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
Run time: 8 mins. As global privacy regulations tighten, researchers can no longer rely on centralizing patient data to conduct multi-site studies — yet the demand for large-scale real-world evidence has never been higher.
The way smoking data get lost illustrates exactly how structured clinical datasets systematically fail to capture what’s clinically meaningful, and why that matters for every AI model built on them.
The milestone reflects accelerating international growth and gives pharmaceutical companies, academic researchers, healthcare providers, and health-tech innovators access to trusted, current, clinically rich, and globally representative real-world data.
The clinical trial industry has made a significant bet on artificial intelligence. The investment has been substantial. The results have been harder to quantify.
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