Certara.RDarwin (version 1.1.1)

create_ModelPK: Get the list of objects describing the PML models by set of PK parameters

Description

This function provides the PML (Pharmacometric Modelling Language) PK parameter sets based on the specified options. They are available as a list of specific S3 classes.

Usage

create_ModelPK(
  CompartmentsNumber = 1,
  Absorption = "Intravenous",
  Parameterization = "Clearance",
  Saturation = FALSE,
  EliminationCpt = FALSE,
  FractionExcreted = FALSE,
  ByVector = FALSE,
  ClosedForm = TRUE,
  ...
)
get_PMLParametersSets(
  CompartmentsNumber = 1,
  Absorption = "Intravenous",
  Parameterization = "Clearance",
  Saturation = FALSE,
  EliminationCpt = FALSE,
  FractionExcreted = FALSE,
  ByVector = FALSE,
  ClosedForm = TRUE,
  ...
)

Value

A list of PML models (PMLModels class instance) matching the specified options.

Arguments

CompartmentsNumber

The number of compartments in the model. Supported embedded models are 1-, 2-, 3-compartments. Default is 1.

Absorption

The absorption type of the model. Supported types are:

• Intravenous (Default) - Dose is given in the main compartment (A1) directly.

• First-Order - Dose is absorbed to the main compartment (A1) from the absorption compartment (Aa) by first-order kinetic.

• Gamma - Dose is absorbed to A1 by Gamma Distributed delay kinetic.

• Inverse Gaussian - Dose is absorbed to A1 by Inverse Gaussian Distributed delay kinetic.

• Weibull - Dose is absorbed to A1 by Weibull Distributed delay kinetic.

Parameterization

The parameterization type. Possible options are Clearance - Clearance parameters: Cl, Cl2 to be used and Micro - Micro parameters: Ke, K12, K21 to be used. Default is Clearance.

Saturation

Logical indicating whether saturation should be considered. Default is FALSE.

EliminationCpt

Logical indicating whether elimination compartment should be included. Default is FALSE.

FractionExcreted

Logical indicating whether fraction excreted structural parameter should be included in urinecpt statement: urinecpt(A0 = Cl * C, fe=Fe). Valid only if EliminationCpt == TRUE. Default is FALSE.

ByVector

Logical indicating whether each element in vectorized argument should be treated as a separate PML structure (i.e. treated as data.frame vectors), TRUE, or as parameters to obtain a pool (i.e. expanded) of PML structures, FALSE. Default is FALSE (one value for a function call).

ClosedForm

Logical indicating whether closed forms (cfMicro) should be used when possible. Note that closed forms are not available for the models with elimination compartment, models with saturation or absorption types other than Intravenous or First-Order. The models with interpolated covariates must use ClosedForm == FALSE. Default is TRUE (one value for a function call).

...

Additional named arguments, including Structural parameters (StParm), Covariates, Dosepoints (for PK models), Thetas and Omegas. See 'Additional arguments' section.

Additional arguments

Additional arguments (ellipsis) will be applied sequentially. They can be used to add or modify Structural parameters (StParm), Covariates, Observations, Dosepoints (for PK models); by the way it is advised to use specific functions for it (see 'See Also' section for the references). Also it is possible to modify Omegas and Thetas, but it is impossible to add them (they are parts of other structures). If PMLStructure argument is not specified, class instances will be modified or added in all PML structures. If PMLStructure argument is specified, class instances in the specified PML structure will be modified/added. Note that only one PML structure could be added to the class instance. If multiple structures should be modified, suggest to use specific functions.

Details

The names of PMLStructure are constructed by the following parts:

• Model type ('PK'),

• Compartments number

• Abbreviated absorption type:

  • 'IV' for Intravenous,

  • 'FO' for First-Order,

  • 'G' for Gamma,

  • 'W' for Weibull,

  • 'IG' for Inverse Gaussian,

• Abbreviated parameterization ('C' for Clearance and 'M' for Micro),

• Abbreviated saturation if presented ('S'),

• Abbreviated elimination if presented ('E'),

• Abbreviated fraction excreted if presented ('F').

See Also

Functions used for Dosepoint specification: Dosepoint(), modify_Dosepoint()

Functions used for StParm specification: StParm(), add_StParm(), create_ModelPD(), modify_StParm(), modify_StParmCustom(), remove_StParm()

Functions used for Observation specification: Observation(), ObservationCustom(), Sigmas(), create_ModelPD(), modify_Observation(), remove_Observation()

Functions used for Omega specification: Omega(), create_ModelPD(), modify_Omega()

Functions used for Theta specification: InitialEstimate(), Theta(), create_ModelPD(), modify_Theta()

Functions used for Covariate specification: Covariate(), add_Covariate(), create_ModelPD(), remove_Covariate()

Examples

# Get PK model set with default options
PMLParametersSets <- create_ModelPK()

#' # Get PK Model search with custom options:
# will create 2 PML Parameters Sets with 2 and 3 compartments,
# with Absorption First-Order and Gamma accordingly:
ModelPKSearch <-
  create_ModelPK(CompartmentsNumber = c(2, 3),
                 Parameterization = "Micro",
                 Absorption = c("First-Order", "Gamma"),
                 ByVector = TRUE,
                 ClosedForm = TRUE)


# Next example will create a set of 4 PMLParametersSets:
# a combination of models with 2 and 3 compartments and First-Order and Gamma Absorption
PMLParametersSets <-
  create_ModelPK(CompartmentsNumber = c(2, 3),
                 Absorption = c("First-Order", "Gamma"),
                 ByVector = FALSE,
                 ClosedForm = FALSE)

# Create 2 PML Parameters Sets with elimination compartment and fraction excreted
# and add zero order absorption to the main dosepoint of the PML Structure
# with infusion
PMLParametersSets <-
  create_ModelPK(CompartmentsNumber = 1,
                 Absorption = c("Intravenous", "Gamma"),
                 EliminationCpt = TRUE,
                 FractionExcreted = TRUE,
                 duration = StParm(StParmName = "Duration",
                                   OmegaStParm = Omega(State = "None")),
                                   PMLStructure = "PK1IVCEF")

# Create 4 PML Parameters Sets, then modify `Cl` structural parameter for all sets,
# with 2 initial estimates sets to be searched,
# add `tlag` as a structural parameter `Tlag` to 1 compartment First-Order PML parameters set,
# change `tvKa` Theta initial estimate,
# change `nV` Omega initial estimate,
# change `CObs` Observation sigmas,
# add structural parameter `Rate` for 1 compartment Weibull Parameters set,
# add `Weight` covariate for all structural parameters to be searched.

PMLParametersSets <-
   create_ModelPK(
     CompartmentsNumber = 1,
     Absorption = c("First-Order", "Weibull"),
     ByVector = FALSE,
     Cl = StParm(
       StParmName = "Cl",
       Type = "LogNormal2",
       ThetaStParm =
         Theta(Name = "tvCl",
               InitialEstimates =
                 InitialEstimate(c(-Inf, 0.2, Inf),
                                 c(0, 3, 10)))
     ),
     tlag = StParm(
       StParmName = "Tlag",
       State = "Searched",
       PMLStructure = "PK1FOC",
       Covariates = list(
         Age = Covariate(
           Name = "Age",
           Type = "Categorical",
           State = "Searched",
           Direction = "Backward",
           Center = "None",
           Categories = c(1, 2, 3)
         )
       )
     ),
     tvKa = Theta(Name = "tvKa", InitialEstimates = 10),
     nV = Omega(Name = "nV", InitialOmega = 0.1),
     CObs = Observation(
       ObservationName = "CObs",
       SigmasChosen = list(
         AdditiveMultiplicative = c(PropPart = 0.1, AddPart = 2),
         Proportional = 1
       )
     ),
     A1 = Dosepoint(
       DosepointName = "A1",
       rate = StParm(StParmName = "Rate"),
       PMLStructure = "PK1WC"
     ),
     Weight = Covariate(
       Name = "Weight",
       State = "Searched",
       Center = "Median"
     )
   )