Consulting
Scientific expertise for regulatory engagements, study design, and more.
Expert guidance, every step of the way
When your evidence needs to be rigorous, defensible, and ready for regulatory review, our consulting team is here to support you.
Led by internationally recognized experts — including leaders ranked in the world’s top 2% of most-cited scientists — we provide practical guidance across study design, strategy, and regulatory engagements to ensure your evidence generation is robust, valid, and actionable.
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Explore our expert consulting services
RWE consulting
Expert guidance for regulatory engagements and RWD study design, led by recognized industry leaders.
RWE research
Expert support from study design to dissemination to generate trusted evidence. Consultation to strengthen your evidence strategies and improve research outcomes from leaders in the field.
External control arms
Generate representative, fit-for-purpose control data with TriNetX external control arms.
Epidemiological services
Our epidemiological consulting team brings decades of experience to advance your goals through every stage of the evidence generation journey.
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Got a question, query, or just want to learn more? Our RWD experts are a click away
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Explore our latest articles, news, and whitepapers
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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