While incorporating real-world data (RWD) and real-world evidence (RWE) across the drug development lifecycle is getting a lot of attention, the application of such insights gleaned from rigorous analysis to the design and execution of clinical trials has yet to be widely adopted, despite its potential to address some of these persistent challenges.
A paradigm shift that leverages advanced tech-enabled data analytics can aid pharmaceutical companies in overcoming common clinical trial delays related to randomization and a host of other trial design and execution issues, such as trial eligibility criteria, predicted responses, estimated sample size, endpoint selection, and increased diversity.
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