Patient Feasibility and Site Selection

Define the Patient Selection Criteria

• Inclusion & Exclusion Criteria: Carefully review protocol-defined criteria (age, disease severity, prior treatments, comorbidities, biomarkers, etc.).
• Epidemiological Data Analysis: Use public health databases (e.g., WHO, CDC, NIH) and disease registries to estimate patient prevalence and incidence.
• Patient Journey Mapping: Understand how patients progress through the disease and standard treatment pathways to identify potential recruitment barriers.
• Direct Patient Insights: Use patient advocacy groups, social media, and focus groups to gauge interest and concerns.
• Create Patient Feasibility Questionnaire

Define Site Selection Criteria

• Site Databases & Networks: Utilize databases like ClinicalTrials.gov, TrialTroves, and investigator networks to identify experienced sites.
• Real-World Evidence (RWE) & Epidemiological Data: Use claims data, electronic health records (EHR), and disease registries to assess patient availability.
• Site Infrastructure: Ensure the site has the necessary facilities, equipment, and trained staff to conduct the study efficiently.
• Investigator Expertise: Evaluate the qualifications, experience, and track record of principal investigators (PIs) in conducting similar trials.
• Patient Recruitment Potential: Assess whether target sites have access to the target patient population based on epidemiology and historical recruitment performance.
• Site Investigator Feedback: Ask potential trial sites about patient recruitment challenges and strategies.

Consider Geographic & Logistical Factors

• Site Location: Ensure proximity to patient populations and accessibility for trial participants.
• Regulatory Timelines: Evaluate country-specific regulatory approval timelines, as some regions have faster processes.
• Competing Trials: Avoid sites with ongoing competing trials that could impact recruitment.

Leverage Technology & AI for Site Selection

• AI-Based Predictive Analytics: Use AI-powered tools like IBM Watson, Medidata AI, or TriNetX to predict site performance based on historical data.
• Electronic Health Records (EHR) Mining: Identify potential patient pools within healthcare systems.
• Decentralized & Hybrid Models: Consider remote patient monitoring or decentralized trial elements to enhance recruitment.

Conduct Feasibility Surveys & Pre-Screening

• Send feasibility questionnaires to shortlisted sites to assess:
  • Interest & availability
  • Experience with similar trials
  • Expected recruitment potential
  • Staffing capacity
• Data Quality & Compliance History: Review past performance in terms of protocol adherence, data integrity, and compliance with regulatory requirements.
• Historical Data & Benchmarks: Leverage past performance metrics from previous trials (e.g., enrollment rates, retention rates, data query rates).
• Regulatory & Ethical Compliance: Check the site’s familiarity with Good Clinical Practice (GCP), Institutional Review Board (IRB) approval processes, and local regulatory requirements.
• Feasibility Visits or Virtual Assessments: To verify responses and inspect infrastructure.
• Run a Small-Scale Pilot: Or pre-screening at selected sites to validate recruitment estimates before full study launch.

Develop a Recruitment & Retention Strategy

• Site-Specific Recruitment Plans: Tailor recruitment efforts based on site demographics.
• Community & Physician Engagement: Educate referring physicians and involve patient advocacy groups.
• Patient Support Initiatives: Offer travel reimbursement, flexible scheduling, and caregiver support if needed.

Continuous Site Performance Monitoring

• Implement real-time tracking of recruitment rates, dropout rates, and data quality during the trial to quickly address underperforming sites.