Getting the right outcomes from your clinical trials is all about the data and insights they provide. Biostatistics in clinical trials isn’t just a necessity, it can be a real competitive advantage.
The pressures facing drug development and commercialization have increased significantly in recent years, leading sponsors to find new ways to control cost and predict a program's success. The era of "big data" and innovative trial designs has ushered in new ways to leverage data to model potential clinical and operational outcomes. Among the most effective tools for accomplishing operational efficiency is using adaptive trial designs to generate more clinically significant data while improving patient outcomes. Harnessing the power of analytics is a powerful tool for choosing how and when to use adaptive trials to increase a trial's probability of success.
Adaptive trials have not yet found widespread adoption. In a recent survey, clinical operations and program planning professionals were asked, "How often do you use or advocate for adaptive methods (other than interim analyses and Phase 1 dose escalation)?" Only 54% — just over half of the respondents — indicated they "sometimes" consider adaptive trials, with 29% revealing they "never" attempt to incorporate this format. Only 3% responded they "always" attempt to adopt an adaptive design. These results illustrate an opportunity for planners to learn how this approach may increase a trial's probability of success.
Getting the right outcomes from your clinical trials is all about the data and insights they provide. Biostatistics in clinical trials isn’t just a necessity, it can be a real competitive advantage.
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