The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
In recent times, Single arm trials are being increasingly used to assess new treatment interventions. They establish clinical benefit by demonstrating the effects of a new therapy or treatment, without the need to use placebo or standard of care as a control. Instead, an alternative approach known as external controls or synthetic control arms (SCA) are being used that leverages real world data and historical datasets. Technical knowledge of Bayesian methods is key to being able to design and implement such trials.
Breakthrough treatments in oncology and rare diseases are now commonly approved based on a pivotal single arm trial – however this is not always optimal. Use of single arm trials in oncology or rare diseases requires appropriate comparisons to be developed to document the benefits of the new treatment. Deriving such comparisons from real world or historical trial data is not straightforward and requires data source and methods expertise.
As the use of master protocols becomes more prevalent in drug development, Bayesian methods are extensively used to ensure optimal use of data and flexible trial designs.
Master protocols are used for umbrella trials, basket trials and other clinical trial designs that enable multiple therapies to be tested at once. They provide the rules for adding and dropping arms on clinical trials where standards of care might constantly be changing, thus requiring special tools for updating comparator arms, adding new therapies and so forth.
Cytel recently conducted a webinar on Bayesian Dose-finding Designs for Modern Drug Development, presented by Dr. Yuan Ji.
Dr. Ji is a Professor of Biostatistics at The University of Chicago and a well-known name in the industry. In his presentation, he introduces representative Bayesian designs for dose-finding trials. The webinar offers insights on topics including classical DLT-based dose-finding designs, designs with delayed toxicity using time-to-event endpoints, and designs for combination dose-finding trial. Watch the on demand webinar to see the illustration of Bayesian modeling and inference for dose-finding designs that utilize the concept of probability intervals and related methods for clinical development and decision making.
Cytel and Novartis are together hosting a complimentary Bayesian Virtual Symposium and an Interactive 7-part workshop. This series will expose you to cutting edge topics from industry renowned leaders in Bayesian statistics. The introductory webinar “Bayesian Statistics and FDA Regulatory Acceptability” is presented by Greg Campbell, PhD, Former Director of Biostatistics, U.S. Food and Drug Administration.
In the United States Bayesian statistics has been used in regulatory submissions to the Food and Drug Administration (FDA) for confirmatory clinical trials medical devices for more than fifteen years. In this webinar, Dr. Campbell reviews the Bayesian history and accomplishments for medical devices. He talks about the status and opportunities of Bayesian statistics for pharmaceutical drugs and biologicals. We also learn about the challenges and the future of Bayesian statistics in the regulatory environment. You can access the on demand webinar and register for the rest of the series by clicking the button.
Today, there is a need for advanced quantitative techniques to combine all available information for better decision making in health care. Bayesian statistics allow us to make probabilistic inferences on the parameter of interest, which is missing in a traditional frequentist approach. Apart from the philosophical issues, Bayesian analysis provides a practical and intuitive tool for interpretation of study results and risk evaluation of clinical hypotheses.
Cytel and Novartis are together hosting a complimentary Bayesian Virtual Symposium and an Interactive 7-part workshop. This series will expose you to cutting edge topics from industry renowned leaders in Bayesian statistics. Click the button to learn more and register.