pkindirectmodel: Create a PK/Indirect response model

In Certara.RsNLME: Pharmacometric Modeling

Create a PK/Indirect response model

Description

Use to create a PK/Indirect response model.

Usage

pkindirectmodel(
  isPopulation = TRUE,
  parameterization = "Clearance",
  absorption = "Intravenous",
  numCompartments = 1,
  isClosedForm = TRUE,
  isTlag = FALSE,
  hasEliminationComp = FALSE,
  isFractionExcreted = FALSE,
  isSaturating = FALSE,
  infusionAllowed = FALSE,
  isDuration = FALSE,
  isSequential = FALSE,
  isPkFrozen = FALSE,
  hasEffectsCompartment = FALSE,
  indirectType = "LimitedStimulation",
  isBuildup = TRUE,
  isExponent = FALSE,
  indirectFrozen = FALSE,
  data = NULL,
  columnMap = TRUE,
  modelName = "",
  workingDir = "",
  ...
)

Arguments

isPopulation	Is this a population model TRUE or individual model FALSE?
parameterization	Type of parameterization. Options are "Clearance", "Micro", "Macro", or "Macro1".
absorption	Type of absorption. Options are "Intravenous", "FirstOrder", "Gamma", "InverseGaussian", "Weibull" .
numCompartments	Value of either 1, 2, or 3.
isClosedForm	Set to TRUE to convert model from a differential equation to close form.
isTlag	Set to TRUE to add a lag time parameter to the model.
hasEliminationComp	Set to TRUE to add an elimination compartment to the model.
isFractionExcreted	Set to TRUE if elimination compartment (hasEliminationComp = TRUE) contains a fraction excreted parameter.
isSaturating	Set to TRUE to use Michaelis-Menten kinetics for elimination. Only applicable to models with paramteterization = "Clearance"
infusionAllowed	Set to TRUE if infusions allowed.
isDuration	Set to TRUE if infusions use duration instead of rate (must also set infusionAllowed = TRUE).
isSequential	Set to TRUE to freeze PK fixed effects and convert the corresponding random effects into covariates as well as remove the PK observed variable from the model.
isPkFrozen	Set to TRUE to freeze PK fixed effects and remove the corresponding random effects as well as the PK observed variable from the model.
hasEffectsCompartment	Set to TRUE to include an effect compartment into the model.
indirectType	Type of drug actions for the indirect response model. Options are "LimitedStimulation", "InfiniteStimulation", "LimitedInhibition", "InverseInhibition", "LinearStimulation", or "LogLinearStimulation".
isBuildup	Set to FALSE to have the drug actions affect the loss/degradation instead of the production.
isExponent	Set to TRUE to add an exponent parameter to the drug action term.
indirectFrozen	Set to TRUE to freeze PD fixed effects and remove the corresponding random effects as well as the PD observed variable from the model.
data	Input dataset
columnMap	If TRUE (default) column mapping arguments are required. Set to FALSE to manually map columns after defining model using colMapping.
modelName	Model name for subdirectory created for model output in current working directory.
workingDir	Working directory to run the model. Current working directory will be used if workingDir not specified.
...	Arguments passed on to pkindirectmodel_MappingParameters ID Column mapping argument for input dataset column(s) that identify individual data profiles. Only applicable to population models isPopulation = TRUE. Time Column mapping argument that represents the input dataset column for the relative time used in a study and only applicable to time-based models. A1 Column mapping argument that represents the input dataset column for the amount of drug administered. Only applicable to the following types of models: Models with absorption = "Intravenous" and parameterization set to either "Clearance","Micro", or "Macro" Models with absorption set to either "Gamma", "InverseGaussian", or "Weibull" Aa Column mapping argument that represents the input dataset column for the amount of drug administered and only applicable to models with absorption = "FirstOrder". A Column mapping argument that represents the input dataset column for the amount of drug administered and only applicable to models with absorption = "Intravenous" and parameterization = "Macro1". A1_Rate Column mapping argument that represents the input dataset column for the rate of drug administered. Only applicable to the following types of models: Models with absorption = "Intravenous", infusionAllowed = TRUE and parameterization set to either "Clearance","Micro" or "Macro" Models with absorption set to either "Gamma", "InverseGaussian", or "Weibull" and infusionAllowed = TRUE A1_Duration Column mapping argument that represents the input dataset column for the duration of drug administered. Only applicable to the following types of models: Models with absorption = "Intravenous", infusionAllowed = TRUE with isDuration = TRUE and parameterization set to either "Clearance","Micro" or "Macro" Models with absorption set to either "Gamma", "InverseGaussian", or "Weibull" and infusionAllowed = TRUE with isDuration = TRUE Aa_Rate Column mapping argument that represents the input dataset column for the rate of drug administered and only applicable to models with absorption = "FirstOrder", infusionAllowed = TRUE. Aa_Duration Column mapping argument that represents the input dataset column for the duration of drug administered and only applicable to models with absorption = "FirstOrder", infusionAllowed = TRUE, and isDuration = TRUE. A_Rate Column mapping argument that represents the input dataset column for the rate of drug administered and only applicable to models with absorption = "Intravenous", infusionAllowed = TRUE, and parameterization = "Macro1". A_Duration Column mapping argument that represents the input dataset column for the duration of drug administered and only applicable to models with absorption = "Intravenous", infusionAllowed = TRUE, isDuration = TRUE, and parameterization = "Macro1". A1Strip Column mapping argument that represents the input dataset column for the stripping dose and only applicable to models with parameterization = "Macro". CObs Column mapping argument that represents the input dataset column for the observations of drug concentration in the central compartment and only applicable to models with parameterization being either set to either "Clearance" or "Micro". C1Obs Column mapping argument that represents the input dataset column for the observations of drug concentration in the central compartment and only applicable to models with parameterization being either set to either "Macro" or "Macro1". A0Obs Column mapping argument that represents the input dataset column for the observed amount of drug in the elimination compartment. (hasEliminationComp = TRUE). EObs Column mapping argument that represents the input dataset column for the observed drug effect. nV If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nV. nV2 If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nV2. nV3 If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nV3. nCl If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nCl. nCl2 If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nCl2. nCl3 If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nCl3. nKa If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nKa. nA If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nA. nAlpha If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nAlpha. nB If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nB. nBeta If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nBeta. nC If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nC. nGamma If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nGamma. nKe If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nKe. nK12 If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nK12. nK21 If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nK21. nK13 If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nK13. nK31 If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nK31. nTlag If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nTlag. nKm If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nKm. nVmax If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nVmax. nFe If isSequential = TRUE and isFractionExcreted = TRUE, mapped to the input dataset column that lists the values for random effect nFe. nMeanDelayTime If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nMeanDelayTime. nShapeParam If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nShapeParam. nShapeParamMinusOne If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nShapeParamMinusOne.

Value

NlmePmlModel object

Column mapping

Note that quoted and unquoted column names are supported. Please see colMapping.

Examples

model <- pkindirectmodel(
  parameterization = "Micro",
  data = pkpdData,
  ID = "ID",
  Time = "Time",
  A1 = "Dose",
  CObs = "CObs",
  EObs = "EObs"
)

# View PML Code
print(model)

Certara.RsNLME documentation built on April 3, 2025, 11:04 p.m.