Watch our on-demand webinar series which introduces biostatisticians and other members of the development team to some of the more commonly used innovative trial designs, the benefits of each, and the practical considerations for adoption. The series includes a stellar lineup of Cytel colleagues and partners including world renowned statisticians Nitin Patel, Zoran Antonijevic, Chris Jennison, Satrajit Roychoudhury, Thomas Burnett, Jose Pinheiro and more...
Series Overview
- Innovative Drug Development at a Glance - The Concepts, The Vision, & The Factors to Consider
Zoran Antonijevic, Head of Biometrics at MedSource - Group Sequential Designs and Sample Size Re-estimation – Modern Uses
Dr. Christopher Jennison, Professor of Statistics, University of Bath, UK -
Practical Model-based Approaches for Phase I Oncology Trials
Dr. Satrajit Roychoudhury, Senior Director, Statistical Research and Data Science Center, Pfizer -
Adaptive Enrichment Designs in Clinical Development
Dr. Thomas Burnett, Senior Research Associate in Medical and Pharmaceutical Statistics, Lancaster University - Adaptive and Bayesian Designs for Dose-Finding
Bjoern Bornkamp, Statistical Methodologist, Novartis Jose Pinheiro, Senior Director, Johnson & Johnson - Designing Clinical Trials from a Program Perspective
Nitin Patel, Co-Founder and Board Member, Cytel
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Abstracts
Innovative Drug Development at a Glance - The Concepts, The Vision, & The Factors to Consider
Zoran Antonijevic, Head of Biometrics at MedSource
This webinar defines complex innovative trial design, briefly introduces the concepts, summarizes the potential benefits of each, and highlights key factors to consider when applying these techniques. With pharmaceutical and biotech companies under the pressure to deliver more and deliver faster with fewer resources, there is no time like the present to embark on this journey.
Group Sequential Designs and Sample Size Re-estimation – Modern Uses
Dr. Christopher Jennison, Professor of Statistics, University of Bath, UK
Group Sequential Designs were one of the earliest deviations from a traditional two-arm clinical trial with no interim looks at the data. They still add amazing value to trials through their abilities to safeguard patients, reach positive conclusions early, and keep trial designs simple and streamlined. Sample Size Re-estimation is another key tool in the modern trial designer’s toolkit. Learn the basics of these two methods, how they are used, and how they can improve trial design.
Practical Model-based Approaches for Phase I Oncology Trials
Dr. Satrajit Roychoudhury, Senior Director, Statistical Research and Data Science Center, Pfizer
Phase I Oncology trials used dose-escalation to determine the maximum tolerated dose for further study. Modern model-based techniques help to acquire knowledge about the chemistry of the new drug and select appropriate dose for later phases. It offers clinicians more flexibility than more traditional designs like the 3+3. Through this introduction to advanced dose escalation methods, you will first learn about the traditional 3+3 method for dose-escalation and then gain an understanding of how Bayesian logistic regression model (BLRM) techniques can improve the traditional method.
Adaptive Enrichment Designs in Clinical Development
Dr. Thomas Burnett, Senior Research Associate in Medical and Pharmaceutical Statistics, Lancaster University
Recent developments in genomics have made it possible to test how those with different biomarkers will respond to a new therapy or vaccine, optimizing using “enrichment strategies” and adaptive designs. This webinar will teach you the foundational elements of these designs, setting the stage for later webinars on basket, umbrella and MAMS designs.
Adaptive and Bayesian Designs for Dose-Finding
Bjoern Bornkamp, Statistical Methodologist, Novartis Jose Pinheiro, Senior Director, Johnson & Johnson
Finding the right dose in Phase 2 gives a potential new therapy its best chance to demonstrate efficacy during Phase 3. A well-executed dose-ranging trial therefore has the potential to alter the course of the entire clinical development program. This webinar will demonstrate how adaptive and Bayesian techniques can be implemented for optimal dose-finding.
Designing Clinical Trials from a Program Perspective
Nitin Patel, Co-Founder and Board Member, Cytel
In this webinar, we’ll provide an overview of the concepts of program optimization. As a case study, we will describe a phase II trial design based on program-level optimization. We utilize a hybrid Bayesian-frequentist framework to evaluate the impact of phase II design choices on the probability of phase III success, clinical utility, time to market, trial costs and expected net present value (ENPV) of the product. These factors include phase II sample size, go-no go and dose selection decision rules for phase III, and phase III sample size. Using neuropathic pain as an example, we use simulations to illustrate the framework and show the benefit of including these factors in the overall decision process.