Our clinical study program
GRAIL’s clinical development program is one of the largest in cancer screening, enrolling over 380,000 participants across multiple studies. These studies demonstrate broad applicability of our multi-cancer early detection technologies and aim to advance earlier cancer detection and improve outcomes through innovative, blood-based screening. To support and validate our technology, we are partnering with leading community and academic medical centers around the world.
REACH/Galleri-Medicare Study
This multi-center comparative, prospective, cohort study is designed to assess the real world clinical impact, including safety and test performance, of the Galleri® test.
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SUMMIT Study
A prospective, observational, longitudinal, cohort study in London, United Kingdom. The study is designed to enroll approximately 13,000 men and women who do not have a high risk for lung or other cancer due to significant smoking history at the time of enrollment.
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REFLECTION Study
An observational study of patients who have been administered the Galleri® test.
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STRIVE Study
A prospective, observational, longitudinal, cohort study that enrolled approximately 100,000 women to refine the predictive ability of the Galleri® test to detect invasive cancers.
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PATHFINDER 2 Study
This is a prospective, multi-center interventional study of the Galleri® multi-cancer early detection test with return of test results for participants enrolled through healthcare systems in North America.
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NHS-Galleri Trial
A prospective, randomized, controlled trial to assess the performance and clinical utility of the Galleri® test for population screening in the UK when added to standard of care.
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PATHFINDER Study
A prospective, interventional, return-of-results, multi-center study to assess the implementation of an earlier version of the Galleri® multi-cancer early detection (MCED) test in a clinical setting. Later, blood samples were reanalyzed with the current version of Galleri.
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The Circulating Cell-free Genome Atlas (CCGA) Study
A multicenter, prospective, case-control, observational, longitudinal study designed to identify the best performing assay and then determine whether genome-wide cfDNA methylation sequencing in combination with machine learning could distinguish cancer from non-cancer and localize a signal shared by a large number of cancers.
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