person("Nicolas", "Luyckx", , "nicolas.luyckx@calvagone.com", role = c("aut", "cre"))
A generic, easy-to-use and intuitive
pharmacokinetic/pharmacodynamic (PK/PD) simulation platform based on R
packages 'RxODE' and 'mrgsolve'. CAMPSIS provides an abstraction layer
over the underlying processes of writing a PK/PD model, assembling a
custom dataset and running a simulation. CAMPSIS has a strong
dependency to the R package 'campsismod', which allows to read/write a
model from/to files and adapt it further on the fly in the R
environment. Package 'campsis' allows the user to assemble a dataset
in an intuitive manner. Once the user’s dataset is ready, the package
is in charge of preparing the simulation, calling 'RxODE' or
'mrgsolve' and returning the results, for the given model, dataset and
desired simulation settings.
assertthat, dplyr, ggplot2, MASS, methods, plyr, progress,
purrr, rlang, stats, tibble, tidyr
'global.R' 'utilities.R' 'check.R' 'generic.R' 'seed.R'
'distribution.R' 'dataset_config.R' 'time_entry.R' 'occasion.R'
'occasions.R' 'treatment_iov.R' 'treatment_iovs.R'
'dose_adaptation.R' 'dose_adaptations.R' 'treatment_entry.R'
'treatment.R' 'observations.R' 'observations_set.R'
'covariate.R' 'covariates.R' 'bootstrap.R' 'protocol.R' 'arm.R'
'arms.R' 'event.R' 'events.R' 'scenario.R' 'scenarios.R'
'simulation_engine.R' 'dataset.R' 'parameter_uncertainty.R'
'event_logic.R' 'simulation_progress.R' 'dataset_summary.R'
'simulate_preprocess.R' 'simulate.R' 'results_processing.R'
'default_plot.R'

A generic, easy-to-use and intuitive
pharmacokinetic/pharmacodynamic (PK/PD) simulation platform based on R
packages 'rxode2', 'RxODE' and 'mrgsolve'. CAMPSIS provides an
abstraction layer over the underlying processes of writing a PK/PD
model, assembling a custom dataset and running a simulation. CAMPSIS
has a strong dependency to the R package 'campsismod', which allows to
read/write a model from/to files and adapt it further on the fly in
the R environment. Package 'campsis' allows the user to assemble a
dataset in an intuitive manner. Once the user’s dataset is ready, the
package is in charge of preparing the simulation, calling 'rxode2',
'RxODE' or 'mrgsolve' (at the user's choice) and returning the
results, for the given model, dataset and desired simulation settings.
assertthat, digest, dplyr, ggplot2, MASS, methods, plyr,
progress, purrr, rlang, stats, tibble, tidyr
bookdown, devtools, gridExtra, knitr, mrgsolve, pkgdown,
rmarkdown, roxygen2, RxODE, rxode2, stringr, testthat