Webinar: MCP-Mod – Theory, Implementation and Extensions

Events

  • 08 May 2019
  • Webinar
  • Organiser: Promoting Statistical Insight
  • Event Details

To learn more about this upcoming Webinar please visit the Promoting Statistical Insight website.

Dates: 08 – 08 May, 2019

Cytel sponsored webinar in association with PSI

Time: 14:00 - 15:30 UK time

MCP-Mod (Multiple Comparisons & Modelling) is a popular statistical methodology for model-based design and analysis of dose finding studies. This webinar will describe the theory behind MCP-Mod (plus extensions), and how to implement it within available software. Pantelis Vlachos (Cytel) will provide a brief introduction to the methodology and illustrate the MCP-MoD capabilities in EAST 6.5. Saswati Saha (Inserm, Aix-Marseille University) will discuss new variations and alternatives to MCP-Mod and show how to implement them in R. Neal Thomas (Pfizer) will present further technical details of MCP-Mod by evaluating the method using results from least squares linear model theory.

Abstracts:

Pantelis Vlachos (Cytel Inc.): MCP-Mod in East®: Early development dose-finding design and analysis

Bio: Pantelis is Director/Strategic Consultant for Cytel, Inc. based in Geneva. He joined the company in January 2013. Before that, he was a Principal Biostatistician at Merck Serono as well as a Professor of Statistics at Carnegie Mellon University for 12 years. His research interests lie in the area of adaptive designs, mainly from a Bayesian perspective, as well as hierarchical model testing and checking although his secret passion is Text Mining. He has served as Managing Editor of the journal “Bayesian Analysis” as well as editorial boards of several other journals and online statistical data and software archives.

Neal Thomas (Pfizer Inc.): Understanding MCP-Mod dose finding as a method based on linear regression

Bio: Neal received a PhD in Statistics from the University of Chicago. He is the leader of the Statistical Research and Innovation center at Pfizer working on clinical and non-clinical applications in several therapeutic areas. Previous work experience includes sample surveys, educational statistics (ETS), and health policy applications. Statistical research interests include design of observational studies, dose response, missing data methods, matrix sampling, psychometric models, and Bayesian statistics.

Saswati Saha (Inserm, Aix-Marseille University): Model based dose-finding methods in Phase II clinical trials

Bio: Saswati completed her Ph.D as a part of IDEAS network on December 2018 from the Competence Center for Clinical Trials (KKSB) at University of Bremen under the supervision of Professor Werner Brannath. Her primary areas of research during her PhD were dose response modelling, multiple testing, drug combination studies, dose finding and confidence interval estimation for target doses in drug development.

Saswati studied at the Indian Statistical Institute, where she completed her Bachelor’s degree (2011) and Master’s degree (2013) in Statistics. After her masters she worked on credit risk modelling in two renowned financial institutions, Ernst & Young and Genpact, for two years and dealt with time series modelling for stress testing and logistic regression modelling for building scorecards.

The webinar is free to register, and to do so, please go here. If you wish to hear more about the event itself, please click here to download the details.

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