Site Selection and Investigator Intelligence
Site selection is one of the highest-leverage decisions in trial management, and it's routinely made on inadequate information. The standard process relies on investigator relationships, geographic preferences, and instinct. The data to make this decision systematically exists and is now accessible through AI tools.
The data that predicts enrollment performance
Three data sources, used together, predict site enrollment performance with far more accuracy than investigator reputation alone:
Historical enrollment data. ClinicalTrials.gov contains enrollment information for completed trials, including site-level data for many studies. An investigator's enrollment history in trials with similar designs and patient populations is the strongest predictor of performance in your trial.
Patient population density. The number of eligible patients within the catchment area of each potential site, estimated from claims data, disease registry data, or epidemiological models. A site with a thin eligible population is structurally disadvantaged regardless of the investigator's skill.
Operational performance metrics. Site activation time, protocol deviation rate, query response time, and patient retention rate from prior trials. These operational metrics predict whether a site will be a partner or a liability.
The AI-assisted site selection workflow
- Define your enrollment target (patients per site per month to meet timeline).
- Use AI to search ClinicalTrials.gov for trials in your indication and geography, extract historical enrollment rates, and identify investigators with demonstrated performance.
- Cross-reference with patient population density data for each candidate site.
- Score candidate sites on historical performance, population access, and operational metrics.
- Allocate activation budget to the top-scoring sites first, with a reserve for geographic or demographic diversity requirements.
What changes
The typical site selection process takes three to four months. AI-assisted site selection, with well-structured data access, takes two to three weeks. The higher-leverage change is the decision quality: sites selected on performance data enroll 30-50% faster on average than sites selected on relationships.
That difference, across 30 sites in a Phase 3 trial, can compress enrollment from 24 months to 16 months.