasibility questionnaires balance comprehensiveness with clarity. Best practices include:

• Tailoring questionnaires by therapeutic area (oncology, cardiology, infectious disease)
• Using a mix of quantitative and qualitative questions
• Integrating electronic platforms to streamline completion and analysis
• Embedding mandatory data validation checks (e.g., requiring supporting documentation uploads)

Some sponsors now deploy digital feasibility tools integrated with Clinical Trial Management Systems (CTMS). These allow automated scoring, comparison across sites, and identification of red flags such as inconsistent patient data. For example, an AI-enabled feasibility tool might score sites based on patient pool adequacy, infrastructure readiness, and regulatory history, generating a composite feasibility index for decision-making.

Sample Feasibility Scoring Framework

This weighted approach ensures objective decision-making while allowing customization for specific trial needs. For instance, in rare disease studies with small populations, patient recruitment weight might increase to 60%.

Conclusion

Feasibility questionnaires are a cornerstone of site selection and clinical trial planning. By including targeted questions on patients, investigators, infrastructure, and regulatory environment—and by validating responses through data cross-checks—sponsors can mitigate risks of underperformance and regulatory non-compliance. Effective design not only accelerates trial start-up but also strengthens inspection readiness by demonstrating a structured feasibility process.

Optimizing Site Feasibility in Clinical Trials for Ultra-Rare Diseases

Why Site Feasibility is Especially Crucial for Ultra-Rare Trials

In ultra-rare disease clinical trials, where eligible patient populations may be limited to only a few individuals per country—or even globally—site feasibility takes on an elevated level of importance. A misstep in site selection can lead to zero enrollment, delays, protocol amendments, or even trial failure. Sponsors cannot afford traditional high-volume approaches or selection based on historical metrics alone.

Feasibility assessments in these studies must focus on disease-specific patient availability, diagnostic capacity, investigator expertise in rare pathologies, and local regulatory familiarity with orphan drug protocols. Effective feasibility processes enable targeted recruitment, reduced site burden, and streamlined regulatory navigation. Agencies like the EMA and FDA expect robust documentation showing rationale behind site selection for such sensitive research populations.

Challenges in Identifying Feasible Sites for Ultra-Rare Conditions

Key challenges in site feasibility include:

• Scattered patient populations: Patients may be spread across countries or continents
• Limited diagnostic infrastructure: Especially for genotypically defined subgroups
• Low investigator experience: Physicians may have managed only 1–2 cases ever
• Ethical and regulatory complexity: Local authorities may lack rare disease trial precedents

For example, in a lysosomal storage disorder trial targeting 12 global patients, one high-profile academic site failed to enroll due to lack of genetic testing facilities, despite clinical interest. Early feasibility vetting could have flagged this mismatch.

Steps in Conducting Rare Disease Feasibility Assessments

A structured feasibility process for ultra-rare studies involves:

1. Feasibility Questionnaire: Tailored to assess site’s access to target population, diagnostic tools, and previous rare disease experience
2. Patient Funnel Analysis: Estimating the number of patients diagnosable, consentable, and willing to participate within study timelines
3. Protocol Complexity Assessment: Determining alignment between study demands and site capabilities (e.g., need for sedation MRI, long-term follow-up)
4. Regulatory Landscape Review: Understanding IRB timelines, import/export rules, and pediatric approval pathways
5. Site Qualification Visits (SQVs): Virtual or on-site walkthroughs for infrastructure and PI engagement evaluation

These steps, executed sequentially, provide a risk-profiled site readiness score and inform go/no-go decisions with clarity.

Patient Mapping and Registry Utilization

Feasibility should include proactive engagement with national rare disease registries, patient advocacy groups, and reference centers. Mapping where patients are diagnosed, managed, and treated—not just where hospitals exist—is critical.

For instance, India’s Clinical Trial Registry and national disease registries can help sponsors assess where most of the genetically confirmed cases are clustered. Such data may suggest partnerships with local genetic labs or patient support NGOs to ensure effective outreach during recruitment.

Case Study: Multi-National Feasibility for a Pediatric Enzyme Replacement Trial

A sponsor planning a global trial for a pediatric metabolic disorder with 18 patients worldwide began by distributing a standard feasibility questionnaire. Despite 30 responses, only 8 sites could confirm access to more than 1 patient, and only 4 had proven ERT experience. Post-screening, 5 were qualified through remote SQVs. This focused approach led to 95% of planned enrollment in under 8 months.

Such precision feasibility ensured optimal site-to-patient ratio, regulatory readiness, and engagement from experienced clinicians—drastically reducing trial risk.

Feasibility in Decentralized or Hybrid Trial Models

Decentralized trial (DCT) elements are gaining traction in rare disease research. Feasibility must now include assessment of:

• Telemedicine infrastructure for follow-ups
• Home health visit availability for sample collection or infusions
• Local lab capabilities for urgent assessments
• eConsent and remote monitoring readiness

Ultra-rare disease trials may enroll just one or two patients per site—making hybrid or DCT components not just helpful but essential for trial execution.

Regulatory Expectations and Documentation

Agencies such as EMA, FDA, and PMDA expect site selection to be justified in the Clinical Trial Application (CTA) dossier. Key documents include:

• Site feasibility reports and questionnaires
• Rationale for geographic distribution of sites
• Documentation of site capabilities for protocol-specific procedures
• Backup site lists and criteria for substitution

During GCP inspections, regulators may question why non-performing sites were selected or why local approvals were delayed. A clear feasibility traceability matrix helps defend site selection rationale.

Conclusion: Precision Feasibility is a Cornerstone of Rare Disease Trial Success

In ultra-rare clinical trials, each patient is precious—and each site is strategic. A well-executed feasibility process minimizes trial risk, optimizes resource use, and accelerates timelines. Sponsors should invest in tailored feasibility assessments that go beyond numbers and focus on true site readiness for complex, high-stakes research.

From infrastructure and personnel to patient access and regulatory history, every data point matters. Precision in feasibility leads to precision in outcomes—both scientific and operational.