Site Selection & Optimization brings together patient access, investigator performance, and enrollment intelligence to help teams build country and site strategies that recruit faster and improve trial performance.
See where eligible patients receive care and where recruitment opportunities are strongest.
Rank investigators on experience, performance, capacity, and enrollment potential.
Identify competing trial activity, site capacity, and enrollment challenges before selection.
Understand the competitive picture. Identify where to invest and where to compete.
Design protocols real patients can qualify for, grounded in competitive evidence.
Place trials where eligible patients and capable sites meet.
Reach the right patients at the right moment.
Stay compliant and meet critical reporting obligations.
Identify investigators with the experience, capacity, and track record to deliver your study.
Forecast recruitment performance before finalizing country, site, and investigator decisions.
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Patient Intelligence, powered by NorstellaLinQ, helps teams understand where patients are, how they move through care, and which sites are best positioned to reach them, bringing patient access into site selection from the start.
Understand where eligible patients receive care.
See how patients move between providers and specialists.
Identify sites with the strongest access to eligible patients.
Site Selection combines investigator performance data, patient access intelligence, and clinical trial benchmarks to help teams make better country and site decisions.
Curated trials with reported enrollment results
Built on curated clinical trial, site, and investigator intelligence maintained by Citeline analysts.
Benchmark sites and investigators using enrollment performance, activation timelines, and historical trial outcomes.
Evaluate sites and investigators across 185 countries, including individual site performance and capacity.
| Traditional Approach | The Site Selection Workflow |
|---|---|
| Sites selected based on existing relationships | Sites ranked by performance, capacity, and patient access |
| Historical averages used to estimate enrollment | Enrollment potential forecast before selection |
| Limited visibility into competing studies | Competing trial activity visible at site level |
| Patient access inferred from assumptions | Patient density mapped around each site |
| Known investigators prioritized | Investigators recommended based on protocol fit |
| Decisions spread across disconnected tools | Countries, sites, and investigators evaluated in one workflow |
