Package: Certara.RsNLME 3.0.1

Certara.RsNLME: Pharmacometric Modeling

Facilitate Pharmacokinetic (PK) and Pharmacodynamic (PD) modeling and simulation with powerful tools for Nonlinear Mixed-Effects (NLME) modeling. The package provides access to the same advanced Maximum Likelihood algorithms used by the NLME-Engine in the Phoenix platform. These tools support a range of analyses, from parametric methods to individual and pooled data analysis <https://www.certara.com/app/uploads/2020/06/BR_PhoenixNLME-v4.pdf>. Execution is supported both locally or on remote machines.

Authors:James Craig [aut, cre], Michael Tomashevskiy [aut], Vitalii Nazarov [aut], Shuhua Hu [ctb], Soltanshahi Fred [aut], Certara USA, Inc. [cph, fnd]

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Certara.RsNLME/json (API)

# Install 'Certara.RsNLME' in R:
install.packages('Certara.RsNLME', repos = c('https://certara-jcraig.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/certara/r-rsnlme/issues

Datasets:
  • OneCpt_IVInfusionData - Pharmacokinetic dataset containing 100 subjects with single dose given by infusion
  • pkData - Pharmacokinetic dataset containing 16 subjects with single bolus dose
  • pkcovbqlData - Pharmacokinetic pediatric dataset containing 80 subjects with single bolus dose.
  • pkpdData - Pharmacokinetic/Pharmacodynamic dataset containing 200 subjects with single bolus dose

On CRAN:

2.23 score 34 scripts 90 exports 35 dependencies

Last updated 22 hours agofrom:90f6dbd85d. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 21 2024
R-4.5-winOKNov 21 2024
R-4.5-linuxOKNov 21 2024
R-4.4-winOKNov 21 2024
R-4.4-macOKNov 21 2024
R-4.3-winOKNov 21 2024
R-4.3-macOKNov 21 2024

Exports:acceptAllEffectsaddADDLaddCovariateaddDoseCycleaddExtraDefaddInfusionaddLabeladdMDVaddResetaddSecondaryaddSteadyStateaddTablesToColumnMappingbootstrapBootstrapParamscancelJobcheckHostParamscolMappingcopyModelCovariateEffectModelcovariateModelcovariateNamescreate_model_from_metamodelcreateModelInfodataMappingdoseNameseditModelemaxmodelengineParamsextract_mmdlextraDoseLinesextraDoseNamesfitmodelfixedEffectgetRandomEffectNamesgetThetashostParamsinitFixedEffectsinitFixedEffects<-linearmodellistCovariateEffectNamesloadModelmodelVariableNamesNlmeDatasetNlmeEngineExtraParamsNlmeJobStatusNlmeObservationVarNlmeParallelHostNlmeParallelMethodNlmePmlModelNlmeRemoteExecutorNlmeScenarioNlmeSimTableDefNlmeSimulationParamsNlmeTableDefNlmeUserAuthenticationNlmeVpcParamsobservationNamesobtain_NLMELicenseparse_NLMEHostsparsePMLColMappkemaxmodelpkindirectmodelpklinearmodelpkmodelProfileParametersprofilePertubateProfileVarrandomEffectremove_NLMELicenseremoveCovariateResetColumnInforesidualEffectNamesresidualErrorrun_metamodelRunProfilePertubationsaveModelsaveUpdatedMetamodelsecondaryParameterNamesshotgunSearchsimmodelSortColumnssortfitStepwiseParamsstepwiseSearchstructuralParameterstructuralParameterNamestableParamstextualmodelvpcmodelwriteDefaultFiles

Dependencies:askpassassertthatbackportsbase64urlbatchtoolsbrewCertara.NLME8checkmateclicrayoncredentialscurldata.tabledigestfsgluehmsjsonlitelifecycleopensslpkgconfigplyrprettyunitsprogressR6rappdirsRcppreshaperlangsshstringisysvctrswithrxml2

Readme and manuals

Help Manual

Help pageTopics
Adds ADDL extra column definition to model objectaddADDL
Add covariate to model objectaddCovariate
Adds a dosing cycle to modeladdDoseCycle
Adds user defined extra column/table definitions to column definition fileaddExtraDef
Change existing dosing compartment to infusionaddInfusion
Add levels and labels to categorical or occasion covariateaddLabel
Adds MDV extra column definition to model objectaddMDV
Adds reset instructions to the modeladdReset addReset,NlmePmlModel-method
Adds a secondary parameter to model definitionaddSecondary addSecondary,NlmePmlModel-method
Adds Steady State extra column definition to model objectaddSteadyState
Executes an NLME Bootstrapbootstrap
Generic function for cancelling a jobcancelJob cancelJob,SimpleNlmeJob-method
Add column mappingscolMapping
Copy model object to iterate over base modelcopyModel
Return covariate namescovariateNames
Parse the model and get the list of termscreateModelInfo
Initialize input data for PK/PD modeldataMapping
Return dose namesdoseNames
Directly edit PML text in model objecteditModel
Create an Emax or Imax modelemaxmodel
Specify engine parameters for model executionengineParams
Return extra dose linesextraDoseLines
Return extra dose namesextraDoseNames
Executes an NLME simple estimationfitmodel
Specifies the initial values, lower bounds, upper bounds, and units for fixed effects in a modelfixedEffect
Return random effect names in modelgetRandomEffectNames
Return theta names and valuesgetThetas
Initialize for NlmeParallelHosthostParams
Display/Set initial estimates for fixed effectsinitFixedEffects initFixedEffects,NlmePmlModel-method initFixedEffects<- initFixedEffects<-,NlmePmlModel-method
Create linear modellinearmodel
Lists covariate effect names in the modellistCovariateEffectNames listCovariateEffectNames,NlmePmlModel-method
Return model variable namesmodelVariableNames
Obtain NLME Licenseobtain_NLMELicense
Pharmacokinetic dataset containing 100 subjects with single dose given by infusionOneCpt_IVInfusionData
Embed column definition info into the modelparsePMLColMap
Pharmacokinetic pediatric dataset containing 80 subjects with single bolus dose.pkcovbqlData
Pharmacokinetic dataset containing 16 subjects with single bolus dosepkData
Create a PK/Emax or PK/Imax modelpkemaxmodel
Create a PK/Indirect response modelpkindirectmodel
Create PK linear modelpklinearmodel
Creates a PK modelpkmodel
Pharmacokinetic/Pharmacodynamic dataset containing 200 subjects with single bolus dosepkpdData
Print generic for class NlmePmlModelprint.NlmePmlModel
Sets or updates the covariance matrix of random effectsrandomEffect
Remove NLME Licenseremove_NLMELicense
Remove covariate from structural parameters in a model object.removeCovariate
Return residual effect terms available in modelresidualEffectNames
Assign residual error model to model objectresidualError
Get secondary parameter namessecondaryParameterNames
Executes an NLME shotgun covariate searchshotgunSearch
Executes an NLME simulationsimmodel
Executes an NLME simple estimation with sort keys and given scenariossortfit
Executes an NLME stepwise covariate searchstepwiseSearch
Set structural parameter in model objectstructuralParameter
Get structural parameter namesstructuralParameterNames
Wrapper around NlmeTableDef/NlmeSimTableDef-classes initializers.tableParams
Create a textual model objecttextualmodel
Perform visual predictive check for NLME modelsvpcmodel