Cytel Blog

The Cytel Trial Design Innovations (CTDI) Webinar Series recently hosted a webinar on designing event-based studies. Such studies are essential to designing high-efficiency clinical trials in certain therapeutic areas, but they add a number of challenges to the already complex landscape of adaptive trials.

The webinar was held on January 23rd, featuring Biostatistician and pioneering Bayesian trial-designer Pantelis Vlachos. We had the opportunity to sit down with Dr. Vlachos and speak about innovative trial designs and their benefits, adaptations and interim looks in oncology and cardiovascular, the challenges of designing event-based studies more generally, and how Cytel’s array of software tools, particularly East^®, has enabled trial sponsors to fully consider their options in the design of high-efficiency clinical trials.

With only two weeks left for this fabulous year to end, we would like to thank all our blog subscribers and new readers for following and appreciating the Cytel blog. This year, we collaborated with several experts from both within and outside the company to bring to you a range of interesting topics including real-world evidence, AI, challenges in rare diseases, patient-reported outcomes, data management, and our popular series “The Good Data Submission Doctor” and “Career Perspectives”. In this blog, we share with you the top 5 Cytel blogs that resonated most with our community in 2019.

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Cytel is delighted to have Kannan Natarajan speaking at the “Complex Innovative Trial Design Symposium and East User Training” on November 6 in Boston, MA. We got a chance to sit down with Kannan and talk about his career in statistics, the changing role of statisticians, his views on evolving statistical thinking, estimands and relevance of technology in the context of rare diseases.

In honor of Rare Disease Day 2019 we share a new Cytel podcast featuring Cytel Strategic Consultant Ursula Garczarek discussing how innovative statistical approaches can overcome challenges in rare disease development. Below, you can access the podcast and a summary of some of Ursula's key insights from working in rare diseases and interacting with regulatory agencies for complex and innovative designs.

There is a consensus in the industry that data on rare diseases is limited, incomplete, and difficult to find or access. Recently we came across the CoRDS patient registry based at Sanford University and learned that the registry is an effective tool used to gather information useful to researchers studying rare diseases.

We sat down with Benjamin Forred, Project Manager, and Austin Letcher, Senior Research Associate at CoRDS to learn more about the registry and hopes for the future.

A paper "Best practices case studies for 'less well-understood' Adaptive designs", has been published by the DIA Scientific Working Group on Adaptive Designs as a twin document to the previously discussed "Challenges and Opportunities of 'Less Well Understood' Adaptive Designs".  This publication furthers understanding by reviewing 10 important case studies and sharing details on their design and operational characteristics, as well as related regulatory interactions.  

To read an abstract and details of the full publication click here. 

 In this blog we'll take a look at some of the case studies under discussion. 

“We shouldn’t use an adaptive design, our sample size is too small.”

Most clinical trial planners have heard this line of reasoning so often it has come to be taken as true. Never mind the fact that the first product to receive FDA approval using an adaptive sample size re-estimation design, was for a genetic condition affecting fewer than two thousand children worldwide [1].

Sofia S. Villar is a member of the DART (Design and Analysis of Randomised Trials) group at the MRC Biostatistics Unit in Cambridge England. She has recently been awarded the first Biometrika post-doctoral research fellowship. 

In the post below Villar offers her position on how challenges in rare disease drug development may be alleviated by Bayesian-Bandit adaptive designs. The "Multi-armed Bandit" is an agent who tries to acquire new knowledge while trying to capitalize on existing knowledge. Clinical studies can therefore utilize bandit designs to recruit patients whose primary goal in participating in a trial is to improve their health outcomes.