Using CTS and PK-PD models to predict the effect of uncertainty about population parameters on clinical trial power.
- Author:
Ling ZHU
1
;
Xinling SHI
;
Yajie LIU
Author Information
1. Department of Electronic Engineering, Information School, Yunnan University, Kunming 650091, China.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Clinical Trials as Topic;
methods;
Computer Simulation;
Data Interpretation, Statistical;
Humans;
Models, Biological;
Monte Carlo Method;
Pharmacokinetics;
Pharmacology;
Uncertainty
- From:
Journal of Biomedical Engineering
2009;26(1):42-62
- CountryChina
- Language:Chinese
-
Abstract:
The traditional clinical trail designs always depend on expert opinions and lack statistical evaluations. In this article, we present a method and illustrate how population parameter uncertainty may be incorporated in the overall simulation model. Using the techniques of clinical trail simulation (CTS) and setting up predictions on the basis of pharmacokinetics-pharmacodynamics (PK-PD) models, we advance the modeling methods for simulation, for treatment effects, and for the clinical trail power under the given PK-PD conditions. Then we discuss the model of uncertainty, suggest an ANOVA-based method, add eta2 statistics for sensitivity analysis, and canvass the effect of uncertainty about population parameters on clinical trail power. The results from simulations and the indices derived from this type of sensitivity analysis may be used for grading the influence on the prediction quality of uncertainty about different population parameters. The experiment results are satisfactory and the approach presented has practical value in clinical trails.
