External Control Arms
Build smarter control groups with fit-for-purpose real-world patient cohorts.
Shorter timelines. Stronger evidence.
Based on a proven methodology built upon 30+ years of experience, TriNetX external control arms (ECAs) help you with timely, representative, granular, and fit-for-purpose control groups.
Designed for studies where randomized controls are impractical, our experts will guide you through set-up, regulations, and execution as we use real-world patient data in lieu of additional patient recruitment, reducing costs and timelines while generating robust, regulation-ready evidence to support your trial.
Navigate regulatory uncertainty with confidence
Strengthen your HTA and EMA submissions with representative, fit-for-purpose ECAs designed for regulatory readiness.
Our methodology ensures scientifically sound data and processes, delivering evidence that regulators can trust and increasing your chances of a successful submission.
Overcome data and implementation challenges
TriNetX ECAs maintain the integrity of your analyses and results while helping you gain deeper insights into treatment impact. You can even generate supplementary control information for prospective experimental arms.
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Explore our insights
Even when the data foundation is right, even when the AI is producing high-quality insights, why are so many clinical operations teams not seeing the productivity gains the technology promised?
Jeff Brown spent last week in Milan at the ISPE Annual Meeting, where pharmacoepidemiology researchers, regulators, and industry experts gathered around a shared ambition: unlocking the power of data and pharmacoepidemiology to improve patient health.
This independently conducted Brief Report, conducted utilizing the TriNetX LIVE™ platform, makes that case in terms that Health Economics and Outcomes Research teams need to confront directly with additional research and contextualization.
This study compares the performance of a classic ML model and a LLM in deriving breast cancer stage from structured EHR data.
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