We built a clinical trial site matching marketplace over 16 weeks, designed to serve both the consortium members and, eventually, the broader biopharma industry. Platform Architecture: the marketplace connected two user types: Sponsors/CROs (demand side — companies seeking clinical trial sites for specific studies) and Research Sites (supply side — hospitals, academic medical centers, physician practices, and dedicated research centers offering clinical trial capabilities). Site Profiles: we built comprehensive, structured profiles for research sites: capabilities (therapeutic area expertise, equipment available, lab certifications, pharmacy capabilities, IRB type — central vs. local, imaging capabilities), investigator profiles (principal investigators and sub-investigators — credentials, therapeutic area experience, publication history, active and completed trials, enrollment track record), patient population data (de-identified patient demographics and disease prevalence for the site's catchment area — derived from: census data, claims data analysis, and site-reported information.
For rare diseases: connections to patient registries and advocacy organizations), performance metrics (historical enrollment rates — actual vs. projected for completed studies, screen failure rates, protocol deviation rates, and query resolution times — quantitative quality indicators that sponsors could evaluate objectively), capacity and availability (current trial load, available research coordinator FTEs, study startup timeline estimates, and upcoming capacity based on expected trial completions), and compliance and quality (FDA inspection history, CAP/CLIA certifications, IRB approval timelines, and any corrective actions or findings). We recruited and profiled 340 research sites across New England (Massachusetts, Connecticut, Rhode Island, New Hampshire, Maine, Vermont) through a combination of: consortium member introductions, direct outreach to hospital research departments, partnerships with institutional research networks, and site self-registration.
Matching Engine: the core intellectual property — an AI-powered matching system that scored site-study compatibility: protocol analysis (the sponsor uploaded the study protocol, and the system extracted: therapeutic area, indication, inclusion/exclusion criteria, required procedures and assessments, visit schedule complexity, and specialized requirements — biomarker testing, imaging protocols, genetic testing), multi-factor scoring (each site received a compatibility score based on: therapeutic area match (does the site have experience with this indication?), patient population match (does the site's catchment area include the target patient population? — using de-identified claims data analysis), investigator experience (has the PI conducted similar trials? what was their enrollment performance?), capability match (does the site have the required equipment, lab certifications, and pharmacy capabilities?), capacity match (does the site have available coordinator FTEs and patient slots?
), quality score (historical performance metrics — enrollment rate, deviation rate, query resolution), and geographic match (proximity to the sponsor's monitoring team and to other selected sites for the study)), and recommendation generation (for each study, the system generated a ranked list of recommended sites with: compatibility scores, detailed rationale for each recommendation, and identified gaps — capabilities the site was missing that might be addressable). Contract Facilitation: to address the contracting bottleneck, we built a contract module: the consortium developed a standardized clinical trial agreement (CTA) template that all 12 members agreed to use as a starting point — pre-negotiated terms covering: indemnification, insurance, intellectual property, publication rights, and data ownership.
The platform generated: pre-populated CTAs based on the study protocol and site information, redlined versions showing deviations from the standard template, and a negotiation workflow that tracked changes, approvals, and execution — reducing bilateral negotiation by providing a shared starting point. Dashboard and Analytics: the platform provided: real-time enrollment tracking (after sites were activated, sponsors tracked enrollment progress against projections — with early warning when sites fell behind), portfolio-level analytics (consortium members could see their trial portfolio's enrollment health across all studies and sites), and benchmark data (how a site's performance compared to peer sites on: enrollment rate, startup time, and data quality).