The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
As a part of Cytel’s "New Horizons Webinar Series", Alind Gupta, Senior Data Scientist, presents case studies from his research on applying machine learning for predictive analysis and evidence generation.
The biopharmaceutical and healthcare industries now collect more data than ever before due to advances in the variety of information sources combined with the ability to store vast quantities of diverse data. Sophisticated machine learning (ML) and AI techniques allow us to access and analyze any combination of a multitude of data sources. The way that traditional controlled sources are viewed is being adapted in light of new evidence that emerges from real-world data. In his presentation, Alind introduces us to the concept of ML and Causal Inference and discusses case studies from randomized clinical trials and real-world data.
Click the button to register for the on demand webinar.
Platform trials are a new type of clinical trials where multiple interventions can be evaluated simultaneously against a common control group within a single master protocol. Platform trial designs are an extension of adaptive trial designs that are sometimes referred to as a multi-arm, multi-stage (MAMS) design, as multiple interventions (‘‘multi-arm’’) undergoing multiple interim evaluations (‘‘multi-stage’’) are part of the design features.
This autumn Cytel has been holding a number of webinars on Platform Trials, ranging from a discussion with Cyrus Mehta on statistical innovations to incentivize more sponsors to consider platform trials, to next week's event with Jason Connor (Confluence) on the use of Bayesian methods for these innovative trial designs.
In a recent webinar Jay Park, Director of Trials Research for Cytel in Canada, presented a webinar to review the concept of platform trials and discuss important design considerations for platform trials. Jay is the author of several leading papers on Platform Trials, including one in CA: A Cancer Journal for Clinicians, the journal with the world's highest impact factor. He has also produced a complimentary primer on the subject which you can download here.
Continue reading this blog to get a summary of his talk. Click the button to access the on demand webinar.
Measuring treatment effect during a clinical trial is often the source of much debate, particularly during rare disease trials that must stimulate investigations using small samples. Unlike statistically significant results, for which there are many tests, meaningful measures of treatment effect are still under development (Kieser 2012). Cytel statistician Ursula Garczarek wonders whether this holds true in the realm of small samples and small target populations. After all, does the summary statistic in such a small trial rely on many assumptions that might not correlate with reality?
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.
Pharmaceutical and biotech companies are under pressure to deliver more and deliver faster with fewer resources. The cost of drug development, failure rate and human cost associated with prolonged participation in a trial turn out to be steep in case of an ineffective trial. As the industry seeks new levels of clinical trial efficiency and probability of success, more companies are looking to use advanced, innovative and computationally intensive designs like Bayesian methods.
Bayesian methods are of growing interest to the drug development industry, as they allow clinical investigators to leverage historical trial data as well as learnings from new data as it accrues throughout a trial. The result is better-informed decision making, greater program flexibility, and the ability to run smaller, more resource-efficient trials.
Cytel’s New Horizons Webinar Series introduces you to the latest innovations in statistical trial design. This webinar from the series is presented by Dr. Yuan Ji, a consultant for Cytel. Yuan is the founder of Laiya Consulting and currently is the Professor of Biostatistics at The University of Chicago. In his presentation, Professor Ji introduces the U-Design version 1.4, which mainly consists of a new module of dose-finding trial designs with joint efficacy and toxicity outcomes.
Click the button to register for the next webinar in this series, presented by Cytel's Ursula Garczarek. Ursula will be presenting a case study on the value of detailed clinical trial simulations for rare diseases.
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.
Innovation in trial designs are offering new routes forward for organizations of any size. They are now also aligned with the overarching goals of improved clinical development, better pre-planning, greater patient safety, less medical waste, and/or increased knowledge.
Cytel is hosting "New Horizons Webinar Series" that will introduce biostatisticians to the latest innovations in statistical trial design. The first webinar in the series on Adaptive Multi-arm Multi-stage Clinical Trials is going to be presented by Cytel's President & Co-Founder, Cyrus Mehta. Click on the button to register.