PKgraph: An R package for graphically diagnosing population pharmacokinetic models

  • Authors:

  • Xiaoyong Sun;Kai Wu;Dianne Cook

  • Affiliations:

  • Bioinformatics and Computation Biology Program, Department of Statistics, Iowa State University, Ames, Iowa 50011, USA;Novartis Institutes for BioMedical Research, Inc., 220 Mass. Ave., Cambridge, MA 02139, USA;Bioinformatics and Computation Biology Program, Department of Statistics, Iowa State University, Ames, Iowa 50011, USA

  • Venue:
  • Computer Methods and Programs in Biomedicine
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Abstract: Population pharmacokinetic (PopPK) modeling has become increasing important in drug development because it handles unbalanced design, sparse data and the study of individual variation. However, the increased complexity of the model makes it more of a challenge to diagnose the fit. Graphics can play an important and unique role in PopPK model diagnostics. The software described in this paper, PKgraph, provides a graphical user interface for PopPK model diagnosis. It also provides an integrated and comprehensive platform for the analysis of pharmacokinetic data including exploratory data analysis, goodness of model fit, model validation and model comparison. Results from a variety of modeling fitting software, including NONMEM, Monolix, SAS and R, can be used. PKgraph is programmed in R, and uses the R packages lattice, ggplot2 for static graphics, and rggobi for interactive graphics.