This course will discuss, and propose methods to address, key statistical issues leading to the problems currently observed in dose finding studies.  A review of basic multiple comparisons and modeling methods, will be included, as traditionally used in these studies. A unified strategy for designing and analyzing dose finding studies, denoted MCP-Mod, combining multiple comparisons and modeling, will be the focus of the course. MCP-Mod received a positive CHMP qualification opinion in January 2014, as an efficient statistical methodology for model-based design and analysis of phase II dose finding studies under model uncertainty. It will be discussed in detail, including a step-by-step description of its practical implementation. An extension of MCP-Mod will be described for count data, time-to-event endpoints as well as situations involving generalized non-linear models, linear and non-linear mixed effects models, and Cox proportional hazards models. A short reference will be made to another extension of the comprehensive multiple comparisons and modeling framework to confirmatory testing in dose-response studies using MCP-Mod. Case studies based on real clinical trials, together with concrete examples of code in R based on the Dose Finding package available on CRAN, will be used to illustrate the practical use of the methodology.

Instructors:
Frank Bretz, PhD
Global Head of Statistical Methodology
Novartis Pharma AG, Switzerland

Jose C. Pinheiro, PhD
Senior Director, Quantitative Decision Strategies
Janssen Research & Development, LLC, United States

Bjoern Bornkamp, PhD,
MSc Expert Statistical Methodologist - Integrated Information Sciences
Novartis Pharma AG, Switzerland

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