MI260: Bayesian Model-Based Meta-Analysis to Support Decision Making in Drug Development (2 CR)
Product Description
August 19-20, 2010
MI260 provides an introduction to model-based meta-analysis of summary data or a combination of summary and individual data from clinical trials to support decision-making in clinical drug development. Upon completion of the course, participants will be able to design a model-based meta-analysis of clinical trial data to address strategic decisions in a clinical drug development program and implement it using a Bayesian approach executed with WinBUGS and R. The course includes hands-on experience in constructing models for the relationship between an efficacy- or safety-related clinical outcome and independent variables such as dose, time and patient characteristics by analysis of summary data from multiple studies, e.g., treatment means and standard deviations, as well as by analysis of a combination of summary and individual data. In addition participants will learn to execute and interpret population simulations to support decision-making in clinical drug development. Participants may apply the 2 credit hours from this course to the Metrum Institute Certificate Program in Pharmacometrics.
Prerequisites: Experience with PK-PD modeling and some familiarity and hands-on experience with nonlinear regression, mixed-effects modeling, Bayesian modeling using WinBUGS, and use of R (or S-PLUS). Applicable MI courses include: MI200, MI205 (formerly MI220) and MI250, or contact us.
Computer Hardware/Software: This course requires a Windows laptop computer with an available USB 2.0 port. All required software used for hands-on examples will be freeware/open-source software and simple instructions will be provided for users to configure their computers before the course.
Location: College of the Atlantic, 105 Eden Street, Bar Harbor, ME
MI260 provides an introduction to model-based meta-analysis of summary data or a combination of summary and individual data from clinical trials to support decision-making in clinical drug development. Upon completion of the course, participants will be able to design a model-based meta-analysis of clinical trial data to address strategic decisions in a clinical drug development program and implement it using a Bayesian approach executed with WinBUGS and R. The course includes hands-on experience in constructing models for the relationship between an efficacy- or safety-related clinical outcome and independent variables such as dose, time and patient characteristics by analysis of summary data from multiple studies, e.g., treatment means and standard deviations, as well as by analysis of a combination of summary and individual data. In addition participants will learn to execute and interpret population simulations to support decision-making in clinical drug development. Participants may apply the 2 credit hours from this course to the Metrum Institute Certificate Program in Pharmacometrics.
Prerequisites: Experience with PK-PD modeling and some familiarity and hands-on experience with nonlinear regression, mixed-effects modeling, Bayesian modeling using WinBUGS, and use of R (or S-PLUS). Applicable MI courses include: MI200, MI205 (formerly MI220) and MI250, or contact us.
Computer Hardware/Software: This course requires a Windows laptop computer with an available USB 2.0 port. All required software used for hands-on examples will be freeware/open-source software and simple instructions will be provided for users to configure their computers before the course.
Location: College of the Atlantic, 105 Eden Street, Bar Harbor, ME
