Innovations in the process of designing adaptive clinical trials have unlocked new possibilities for designing and executing more efficient, cost-effective, and ethical clinical trials. As more adaptive methods are introduced, biostatisticians struggle to optimize the growing number of interdependent trial parameters and ensure control over various execution assumptions. These trends are especially true for multi-arm multi-stage trial designs, which are typically conducted earlier in the drug development cycle and are therefore gaining prominence as decision points in the product’s evidence-generation roadmap.
Many design and optimization efforts are conducted using custom code, which allows for the flexible processing of increasingly complex tasks and design characteristics. But using languages such as R requires specialized training and expertise. Coding work, contingent on the statisticians’ abilities and experience, can be error-prone and time-consuming.
To learn more about how Solara® enables trial optimization and parameter selection in a systematic and holistic way using a combination of cloud computing and design-selection algorithms, download our new complimentary white paper, “Leveraging Cloud Computing and Advanced Software for Parameter Optimization of Multi-Arm Multi-Stage Designs”:
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Read more from Perspectives on Enquiry and Evidence:
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Adaptive Multi-Arm Multi-Stage Designs: A Comparison of Methods
How to Ensure Your Adaptive Trial Is Appropriate for Regulatory Submission
Optimizing Early Clinical Development Strategy
