Covariate Distribution Models in Simulation

Abstract

The components of a clinical trial simulation consist of the input–output model, the covariate distribution model, and the trial execution model. The input–output model consists of submodels that incorporate the drug’s pharmacokinetics and pharmacodynamics, the disease progression during the trial, the trial endpoints, and the residual variability. Some of these submodels may include covariate influences on model parameters, which comprise the covariate distribution model. Appropriate simulation of clinical trials requires appropriate simulation of covariates because generation of covariates from an invalid probability distribution may result in an inadequate distribution of the simulation output. Basically, you need the right inputs to get the right outputs. This chapter will define covariate distribution models, will show how internal and external datasets may be used to define an appropriate probability distribution, and will demonstrate how to model covariate distributions.