Cytel Blog

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.

Cytel scientists recently published a new eBook on synthetic control arms and a new scientific primer for the more technically advanced. Our new primer focuses on assessing the validity of data, the validity of methodology, and the modes of analysis and interpretation within this burgeoning field. Each of these is a crucial part of understanding how to make the most impact with a synthetic control. Read our blog to learn more about the eBook and the primer, and register to download both.

Cytel also conducted a webinar on Synthetic and External Controls in Clinical Trials with Dr. Kristian Thorlund, a Professor of Biostatistics at McMaster University and Senior Vice President of Real World Evidence at Cytel. In this webinar, Dr. Thorlund introduces synthetic control arms and discusses the validity of data, results and interpretations. He also answers several questions from the audience around sample size calculations, quality of datasets and use of synthetic controls in various kinds of clinical trials. Click on the button to get free access to the recording and the slides from the webinar.

On June 17, 2020, Cytel is conducting a webinar with Dr. Satrajit Roychoudhury, Senior Director, Statistical Research and Data Science Center, Pfizer. Dr. Roychoudhury will be talking 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 register 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.

Cytel has recently published a new ebook on synthetic control arms, and a new scientific primer as well.

In our previous blog, “Remote Working Arrangement – How to get it right?”, we talked about how the need for social distancing has led most of the employers, across the globe, to make work-from-home arrangements for their employees. As we continue to stay indoors and combat COVID-19, keeping aside some time every day to read and watch useful resources on important industry topics can be very helpful. Cytel's team of oncology trial design and advanced analytics experts have been hosting a series of complimentary webinars covering a range of innovative topics including adaptive design, machine learning, estimands and trial design software. In this post, we offer you a recap of the webinars we conducted in the past few weeks. You can register for the upcoming webinars in our oncology series by clicking on the button below.

Cytel's team of oncology trial design and advanced analytics experts are hosting a series of complimentary webinars covering a range of innovative topics and solutions. On April 28, 2020, Cytel conducted a webinar with Professor Martin Fey, Medical Oncologist, “A Clinician’s Perspective on Cancer Drugs Development”. Our previous blog features an interview with Professor Fey where he talks about his experience of over forty years in medical oncology, the evolution of clinical cancer trials, the difference between clinically meaningful and statistically significant results, the debate around patient perspectives and other important topics around cancer drugs development.

In his webinar, Professor Fey provides us an overview of drug development for cancer treatments, clinician’s perspective on endpoints, importance of patient reported outcomes and patient perspective, and the significance of biomarkers. Continue reading this post for key highlights from the webinar.

Access webinar slides and recording by clicking on the button below.

In our previous blog, we spoke with Alind Gupta, who works as a Machine Learning Researcher at Cytel in Canada. The interview gives you a deep dive into black-box models and transparent machine learning, and how the latter is becoming more important in clinical research today.

On March 21, Cytel conducted a webinar with Alind on, “Transparent Machine Learning in Oncology”. Alind presented our continuing work in immuno-oncology using Bayesian network models for predicting safety and survival outcomes, extrapolating from limited follow-up data and validating with external real-world data for key subgroups. Continue reading for key highlights from the webinar.

Register now to get free access to webinar slides and recording.

Cytel is hosting a webinar, “A Clinician’s Perspective on Cancer Drugs Development”, on April 28, 2020. Our speaker, Professor Martin Fey, Medical Oncologist from Switzerland, will brief us on treatment evolution and give us a deep dive into clinician perspective on endpoints, PRO and patients perspectives, and importance of biomarkers in oncology.

In this interview, we speak to Professor Fey about his experience of over forty years in medical oncology, the evolution of clinical cancer trials, the difference between clinically meaningful and statistically significant results, the debate around patient perspectives and other important topics around cancer drugs development.

Cytel is hosting a webinar on Transparent Machine Learning in Oncology, on April 21, 2020. Our speaker, Alind Gupta, Machine Learning specialist, will provide insights on a particular transparent ML method called Bayesian networks, and how we have been using it for HEOR and other real world applications in oncology trials. As the adoption of machine learning is on the rise, we speak to Alind about the differences between black-box models and transparent machine learning, and how the latter is becoming more important in clinical research today. Alind also speaks about the application of ML on real-world data and how it is going to evolve in the coming years.

Machine learning (ML) aims to discover patterns from data that can be used for prediction, but the use of “black-box” ML models in healthcare research and decision-making has been limited, due to clinical liability and lack of trust from stakeholders. FDA guidelines for ML-based devices mandate transparency to assure continual safety and efficiency as notable recent failures have prompted increasing ML research into bias, fairness and causality. This has ramifications for all therapeutic areas but particularly within oncology.