|
Activity Number:
|
607
- Effective Application of Modeling, Simulation and Knowledge Sharing in Drug Development
|
|
Type:
|
Topic Contributed
|
|
Date/Time:
|
Thursday, August 1, 2019 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Statistics and Pharmacometrics Interest Group
|
|
Abstract #302971
|
Presentation
|
|
Title:
|
Meta-Data and Software for Bayesian Emax Dose Response Models
|
|
Author(s):
|
Neal Thomas*
|
|
Companies:
|
Pfizer
|
|
Keywords:
|
Bayesian;
Emax;
meta-data;
R package
|
|
Abstract:
|
Meta-analyses and an R package for clinical dose response that support a Bayesian model-based approach to designs and analyses will be described. Meta-data from approximately 200 compounds will be briefly summarized. With few exceptions, the meta-data support the Emax model commonly recommended by clinical pharmacologists. Meta-analyses also yield an empirical basis for specifying prior distributions for the parameters in the difficult-to-estimate Emax model. We will conclude with an example utilizing the R package to demonstrate how the meta-analysis findings were applied to assess a proposed design for a recent study.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2019 program
|
