Designing Feasibility Questionnaires Using Historical Site Data

The Importance of Historical Site Data in Feasibility Planning

Feasibility questionnaires are foundational tools in clinical trial planning. They help sponsors and CROs identify and select high-performing sites based on several factors like patient pool, investigator experience, infrastructure, and regulatory track record. However, when these questionnaires are designed without historical context, they can result in overly optimistic or inaccurate site responses. That’s where leveraging historical site data becomes critical.

Historical site data includes past enrollment rates, protocol deviation frequencies, screen failure rates, regulatory inspection outcomes, and adherence to visit schedules. Sponsors that fail to incorporate this data often face recruitment delays, budget overruns, and poor site compliance. Regulatory bodies including the FDA, EMA, and MHRA emphasize the use of evidence-based feasibility strategies during sponsor inspections.

In this article, we explore how to use historical site data to design smarter, more predictive feasibility questionnaires that improve site selection and study startup efficiency.

Types of Historical Data Relevant to Questionnaire Design

Historical site data spans multiple domains. The most useful categories include:

• Enrollment History: Number of subjects enrolled in similar trials within a specific timeframe
• Protocol Adherence: Frequency of deviations and their root causes
• Screen Failure Rates: Percentage of screened patients not meeting inclusion criteria
• Site Activation Timelines: Average time from contract finalization to first patient in (FPI)
• Regulatory Inspection Outcomes: FDA 483 observations, MHRA findings, or internal QA audits

Below is an example data summary from three sites in a cardiovascular trial:

From this table, it’s evident that Site A outperformed others in all key areas. Integrating this insight into a questionnaire helps to focus future feasibility assessments on parameters that matter.

Integrating Data into Feasibility Questionnaire Logic

Feasibility tools often consist of static checklists or self-reported site capabilities. When these are integrated with historical performance data, they become much more predictive. Here’s how historical data can enhance questionnaire sections:

• Recruitment Potential Section: Pre-fill enrollment numbers from past studies and ask the site to explain any changes
• Protocol Adherence Section: Highlight deviation patterns from previous trials and assess current mitigation measures
• Timeline Commitments: Use actual past activation data to validate new timeline estimates

For example, a dynamic form might display: “In your last three trials in this therapeutic area, your average enrollment was 20 patients over 6 months. What has changed to support your estimate of 60 patients in this protocol?”

This approach discourages over-promising and helps differentiate high-performing, realistic sites from aspirational responders.

Sources of Historical Site Data

Historical site data can be gathered from several internal and public sources:

• Clinical Trial Management Systems (CTMS): Capture site-level metrics from previous studies
• Electronic Data Capture (EDC) Platforms: Document protocol adherence and visit windows
• Trial Registries: Data from Be Part of Research (NIHR) and other registries to validate enrollment timelines
• Quality Management Systems (QMS): Archive audit outcomes, CAPA timelines, and deviations

Sponsors that maintain a structured site master file with past feasibility, audit reports, and performance summaries can extract this data with minimal effort. It’s also beneficial to include CRO partner databases and publicly available performance scores (e.g., from the TransCelerate Shared Investigator Platform).

Feasibility Questionnaire Elements That Benefit from Data Integration

Not all parts of a feasibility questionnaire require historical data, but certain sections benefit significantly from it:

By designing forms with auto-filled historical fields, sponsors can reduce bias and increase transparency. Some tools even allow scoring systems based on prior performance benchmarks.

Case Study: Data-Driven Feasibility Yields Better Enrollment

In a 2023 Phase II neurology study, the sponsor used historical site performance data to filter out low-recruiting sites from a previous epilepsy trial. By incorporating metrics such as “patients enrolled per FTE” and “visit adherence rate,” they excluded 30% of sites that had previously delayed timelines. The remaining sites achieved 95% of the recruitment target three months ahead of schedule.

This outcome illustrates how applying historical metrics during feasibility tool design directly impacts enrollment, cost, and data integrity.

Tools and Platforms That Support Data-Driven Questionnaire Design

Sponsors can use various platforms to operationalize this approach:

• CTMS Platforms: Veeva Vault CTMS, Medidata RAVE
• Feasibility Tools: SiteIQ, Clinscape Feasibility Module
• Analytics Dashboards: Tableau, Power BI connected to CTMS/EDC sources
• Risk-Based Monitoring Tools: RBM dashboards that include performance trend lines

These systems allow sponsors to design adaptive questionnaires, conduct real-time validation of site claims, and score site responses against benchmarks.

Challenges and Considerations

Despite the advantages, there are challenges to using historical data:

• Data inconsistency across CROs and systems
• Lack of access to complete legacy data for global sites
• Privacy and data protection regulations (e.g., GDPR)
• Misinterpretation of context (e.g., poor performance due to protocol flaws, not site issues)

Therefore, sponsors must contextualize historical data and allow sites to provide explanations for deviations or poor performance. Data should be used to initiate dialogue, not penalize sites without cause.

Conclusion

Designing feasibility questionnaires using historical site data enables evidence-based site selection, reduces trial risk, and improves regulatory compliance. Sponsors should move away from static, self-reported surveys and adopt dynamic, data-informed tools that consider past performance. Platforms such as CTMS, QMS, and analytics dashboards can help integrate these insights into feasibility tools, creating a predictive framework for identifying high-performing, inspection-ready sites. In doing so, the industry takes a meaningful step toward smarter, faster, and more reliable clinical trial execution.

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.

Lessons from Overcoming Recruitment Barriers in Rare Disease Clinical Trials

Introduction: Why Recruitment Is the Greatest Barrier in Rare Disease Research

Recruitment remains the single most critical challenge in rare disease clinical trials. With patient populations often numbering in the hundreds—or even dozens—globally, traditional recruitment approaches used in large-scale trials are ineffective. Barriers such as delayed diagnosis, limited clinical expertise, geographic dispersion, and lack of awareness significantly delay trial initiation and completion. These obstacles increase trial costs, risk under-enrollment, and can ultimately threaten the viability of drug development programs.

This article presents a case study of a multinational rare disease trial that faced severe recruitment challenges. By employing innovative strategies such as leveraging global patient registries, forging partnerships with advocacy groups, and implementing digital recruitment campaigns, the trial not only achieved its enrollment targets but also accelerated timelines. The lessons from this case study are highly relevant for sponsors, CROs, and investigators seeking to optimize recruitment in small populations.

Case Study Background: A Gene Therapy for a Rare Neuromuscular Disorder

The trial in focus targeted a genetic neuromuscular disorder affecting fewer than 2,000 individuals worldwide. The investigational therapy, a one-time gene replacement product, aimed to address the root cause by correcting the defective gene. With such a small and globally dispersed population, traditional site-based recruitment was deemed impractical. Initial feasibility assessments showed that most sites could only recruit 1–3 patients each over two years, insufficient to meet trial timelines.

Key challenges included:

• Low disease awareness: Many clinicians lacked experience diagnosing or managing the disorder.
• Geographic spread: Patients were dispersed across 25+ countries, with limited specialist centers.
• Diagnostic uncertainty: Inconsistent access to genetic testing delayed identification of eligible patients.
• Caregiver burden: Families expressed concerns over travel and trial logistics.

Despite these barriers, the sponsor developed a tailored recruitment strategy, integrating technology and community engagement to maximize patient reach.

Building and Leveraging Global Patient Registries

One of the first steps was establishing a global patient registry in collaboration with international advocacy organizations. The registry collected standardized clinical and genetic data, which facilitated rapid identification of potential candidates. This approach addressed both diagnostic and geographical barriers by consolidating fragmented patient information into a single accessible platform.

The registry featured:

• Structured clinical data including disease onset, severity, and progression.
• Genetic confirmation of pathogenic variants, minimizing misdiagnosis risk.
• Longitudinal data on natural history to support trial design.

Within six months, the registry enrolled 60% of the estimated global patient population, providing a reliable pool of trial-eligible candidates. The use of international trial registries also improved visibility and transparency.

Advocacy Partnerships and Community Engagement

Patient advocacy groups were central to recruitment success. They helped raise awareness, educate families about clinical research, and build trust between sponsors and the patient community. Through advocacy-led webinars, newsletters, and caregiver forums, patients and families received clear, culturally sensitive information about trial participation.

These partnerships also enabled:

• Pre-screening campaigns: Advocacy groups coordinated with local clinicians to encourage genetic testing and confirm eligibility.
• Travel support funds: Donor-backed initiatives helped reduce financial burdens on families traveling to study sites.
• Caregiver counseling: Psychosocial support was offered to address concerns about safety and long-term follow-up.

Digital Recruitment Campaigns and Telemedicine Integration

Given the rarity of the condition, digital outreach was essential. Targeted social media campaigns in multiple languages reached undiagnosed and geographically isolated patients. Search engine optimization (SEO) campaigns directed families to trial information pages. Additionally, telemedicine was introduced for pre-screening visits, reducing the need for unnecessary travel.

This hybrid approach—digital recruitment coupled with virtual assessments—helped identify candidates faster and provided a smoother patient experience. Moreover, caregivers appreciated the flexibility, which increased willingness to participate.

Trial Outcomes and Lessons Learned

Ultimately, the trial achieved full enrollment within 18 months, compared to the initial projection of 36 months. Key lessons included:

• Invest early in registries: Establishing centralized patient databases accelerates recruitment.
• Leverage advocacy groups: Trusted community partners are indispensable for outreach and education.
• Adopt digital-first strategies: Social media and telemedicine expand reach and reduce burden.
• Support families: Travel and psychosocial support directly impact recruitment and retention.

The case study demonstrated that recruitment barriers in rare disease trials are not insurmountable if approached with creativity, collaboration, and patient-centricity.

Conclusion: A Roadmap for Future Rare Disease Trials

This case study underscores that recruitment challenges in rare disease trials can be overcome with a multi-pronged strategy that integrates technology, advocacy, and supportive measures. By placing patients and caregivers at the center of trial planning, sponsors not only achieve enrollment targets but also foster long-term trust with rare disease communities.

For future rare disease studies, this roadmap offers a clear lesson: building relationships, investing in infrastructure, and embracing digital solutions are as important as the science itself.