Knowledge creation data supplementation

E. I. Ette, H. M. Chu, and C. J. Godfrey, Data supplementation a pharmacokinetic pharmacodynamic knowledge creation approach for characterizing an unexplored region of the response surface. Pharm Res 22 523-531 (2005). 

Pharmacokinetic/pharmacodynamic (PK/PD) knowledge creation is the process of building on current understanding of data that is already acquired by generating more data (information) that can be translated into knowledge. It entails the use of (valid) models to synthesize data, estimate inestimable uncertainty, or supplement data for further knowledge acquisition (1, 2). 

In the sections that follow types of PK/PD knowledge creation, general steps in the knowledge creation process, data supplementation and the motivation for it, data supplementation procedure, nonparametric approximate Bayesian data supplementation method, structure-based multiple supplementation with a motivating example, and implications of the use of multiple data supplementation for the characterization of an unexplored region of the response are described. The emphasis in this chapter is on the use of data supplementation to characterize unexplored region of the response surface. A discussion on data synthesis, the qualitative characterization of the response surface, and the estimation of inestimable uncertainty has been elegantly presented by Williams et al. (1) and Ette and Onyiah (5). Therefore, these approaches are discussed in brief in the sections that follow. 

PK/PD knowledge creation from a clinical trial data set is a process that can be formalized into a number of steps. In this section we provide a general framework for the steps needed to be taken in the PK/PD knowledge creation process. These steps could vary depending on the type of knowledge creation approach involved. Subsequently, data supplementation—the PK/PD knowledge creation approach of focus in this chapter—is discussed. 

Step 3. Performance of knowledge creation (i.e., data synthesis, estimation of inestimable uncertainty, or data supplementation). 

The rest of this chapter focuses on the data supplementation approach for PK/PD knowledge creation. 

PK/PD knowledge creation via data supplementation results in the further acquisition of knowledge beyond that embedded in one s data. When data supplementation for PK/PD knowledge creation is implemented, the result is a greatly improved understanding of the response surface because of the knowledge created. This in turn leads to efficient design studies. 

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