Analysis of pharmacokinetic (PK) data is concerned with defining the relationship between the dosing regimen and the body's exposure to drug as indicated by the concentration time curve to determine a dose. To analyze PK data, there are three categories of packages within CRAN: noncompartmental analysis (NCA), modeling (typically using compartmental analysis), and reporting (typically for NCA). NCA is used as method of description of PK with minimal assumptions of the rates of distribution of the drug through the body. NCA is typically used to describe the PK of a drug in clinical studies with many samples per subject on the same and sequential days. The NCA packages are:
- Provides basic computational functions for NCA.
- Allows estimation of pharmacokinetic parameters using non-compartmental theory. Both complete sampling and sparse sampling designs are implemented. The package provides methods for hypothesis testing and confidence intervals related to superiority and equivalence.
Modeling of PK data typically uses compartmental methods which assume that the drug enters the body either through an intravenous (IV) or extravascular (often oral or subcutaneous, SC) dose. Packages listed below are restricted to packages that have specific interest to PK modeling and not the (many) packages that support modeling that could be used for PK data. The PK modeling and simulation packages are:
- Provides simplified clinical pharmacokinetic functions for dose regimen design and modification at the point-of-care.
- Provides statistical methods involving PK measures for dose finding in Phase 1 clinical trials.
- Facilitates simulation from hierarchical, ordinary differential equation (ODE) based models typically employed in drug development.
- Is a package to understand the algorithms of NONMEM.
- Provides a graphical user interface for population pharmacokinetic model diagnosis from a variety of modeling fitting software, including NONMEM, Monolix, SAS, and R.
- Provides functions to evaluate common pharmacokinetic/pharmacodynamic models and their gradients.
- Provides a framework for simulation and optimization of pharmacokinetic-pharmacodynamic models at the individual and population level.
Communication of results is as important (or more important) than actually completing an analysis. While many users are currently using rmarkdown and knitr for general reporting, the features of packages which are important for reporting PK data are:
- Provides NCA for a report writer generating rtf and pdf output.
- Generates NCA data sets compliant to CDISC and other pharmacokinetic functions for reviewer.
- Provides automatic pipeline for users to visualize data and models with an archive-oriented management tool for users to store, retrieve and modify figures and graph generation based on lattice and ggplot2.