The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
Last week, Cytel conducted its third webinar in the new introductory webinar series on Complex Innovative Trial Designs. Our speaker, Dr. Satrajit Roychoudhury is a Senior Director, Statistical Research and Data Science Center at Pfizer. In this webinar, Dr. Roychoudhury gets into the basics of phase I designs in oncology trials, explains the caveats of frequently used traditional designs and provides insights on how implementing a model-based approach can enable a better statistical inference and decision-making. You can watch the replay of the webinar and access the slides by clicking on the button.
We also had the privilege to interview Dr. Satrajit Roychoudhury. Read our blog where he talks about his interest in statistics, explains the concept of Bayesian model-based approaches and their importance in oncology trials.
Significance of Bayesian Model-Based Approaches in Oncology Trials: An Interview with Dr. Satrajit Roychoudhury
Cytel conducted a webinar with Dr. Satrajit Roychoudhury, Senior Director, Statistical Research and Data Science Center, Pfizer. Dr. Roychoudhury talked about practical model-based approaches for phase I oncology trials. This webinar is a part of Cytel’s “Introduction to Complex Innovative Trial Designs” webinar series. You can watch the recording by clicking on the button below.
In this blog, we bring to you an insightful interview with Dr. Satrajit Roychoudhury where he talks to us about his interest in statistics, explains the concept of Bayesian model-based approaches and their importance in oncology trials.
In clinical development, a high-quality evidence package is a prerequisite for a new therapy to gain approval from regulators and other key decision-makers. As such, the quality of your clinical data is one of the key factors determining whether an effective new therapy reaches patients.
Implementing a data strategy can help to protect the quality of your evidence package. However, many companies start planning their strategy quite late in the development process, which makes it difficult to address (sufficiently address) the complex considerations involved. As we explore in our new eBook, a data strategy planned well in advance of starting Phase 1 and following the industry’s best practices can help you reduce risk, expedite clinical development, and successfully achieve your business objectives.
Download the new eBook, “Are you Harnessing the Power of your Clinical Data?” to find out how to optimize your data strategy to advance clinical development.
In our previous blog, we talked about the value of planning a data strategy for the entire duration of your program (i.e., a ‘program-wide’ strategy). However, it is also important to plan for specific phases of clinical development, because they each have unique challenges. Below we discuss the major challenges commonly encountered in Phase 1 and Phase 2 studies, and the tactics you can use to resolve them. An upcoming article will engage with challenges in Phase 3 and post-market.