mapbayr
The `mapbayr` package is a tool for use within the R programming environment. It aims to enhance the model-informed precision dosing (MIPD) approach by offering a means to perform maximum a posteriori Bayesian estimation (MAP-BE) of pharmacokinetic (PK) parameters. This package operates with any population PK model formulated in `mrgsolve`, a feature that underscores its versatility and applicability across a broad range of pharmacokinetic studies.
In addition to its core estimation capabilities, `mapbayr` also offers functionalities for data formatting and reporting and the development of standalone Shiny web applications for MIPD purposes. These features make it a comprehensive tool that does not require additional software beyond R, facilitating broader access to advanced PK parameter estimation techniques within the research and clinical community. Overall, `mapbayr` emerges as a robust and reliable solution for MAP-BE of PK parameters in R, capable of matching or surpassing existing tools like NONMEM under certain conditions.
Topic
Drug metabolism;Metabolomics;Small molecules;Statistics and probability
Detail
Operation: Protein structure validation;Standardisation and normalisation
Software interface: Library
Language: R, C++
License: The GNU General Public License v3.0
Cost: Free with restrictions
Version name: -
Credit: -
Input: -
Output: -
Contact: chatelut.etienne@iuct-oncopole.fr
Collection: -
Maturity: -
Publications
- Easy and reliable maximum a posteriori Bayesian estimation of pharmacokinetic parameters with the open-source R package mapbayr.
- Le Louedec F, et al. Easy and reliable maximum a posteriori Bayesian estimation of pharmacokinetic parameters with the open-source R package mapbayr. Easy and reliable maximum a posteriori Bayesian estimation of pharmacokinetic parameters with the open-source R package mapbayr. 2021; 10:1208-1220. doi: 10.1002/psp4.12689
- https://doi.org/10.1002/PSP4.12689
- PMID: 34342170
- PMC: PMC8520754
Download and documentation
Source: https://github.com/FelicienLL/mapbayr/releases/tag/v0.5.0
Documentation: https://cran.r-project.org/web/packages/mapbayr/mapbayr.pdf
Home page: https://github.com/FelicienLL/mapbayr
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