PKconverter
PKconverter converts and computes pharmacokinetic parameters in R to characterize drug absorption, distribution, metabolism, and excretion for population and individual pharmacokinetic analyses.
Key Features:
- R implementation: Provided as an R package for computational pharmacokinetic parameter conversion and calculation.
- Parameter conversion and computation: Calculates various pharmacokinetic parameters based on established functional interrelationships.
- Post‑model derivation: Computes additional parameters that are not directly estimated within a fitted pharmacokinetic model by deriving them from existing estimates.
- Standard error estimation: Calculates standard errors associated with derived pharmacokinetic parameters.
- Population and individual estimation: Supports estimation of both population-level and individual patient-specific pharmacokinetic parameters, including simultaneous estimation of individual parameters.
Scientific Applications:
- Population pharmacokinetic analysis: Enables derivation and reporting of population-level pharmacokinetic parameters from model estimates.
- Individualized parameter estimation: Supports estimation of individual patient-specific parameters for personalized medicine analyses.
- Derived-parameter reporting: Facilitates computation of parameters not directly estimated in models to expand reported pharmacokinetic metrics.
- Uncertainty quantification: Provides standard errors for derived parameters to assess estimation precision.
Methodology:
Implemented as an R package that computes pharmacokinetic parameters from fitted pharmacokinetic model estimates using established functional relationships, calculates standard errors for derived parameters, and supports simultaneous estimation of individual patient-specific parameters.
Topics
Details
- License:
- GPL-2.0
- Programming Languages:
- R
- Added:
- 1/18/2021
- Last Updated:
- 1/23/2021
Operations
Publications
Cho H, Lee E. PKconverter: R package to convert the pharmacokinetic parameters. Translational and Clinical Pharmacology. 2019;27(2):73. doi:10.12793/tcp.2019.27.2.73. PMID:32055585. PMCID:PMC6989246.
PMID: 32055585
PMCID: PMC6989246
Funding: - National Research Foundation of Korea: 2015R1D1A1A01056790