One of No|RateDose|DurationDose

Does dose point has bioavailability?

Bioavailability expression

Does dose have time lag?

Time lag expression

Optional Formula defines how to express duration in PML

Optional Formula defines how to express rate in PML

Code to execute before dose is administrated

Code to execute after dose is administrated

ValueType|ColumnType

Value of dosing parameter

Name of column containing dose information

Model variable name

Corresponding column name in the dataset

Model variable type

Name of covariate

Covariate value

Name of covariate parameter

Type of covariate parameter: Continuous|Category|Occasion

Curve fitting method: Forward|Interpolate|Backward

Is the structure diagonal (TRUE)| or box (FALSE)

Covariate centering value

Are the covariate values all positive

Type of value to use for the centering value: CovarNumber|CovarMean|CovarMedian

List of covariate effects

List of covariate items

Subject datafile

Datafile to model mapping file

PML model file

Initial estimates mapping file

Initial estimates values

Dose column definition file

Dose datafile

Random effects column definition file

Random effects data file

Name of predcheck output file

Directory containing phoenix generated files

Directory containing datafiles(default cwd)

Model has a baseline response

Model is fractional

Model is inhibitory

Model is sigmoidal

List of residual effects to include in the error model

Number of effects being included in the error model

Indirect model type

Is there data available for an effects compartment?

Is the response formation (TRUE) or degradation (FALSE) concentration dependent?

Is there an exponent in the effect statement?

Freeze standard deviation to prevent estimation of the PK part of the model

NLME job object

Intravenous|Extravascular

One of Micro|Clearance|Macro|Macro1

Model type as numeric value from 1:7

Name of observation variable

One of: T, TAD, PRED. If nothing is specified, the user-specified name of axis is used.

Method of binning: "none" (default), "KMEANS", "CENTERS", "BOUNDARIES"

Centers or boundary values specified as numeric vector

Categorical covariates (up to 3) for simulation stratification (overrides stratifyColumns given in NlmeVpcParams)

Values specifying the category right boundaries (used for categorical observations only; useful for count)

Quantiles to be estimate for each x value (bin value) in each strata for the current observable (internal quantiles)

Quantiles to estimate for each internal quantile (quantiles for quantile)

Flag to replace BLQ values with the LLOQ value

Taken from NlmeModelParameterization

Taken from NlmeModelAbsorption

Number of compartments

Does dose have a time lag?

Is there data available for an elimination compartment?

Does compartment include a fraction excreted parameter?

Is the elimination rate equal to the absorption rate?

Is infusion allowed?

Is duration of infusion measured (TRUE) or rate (FALSE)?

Is model part of a PK/PD model that is being fitted sequentially?

Is model closed-form algebraic (TRUE) or differential equation (FALSE)?

Number of random effects

Names of random effects

Matrix of random effect values

Name of the observed variable

Name to use for observation

Name to use for Epsilon

Additive|LogAdditive|Multiplicative |AdditiveMultiplicative|MixRatio|Power|Custom

Is the standard deviation frozen? (Default:FALSE)

Standard deviation value

Definition of a custom type or Power value

Are there BQL values? (Default:FALSE)

Value LLOQ value

Code to execute before the observation

Code to execute after the observation

Name of the scenario

Comma separated indices of covariate effects to use for this scenario

Name of the generated simulation file.

Numeric; Time values for simulation. Applicable for time-based models only. Ignored when "keepSource=TRUE"

Character; Vector of covariate names. Simulation point is added when the covariate value is set. See covariateNames

Character; Vector of dosing compartment names. Simulation point is added when the dose value is set.

Character; String of observed variables names. Simulation point is added when the observation value is set.

Character; List of variables from the model for simulation.

Logical; Set to TRUE to keep the number of rows appearing in the table the same as the number of rows in the input dataset.

Set to TRUE to output time after dose.

Number of replicates to simulate

Random number generator seed

Number of points in simulation for the models in individual mode

Maximum value of independent variable for the models in individual mode

Comma separated character string of Y variables for the models in individual mode

Simulate values at observed values of ivar for the models in individual mode

Optional list of simulation tables. NlmeSimTableDef class instance or a list of such instances. Could be generated by tableParams wrapper function or by NlmeSimTableDef class instance initializing directly.

Name of the structural parameter

Name to use for fixed effects

Name to use for random effects

Does the parameter have a random effect?

Parameter style: LogNormal, Normal, Combination, Log, Logit, Custom

Initial value for the parameter

Lower limit for the parameter value

Upper limit for the parameter value

Unit of measurement for the parameter

Is the parameter frozen?

Estimate the parameter sequentially

Initial value for the random effect

For Custom style, PML code to override the definition

Extra lines of code that relates to this parameter

Name of the generated simulation file.

Numeric; Time values for simulation. Applicable for time-based models only. Ignored when "keepSource=TRUE"

Character; Vector of covariate names. Simulation point is added when the covariate value is set. See covariateNames

Character; Vector of dosing compartment names. Simulation point is added when the dose value is set.

Character; String of observed variables names. Simulation point is added when the observation value is set.

Character; List of variables from the model for simulation.

Logical; Set to TRUE to keep the number of rows appearing in the table the same as the number of rows in the input dataset.

Set to TRUE to output time after dose.

Logical; Set to TRUE to output individual residuals. Valid only if whenObs is specified.

Logical; Set to TRUE to output the weight of current observation. Valid only if whenObs is specified.

Logical; Set to TRUE to output individual weighted residuals. Valid only if whenObs is specified.

Character; The mode of output. Options are "all" (default), "unique", "first". Only applicable to non time-based models for the case where only covrSet is defined or the case where only covrSet and variablesList are defined.

Option "all" (default): it outputs all the rows invoked by specified covariates. Option "unique": if the values in a row are the same as the ones in the previous row for the current subject, then the row is omitted; otherwise, it is printed out. Option "first": it outputs only the first row for each subject.

Integer; Number of replicates to simulate the model

Integer; Random number generator seed

Character; Type of correction to use when calculating a prediction-corrected observation. Options are "none", "proportional", "additive". This option is ignored for discontinuous observed variables (categorical, count, and time-to-event).

Logical; Set to TRUE to use Prediction Variance Correction. Only applicable to the case where predCorrection is set to either "proportional" or "additive".

Logical; Set to TRUE to include population prediction (PRED) results for continuous observed variables in output.

Character or character vector; Names of categorical covariates (up to 3) used to stratify modeling simulation results.

NlmeObservationVar class instance or list of these instances

Optional list of simulation tables. NlmeSimTableDef class instance or a list of such instances. Could be generated by tableParams wrapper function or by NlmeSimTableDef class instance initializing directly.

Name of fixed effect

Initial value

Values to perturbate by (either delta or percentage)

Lower value of reset range

Upper value of reset range

How to execute the run(NlmeParallelHost)

Dataset and model information(NlmeDataset)

Engine parameters(NlmeEngineExtraParams)

Profiles to perturbate(ProfileParameters)

Optional list of columns to sort and fit(SortColumns)

Optional list of scenarios to fit(NlmeScenario)

TRUE will run in background and return prompt(Bool)

Directory in which to run the job. Current working directory is used if NULL

Name of the secondary parameter

Definition of secondary variable

Optional units

Names of input data columns (up to 5 for individual models and no limit for population models) used to sort the input data and model outputs. Can be supplied as either a single string or a vector of strings.

Numeric. Threshold for adding a covariate effect

Numeric. Threshold for removing a covariate effect

-2LL|AIC|BIC; could be abbreviated.

Model object

Model object

Column mapping argument specifying corresponding "ADDL" column in input data set

Column mapping argument specifying corresponding "II" column in input data set

Model object

Name of covariate. If the involved model has columns mapped (i.e. model with columnMap = TRUE) use named character if the name of the covariate is different from the corresponding column in the input dataset, for example, covariate = c(BW = "BodyWeight"), where BW denotes the name of the covariate, and "BodyWeight" is the name of the corresponding column in the input dataset.

Name of structural parameter(s) on which the covariate has an effect. Specify effect as character or character vector if the covariate has an effect on multiple structural parameters.

Type of covariate. Options are "Continuous", "Categorical", "Occasion".

Direction of missing values propagation (if no covariate value is given). Options are "Forward", "Interpolate", "Backward", where "Interpolate" is only applicable to type = "Continuous".

Options are "Yes", "PlusOne", or "No", where option = "No" will remove the covariate effect from the specified structural parameter(s), but retain the covariate in the model. Note: option = "PlusOne" is only applicable to continuous and categorical covariates in the case where structural parameters have style = "LogNormal". Multiple options are not supported (i.e. all covariate effects in the call are supposed to have the same option. If different options are required for different covariate effects, sequential calls of current method could be done.

Centering method. Options are "Mean", "Median", "Value" or "None". Only applicable to covariate type = "Continuous". Must include argument centerValue if center = "Value".

Value used to center covariate. Only applicable if argument center = "Value" and type = "Continuous".

Unique values of categorical or occasion covariate. Only applicable to covariate type = "Categorical" or type = "Occasion".

Label names (in the same order as levels) for unique levels of categorical or occasion covariate in data. Only applicable to covariate type = "Categorical" or type = "Occasion" where its corresponding column in the input dataset has character type.

Set to FALSE if inter-occasion covariance matrix is not diagonal matrix. Only applicable to covariate type = "Occasion".

Initial values for the diagonal elements of the inter-occasion covariance matrix (if isDiagonal = TRUE) or initial values for the lower triangular elements (including diagonal elements) of inter-occasion covariance matrix (if isDiagonal = FALSE) in a row-wise order. Only applicable for covariate type = "Occasion".

Set to FALSE if covariate contains negative values. Only applicable to covariate type = "Continuous".

Model object

Specification of dose type. Options are "SteadyState"and "ADDL"

Dose point name. See doseNames

Mechanism for administering dose. Options are "Bolus" or "Infusion"

Optional. Column mapping argument specifying corresponding "ADDL" column in input data, or numeric value specifiying dose amount.

Optional. Column mapping argument specifying corresponding "II" column in input data, or numeric value specifying delta time.

Optional. Column mapping argument specifying corresponding "Rate" column in input data, or numeric specifying dose rate.

Optional. Column mapping argument specifying corresponding "Duration" column in data, or numeric specifying duration value.

Use second dose point on compartment

Column name in input data corresponding to column mapping for "SteadyState" or "ADDL" as supplied in type argument.

PK/PD model

Character vector of extra column/table definitions

Model object

Name of the compartment to which the dose is administered

Set TRUE if duration is used to specify infusion information

Set TRUE if doseCptName is specified in the model through dosepoint2 statement

Name of the input data column that represents the corresponding infusion rate. If not provided, colName must be mapped through colMapping().

Model object

Existing covariate name

Unique values of categorical or occasion covariate column specified as numeric vector

Unique values specifying corresponding label names for levels of categorical or occasion covariate column in data specified as character vector.

Model object

Column mapping argument specifying corresponding "MDV" column in input data set

An 'NlmePmlModel' object to which you want to add reset instructions.

Lower value of reset range.

Upper value of reset range.

Name of reset column in input data set for column mapping. The default is NULL.

An 'NlmePmlModel' object to which you want to add a secondary parameter.

Name of the secondary parameter.

Definition of secondary parameter.

Optional units of the secondary parameter. The default is "".

Model object

Column mapping argument specifying corresponding "SS" column in input data set

Column mapping argument specifying corresponding "II" column in input data set

Optional. Column mapping argument specifying corresponding "SSOffset" column in input data set

Model object

Tables class objects e.g., NlmeTableDef or NlmeSimTableDef

Name of column definition file

Logical; Set to TRUE if simulation tables are provided

Model object

List of effects

PK/PD model class object.

Host definition for model execution. See hostParams. If missing, multicore local host with 4 threads is used.

Engine parameters. See engineParams. If missing, default parameters generated by engineParams(model) are used.

Bootstrap parameters. See BootstrapParams. If missing, default parameters generated by BootstrapParams() are used.

Set to TRUE to run in background and return prompt.

Additional class initializer arguments for BootstrapParams or hostParams, or arguments available inside engineParams functions. If engineParams arguments are supplied through both params argument and additional argument (i.e., ellipsis), then the arguments in params will be ignored and only the additional arguments will be used with warning. If hostParams arguments are supplied through both hostPlatform argument and additional argument, then its values will be overridden by additional arguments. In addition, if BootstrapParams arguments are supplied through both bootParams argument and additional argument, then its slots will be overridden by additional arguments.

A 'SimpleNlmeJob' object that you want to cancel

NLME Parallel Host to be checked

Model (NlmePmlModel) object

Named character vector specifying valid column names in the input data. Character vector names must be valid model variable names contained in modelVariableNames(model).

optional pairs ModelTerm = ColumnName or ModelTerm = "ColumnName". Has higher precedence than mappings if some ModelTerm is mapped twice in mappings and in .... For multiple mapping, i.e. id mapping, a vector should be provided with the names of columns. See example below.

Model object to be copied

Set to TRUE to accept all effects, update PML statements, and test.mdl file from original model run

New model name for subdirectory created for model output. Subdirectory is created in current working directory.

Working directory to run the model. Current working directory will be used if workingDir not specified.

A PK/PD model

Name of the covariate

Name of the model variable

A value to set

Model object with covariates and covariate effects specified

Model object

Model covariate

Model object

Set to TRUE to force run

File with metamodel description

Directory where the results will be stored; if missing, a subfolder in the current directory with the model name given in parsedMetamodel will be created

Model object

Input data of class data.frame.

An 'NlmePmlModel' object from which you want to delete a secondary parameter.

Name of the secondary parameter to be deleted.

Model object

Model object

Is this a population model TRUE or individual model FALSE?

Set to TRUE if the model contains a baseline response.

Set to TRUE to modify the default form for the model. Only applicable to models with checkBaseline = TRUE.

Set to TRUE to change the model from an Emax to an Imax model.

Set to TRUE to change the model to its corresponding signmoid form.

Input dataset

If TRUE (default) column mapping arguments are required. Set to FALSE to manually map columns after defining model using colMapping.

Model name for subdirectory created for model output in current working directory.

Working directory to run the model. Current working directory will be used if workingDir not specified.

Arguments passed on to emaxmodel_MappingParameters

ID

Column mapping argument for input dataset column(s) that identify individual data profiles. Only applicable to population models isPopulation = TRUE.

C

Column mapping argument that represents the input dataset column for the independent variable that is treated as a covariate during the estimation/simulation process.

EObs

Column mapping argument that represents the input dataset column for the observed drug effect (i.e., the dependent variable).

Column mapping argument for input dataset column(s) that identify individual data profiles. Only applicable to population models isPopulation = TRUE.

Column mapping argument that represents the input dataset column for the independent variable that is treated as a covariate during the estimation/simulation process.

Column mapping argument that represents the input dataset column for the observed drug effect (i.e., the dependent variable).

Model object

Logical; Specifying whether or not to sort the input data by subject and time values.

• If model@hasResetInfo = TRUE, then sort must be set to FALSE (default);

• Otherwise, the default value for sort is TRUE.

Character; Specifying the solver used to numerically solve Ordinary Differential Equations (ODEs). Options are '"MatrixExponent"', '"Higham"', '"DVERK"', '"DOPRI5"', '"AutoDetect"', '"Stiff"'. See Details section.

Numeric; Specifying relative tolerance for the numerical ODE solver.

Numeric; Specifying absolute tolerance for the numerical ODE solver.

Numeric; Specifying maximum number of allowable steps or function evaluations for the ODE solver.

Numeric; Specifying maximum number of iterations for estimation.

Character; Specifying engine method for estimation. For population models, options are "QRPEM", "IT2S-EM", "FOCE-LB", "FO", "FOCE-ELS", "Laplacian", "Naive-Pooled". While, for individual models, "Naive-Pooled" is the only option.

Note: For population models, if model involves any discontinuous observed variable (e.g., count data) or BQL data, the default method is "Laplacian"; otherwise, the default method is "FOCE-ELS".

Character; Specifying method for standard error computations.

• For individual models, options are "Hessian" (default) and "None";

• For population models with method = "QRPEM", options are "Fisher-Score" (default) and "None";

• For population models with method = "IT2s-EM", the only option is "None";

• For population models with method set to either "FOCE-LB", "FO", "FOCE-ELS", "Laplacian", or "Naive-Pooled", options are "Sandwich" (default), "Hessian", "Fisher-Score", "Auto-Detect", and "None".

Here "None" means that standard error calculations are not performed.

Logical; Default TRUE uses central difference for stdErr calculations. Set to FALSE for forward difference method.

Numeric; Specifying the step size used for stdErr calculations. If not specified, 0.01 is used for population models and 0.001 for individual models.

Numeric; Specifying the number of integration points for adaptive Gaussian quadrature (AGQ) algorithm. Only applicable to population models with method set to either "FOCE-ELS" or "Laplacian".

Numeric; Specifying the number of iterations to perform non-parametric estimation. Only applicable to population models when method is not set to Naive-Pooled.

Logical, Set to TRUE to use synthetic gradient during the estimation process. Only applicable to population models when method is not set to Naive-Pooled.

Numeric; Specifying the number of iterations to perform Maximum A Posterior (MAP) initial Naive Pooling (NP) run before estimation. Only applicable to population models when method is not set to Naive-Pooled.

Numeric; Specifying the number of replicates to generate the PCWRES after the simple estimation. Only applicable to population models when method is not set to Naive-Pooled.

Numeric; Specifying the step size used for numerical differentiation when linearizing the model function during the estimation process.

Numeric; Specifying the number of significant decimal digits for the Laplacian algorithm to use to reach convergence. Only applicable to population models.

Numeric; Specifying the number of significant decimal digits for the individual estimation to use to reach convergence. Only applicable to population models.

Numeric; Specifying the period used to perform MAP assistance (mapAssist = 0 means that MAP assistance is not performed). Only applicable to population models with method = "QRPEM".

Numeric; Specifying the number of samples. Only applicable to population models with method = "QRPEM".

Numeric; Specifying the acceptance ratio. Only applicable to population models with method = "QRPEM".

Character; Specifying the distribution used for important sampling, and options are "Normal" (default), "DoubleExponential", "Direct", "T", "Mixture-2", Mixture-3. Only applicable to population models with method = "QRPEM".

Numeric; Specifing the degree of freedom (allowed value is between 3 and 30) for T distribution. Only applicable to population models with method = "QRPEM" and impDist = "T".

Numeric; Specifying the number of samples per subject used in the Sampling Importance Re-Sampling (SIR) algorithm to determine the number of SIR samples taken from the empirical discrete distribution that approximates the target conditional distribution. Only applicable to population models with method = "QRPEM".

Numeric; Specifying the number of burn-in iterations to perform at startup to adjust certain internal parameters. Only applicable to population models with method = "QRPEM".

Logical; Set to TRUE to freeze Omega but not Theta for the number of iterations specified in the numBurnIn. Only applicable to population models with method = "QRPEM".

Logical; Set to TRUE to use Monte-Carlo sampling instead of Quasi-Random. Only applicable to population models with method = "QRPEM".

Logical; Set to TRUE to execute all requested iterations specified in numIterations. Only applicable to population models with method = "QRPEM".

Character; Specifying the quasi-random scrambling method to use, and options are "Owen", "Tezuka-Faur", or "None". Only applicable to population models with method = "QRPEM".

Numeric; Specifying the step size used to numerically calculate the partial derivatives of observed variables with respect to parameters. Only applicable to individual models.

Numeric; Specifying the number of time steps used to output the partial derivatives of observed variables with respect to parameters. Only applicable to individual models.

Model object

Model object

The metamodel file path; relative paths are acceptable.

The directory where the files should be stored If missing, current working directory is used.

the name of the data file If missing, the default file name 'data1.txt' is used to prepare nlmeargsOutput file

the name of the file to output PML code If missing, the default file name 'test.mdl' is used.

the name of the file to output columns defintion If missing, the default file name 'cols1.txt' is used.

the name of the file to output engine parameters If missing, the default file name 'nlmeargs.txt' is used.

PK/PD model class object.

Host definition for model execution. See hostParams. If missing, PhoenixMPIDir64 is given and MPI is installed, MPI local host with 4 threads is used. If MPI is not found, local host without parallelization is used.

Engine parameters. See engineParams. If missing, default parameters generated by engineParams(model) are used.

Optional list of simple tables. See tableParams. By default a table named 'posthoc.csv' is returned with structural parameters values for all source data rows.

Set to TRUE to run in background and return prompt.

Used to specify which files to be outputted to the model directory and loaded as returned value. By default, all the applicable files listed in the Value section will be outputted to the model directory and loaded as returned value. Only those files listed in the Value section can be specified. Simple regex patterns are supported for the specification.

Additional arguments for hostParams or arguments available inside engineParams functions. If engineParams arguments are supplied through both params argument and additional argument (i.e., ellipsis), then the arguments in params will be ignored and only the additional arguments will be used with warning. If hostParams arguments are supplied through both the hostPlatform argument and the ellipses, values supplied to hostPlatform will be overridden by additional arguments supplied via the ellipses e.g., ....

Model object in which to define fixed effects values

Character or character vector specifying names of fixed effects

Numeric or numeric vector specifying the initial values of fixed effects. If supplying vector, must be in the same order/length as corresponding effect.

Numeric or numeric vector specifying the lower limit values of fixed effects. If supplying vector, must be in the same order as effect.

Numeric or numeric vector specifying the upper limit values of fixed effects. If supplying vector, must be in the same order as effect.

Logical or logical vector. Set to TRUE to freeze the fixed effect to the specified initial value. If supplying vector, must be in the same order as effect.

Character or character vector specifying units of measurement for the fixed effects. If supplying a vector, must be in the same order as effect.

PK/PD Model

PK/PD model

Model object

PK/PD model

Directory where temporary NLME run folder is created during execution. If missing, the current working directory will be used.

Directory containing NLME libraries/scripts

Visual name of the host (default A name by which the machine is known on the network)

IP address or name of the host(default 127.0.0.1)

windows or linux. Current OS by default. For remote runs it is possible to point the distro suppported, i.e. RHEL8 or UBUNTU2204. In such case the corresponding PML_BIN_DIR variable will be created and NLME Engine libraries will be looked in ⁠installationDirectory/{$PML_BIN_DIR}⁠.

Integer; Number of compute cores. 4 by default

String; Options are: None|Multicore|LOCAL_MPI|SGE|SGE_MPI| TORQUE|TORQUE_MPI|LSF|LSF_MPI|SLURM_SLURM_MPI.

String; How the user is identified to the remote system

Path to private key file, see ssh::ssh_connect() for details

Either a string or a callback function for password prompt, see ssh::ssh_connect() for details

a path to the script to be executed before starting Rscript within Certara.NLME8 package on the remote host. Ignored when running locally.

Path to Rscript executable on remote host; ignored on local host

Is this a local TRUE or remote FALSE host?

PK/PD model

Named numeric vector

PK/PD model

Is this a population model TRUE or individual model FALSE?

Model type. Options are "Constant", "Linear", "Quadratic".

Input dataset

If TRUE (default) column mapping arguments are required. Set to FALSE to manually map columns after defining model using colMapping.

Model name for subdirectory created for model output in current working directory.

Working directory to run the model. Current working directory will be used if workingDir not specified.

Arguments passed on to linearmodel_MappingParameters

ID

Column mapping argument for input dataset column(s) that identify individual data profiles. Only applicable to population models isPopulation = TRUE.

C

Column mapping argument that represents the input dataset column for the independent variable that is treated as a covariate during the estimation/simulation process.

EObs

Column mapping argument that represents the input dataset column for the observed drug effect (i.e., the dependent variable).

Column mapping argument for input dataset column(s) that identify individual data profiles. Only applicable to population models isPopulation = TRUE.

Column mapping argument that represents the input dataset column for the independent variable that is treated as a covariate during the estimation/simulation process.

Column mapping argument that represents the input dataset column for the observed drug effect (i.e., the dependent variable).

PK/PD model

Directory where the model was saved

Model object

Model object

A character string specifying the directory where the NLME Engine is installed e.g., INSTALLDIR environment variable. The cadlicensingtool executable is expected to be located within this directory, or within a subdirectory specified by the PML_BIN_DIR environment variable.

A logical value indicating whether to force re-authentication even if already authenticated. Default is FALSE.

A logical value indicating whether to force obtaining the license even if already licensed. Default is FALSE.

A logical value indicating whether to print verbose output. Default is getOption("verbose").

Model (NlmePmlModel) object

Set to TRUE to force run

json file with host definition for model execution. See NlmeParallelHost class definition. If missing, MPI local host with 4 threads is used for simple estimation mode, multicore host is used for the others.

Is this a population model TRUE or individual model FALSE?

Type of parameterization. Options are "Clearance", "Micro", "Macro", or "Macro1".

Type of absorption. Options are "Intravenous", "FirstOrder", "Gamma", "InverseGaussian", "Weibull" .

Value of either 1, 2, or 3.

Set to TRUE to convert model from a differential equation to close form.

Set to TRUE to add a lag time parameter to the model.

Set to TRUE to add an elimination compartment to the model.

Set to TRUE if elimination compartment (hasEliminationComp = TRUE) contains a fraction excreted parameter.

Set to TRUE to use Michaelis-Menten kinetics for elimination. Only applicable to models with paramteterization = "Clearance"

Set to TRUE if infusions allowed.

Set to TRUE if infusions use duration instead of rate (must also set infusionAllowed = TRUE).

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.

Set to TRUE to freeze PK fixed effects and remove the corresponding random effects as well as the PK observed variable from the model.

Set to TRUE to include an effect compartment into the model.

Does Emax/Imax model have a baseline response?

Set to TRUE to modify the default form for the Emax/Imax model. Only applicable to models with checkBaseline = TRUE.

Set to TRUE to change the default Emax to Imax model.

Set to TRUE to change the Emax/Imax to its corresponding sigmoid form.

Set to TRUE to freeze PD fixed effects and remove the corresponding random effects as well as the PD observed variable from the model.

Input dataset

If TRUE (default) column mapping arguments are required. Set to FALSE to manually map columns after defining model using colMapping.

Model name for subdirectory created for model output in current working directory.

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.

Is this a population model TRUE or individual model FALSE?

Type of parameterization. Options are "Clearance", "Micro", "Macro", or "Macro1".

Type of absorption. Options are "Intravenous", "FirstOrder", "Gamma", "InverseGaussian", "Weibull" .

Value of either 1, 2, or 3.

Set to TRUE to convert model from a differential equation to close form.

Set to TRUE to add a lag time parameter to the model.

Set to TRUE to add an elimination compartment to the model.

Set to TRUE if elimination compartment (hasEliminationComp = TRUE) contains a fraction excreted parameter.

Set to TRUE to use Michaelis-Menten kinetics for elimination. Only applicable to models with paramteterization = "Clearance"

Set to TRUE if infusions allowed.

Set to TRUE if infusions use duration instead of rate (must also set infusionAllowed = TRUE).

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.

Set to TRUE to freeze PK fixed effects and remove the corresponding random effects as well as the PK observed variable from the model.

Set to TRUE to include an effect compartment into the model.

Type of drug actions for the indirect response model. Options are "LimitedStimulation", "InfiniteStimulation", "LimitedInhibition", "InverseInhibition", "LinearStimulation", or "LogLinearStimulation".

Set to FALSE to have the drug actions affect the loss/degradation instead of the production.

Set to TRUE to add an exponent parameter to the drug action term.

Set to TRUE to freeze PD fixed effects and remove the corresponding random effects as well as the PD observed variable from the model.

Input dataset

If TRUE (default) column mapping arguments are required. Set to FALSE to manually map columns after defining model using colMapping.

Model name for subdirectory created for model output in current working directory.

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.

Column mapping argument for input dataset column(s) that identify individual data profiles. Only applicable to population models isPopulation = TRUE.

Column mapping argument that represents the input dataset column for the relative time used in a study and only applicable to time-based models.

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"

Column mapping argument that represents the input dataset column for the amount of drug administered and only applicable to models with absorption = "FirstOrder".

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".

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

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

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.

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.

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".

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".

Column mapping argument that represents the input dataset column for the stripping dose and only applicable to models with parameterization = "Macro".

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".

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".

Column mapping argument that represents the input dataset column for the observed amount of drug in the elimination compartment. (hasEliminationComp = TRUE).

Column mapping argument that represents the input dataset column for the observed drug effect.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nV.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nV2.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nV3.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nCl.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nCl2.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nCl3.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nKa.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nA.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nAlpha.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nB.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nBeta.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nC.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nGamma.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nKe.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nK12.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nK21.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nK13.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nK31.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nTlag.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nKm.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nVmax.

If isSequential = TRUE and isFractionExcreted = TRUE, mapped to the input dataset column that lists the values for random effect nFe.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nMeanDelayTime.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nShapeParamMinusOne.

If isSequential = TRUE, mapped to the input dataset column that lists the values for random effect nShapeParam.

Is this a population model TRUE or individual model FALSE?

Type of parameterization. Options are "Clearance", "Micro", "Macro", or "Macro1".

Type of absorption. Options are "Intravenous", "FirstOrder", "Gamma", "InverseGaussian", "Weibull" .

Value of either 1, 2, or 3.

Set to TRUE to convert model from a differential equation to close form.

Set to TRUE to add a lag time parameter to the model.

Set to TRUE to add an elimination compartment to the model.

Set to TRUE if elimination compartment (hasEliminationComp = TRUE) contains a fraction excreted parameter.

Set to TRUE to use Michaelis-Menten kinetics for elimination. Only applicable to models with paramteterization = "Clearance"

Set to TRUE if infusions allowed.

Set to TRUE if infusions use duration instead of rate (must also set infusionAllowed = TRUE).

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.

Set to TRUE to freeze PK fixed effects and remove the corresponding random effects as well as the PK observed variable from the model.

Set to TRUE to include an effect compartment into the model.

Type of PD model; Options are "Constant", "Linear", "Quadratic".

Set to TRUE to freeze PD fixed effects and remove the corresponding random effects as well as the PD observed variable from the model.

Input dataset

If TRUE (default) column mapping arguments are required. Set to FALSE to manually map columns after defining model using colMapping.

Model name for subdirectory created for model output in current working directory.

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.

Is this a population model TRUE or individual model FALSE?

Type of parameterization. Options are "Clearance", "Micro", "Macro", or "Macro1".

Type of absorption. Options are "Intravenous", "FirstOrder", "Gamma", "InverseGaussian", "Weibull" .

Value of either 1, 2, or 3.

Set to TRUE to convert model from a differential equation to close form.

Set to TRUE to add a lag time parameter to the model.

Set to TRUE to add an elimination compartment to the model.

Set to TRUE if elimination compartment (hasEliminationComp = TRUE) contains a fraction excreted parameter.

Set to TRUE to use Michaelis-Menten kinetics for elimination. Only applicable to models with paramteterization = "Clearance"

Set to TRUE if infusions allowed.

Set to TRUE if infusions use duration instead of rate (must also set infusionAllowed = TRUE).

Set to TRUE to freeze value of standard deviation of residual error variable.

Input dataset

If TRUE (default) column mapping arguments are required. Set to FALSE to manually map columns after defining model using colMapping.

Model name for subdirectory created for model output in current working directory.

Working directory to run the model. Current working directory will be used if workingDir not specified.

Arguments passed on to pkmodel_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).

Column mapping argument for input dataset column(s) that identify individual data profiles. Only applicable to population models isPopulation = TRUE.

Column mapping argument that represents the input dataset column for the relative time used in a study and only applicable to time-based models.

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"

Column mapping argument that represents the input dataset column for the amount of drug administered and only applicable to models with absorption = "FirstOrder".

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".

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

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

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.

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.

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".

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".

Column mapping argument that represents the input dataset column for the stripping dose and only applicable to models with parameterization = "Macro".

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".

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".

Column mapping argument that represents the input dataset column for the observed amount of drug in the elimination compartment. (hasEliminationComp = TRUE).

NlmeEngineExtraParams class instance

Arguments passed to methods.

An NlmeParallelHost object.

Additional arguments passed to the print function.

NlmePmlModel class instance

Arguments passed to methods.

Handle to an NLME job

Arguments passed to methods.

How to execute the run(NlmeParallelHost)

Engine parameters(NlmeEngineExtraParams)

Profiles to perturbate(ProfileParameters)

PK/PD model

Optional list of columns to sort and fit(SortColumns)

Optional list of scenarios to fit(NlmeScenario)

Set to TRUE to run in background and return prompt(Bool)

PK/PD model

Model object

One or more names of available random effects.

Initial values for the diagonal elements of the covariance matrix of random effects (if isDiagonal = TRUE, or initial values for the lower triangular elements (including diagonal elements) of the covariance matrix (if isDiagonal = FALSE) in a row-wise order.

Set to TRUE to if the covariance matrix of the specified random effects is a diagonal matrix. or FALSE if not.

Set to TRUE to freeze the covariance matrix of random effects.

Additional arguments

PK/PD model

Model object

Covariates to remove from model. If NULL all covariates will be removed from model.

Structural parameters for which to remove covariate effect(s) from. If NULL covariate effect will be removed from all structural parameters.

A character string specifying the directory where the NLME Engine is installed e.g., INSTALLDIR environment variable. The cadlicensingtool executable is expected to be located within this directory, or within a subdirectory specified by the PML_BIN_DIR environment variable.

PK/PD model object

Effect to lookup/set attributes for

A value to be set

Object of class NlmePmlModel

Model object

Name of the predicted variable as returned in residualEffectNames.

Options are "Additive", "LogAdditive", "Multiplicative", "AdditiveMultiplicative", "MixRatio", "Power".

Value for the standard deviation of the residual error variable.

Set to TRUE to freeze the standard deviation to the value specified for SD.

Set to TRUE if BQL values present in the observation data.

Optional LLOQ value if isBQL = TRUE

Column mapping argument that represents the input dataset column that contains the BQL flag for observation values corresponding to EObs. Only applicable to isBQL = TRUE.

Column mapping argument that represents the input dataset column that contains the BQL flag for observation values corresponding to CObs. Only applicable to isBQL = TRUE.

Column mapping argument that represents the input dataset column that contains the BQL flag for observation values corresponding to C1Obs. Only applicable to isBQL = TRUE.

Column mapping argument that represents the input dataset column that contains the BQL flag for observation values corresponding to AObs. Only applicable to isBQL = TRUE.

Value of exponent. Only applicable to errorType = "Power".

The metamodel file path; relative paths are acceptable.

The directory where the final results should be stored If missing, the mmdlfile base directory is used.

json file with host definition for model execution. Generated by Pirana application. Consider using host argument when running from R.

NlmeParallelHost() class instance.

NlmePmlModel object

Optional engine parameters to save with model

Optional host to save with model

the metamodel text to be substituted

the old model from mmdl_withComments

the model to be pasted

the name of initial file with metamodel to be overwritten

Object of class NlmePmlModel

PK/PD model class object.

Host definition for model execution. See hostParams. If missing, multicore local host with 4 threads is used.

Engine parameters. See engineParams. If missing, default parameters generated by engineParams(model) are used.

Covariate Effects Model providing the relationship between covariates and structural parameters to test (covariateModel(model)).

Set to TRUE to run in background and return prompt.

Additional arguments for hostParams or arguments available inside engineParams functions. If engineParams arguments are supplied through both params argument and additional argument (i.e., ellipsis), then the arguments in params will be ignored and only the additional arguments will be used with warning. If hostParams arguments are supplied through both the hostPlatform argument and the ellipses, values supplied to hostPlatform will be overridden by additional arguments supplied via the ellipses e.g., ....

PK/PD model class object.

Simulation parameters. See NlmeSimulationParams. If missing, default parameters generated by NlmeSimulationParams() are used.

Engine parameters. See engineParams. The common parameters include: sort, ODE, rtolODE, atolODE, maxStepsODE. If missing, default parameters generated by engineParams(model) are used.

Host definition for model execution. See hostParams. If missing, simple local host is used.

Set to TRUE to run in background and return prompt.

Additional class initializer arguments for NlmeSimulationParams, or arguments available inside hostParams or engineParams functions. If engineParams arguments are supplied through both params argument and additional argument (i.e., ellipsis), then the arguments in params will be ignored and only the additional arguments will be used with warning. If hostParams arguments are supplied through both hostPlatform argument and additional argument, then its slots will be overridden by additional arguments. In addition, if NlmeSimulationParams arguments are supplied through both simParams argument and additional argument, then its slots will be overridden by additional arguments.

PK/PD model class object.

Host definition for model execution. See hostParams. If missing, PhoenixMPIDir64 is given and MPI is installed, MPI local host with 4 threads is used. If MPI is not found, local host without parallelization is used.

Engine parameters. See engineParams. If missing, default parameters generated by engineParams(model) are used.

List of sort columns. See SortColumns. If missing, empty sort columns argument is used and NLME dataset is used as is.

List of scenarios with different sets of covariates. See NlmeScenario If missing, all covariates effects are considered as enabled.

Optional list of simple tables. See tableParams. By default a table named 'posthoc.csv' is returned with structural parameters values for all source data rows.

Set to TRUE to run in background and return prompt.

Used to specify which files to be outputted to the model directory and loaded as returned value. By default, all the applicable files listed in the Value section will be outputted to the model directory and loaded as returned value. Only those files listed in the Value section can be specified. Simple regex patterns are supported for the specification.

Additional arguments for hostParams or arguments available inside engineParams functions. If engineParams arguments are supplied through both params argument and additional argument (i.e., ellipsis), then the arguments in params will be ignored and only the additional arguments will be used with warning. If hostParams arguments are supplied through both the hostPlatform argument and the ellipses, values supplied to hostPlatform will be overridden by additional arguments supplied via the ellipses e.g., ....

PK/PD model class object.

Host definition for model execution. See hostParams. If missing, multicore local host with 4 threads is used.

Engine parameters. See engineParams. If missing, default parameters generated by engineParams(model) are used.

Covariate Effects Model providing the relationship between covariates and structural parameters to test (covariateModel(model)).

Stepwise parameters defining decision tree. See StepwiseParams

Set to TRUE to run in background and return prompt.

Additional arguments for hostParams or arguments available inside engineParams functions. If engineParams arguments are supplied through both params argument and additional argument (i.e., ellipsis), then the arguments in params will be ignored and only the additional arguments will be used with warning. If hostParams arguments are supplied through both the hostPlatform argument and the ellipses, values supplied to hostPlatform will be overridden by additional arguments supplied via the ellipses e.g., ....

Model with the parameter

The names of structural parameters

A value of the fixed effect to be set

Model object

Name of the structural parameter

Name of the corresponding fixed effect

Name of the corresponding random effect; only applicable to population models.

Use to specify the relationship of the structural parameter with its corresponding fixed effect, random effect, and covariate, if exists.

• "LogNormal" (Default): The structural parameter is defined as Product * exp(Eta)

• "LogNormal1": The structural parameter is defined as Sum * exp(Eta)

• "LogNormal2": The structural parameter is defined as exp(Sum + Eta)

• "LogitNormal": The structural parameter is defined as ilogit(Sum + Eta)

• "Normal": The structural parameter is defined as Sum + Eta)

Product denotes the product of the corresponding fixed effect and covariate effect terms (if exists), Eta represents the corresponding random effect, and Sum denotes the sum of its corresponding fixed effect and covariate effect terms (if exists).

Set to FALSE to remove the corresponding random effect from the model. Only applicable to population models. If NULL the system will automatically set hasRandomEffect = TRUE for population models, and hasRandomEffect = FALSE for individual models.

Object of class NlmePmlModel

Set to TRUE to omit empty names

Name of the generated simulation file.

Numeric; Time values for simulation. Applicable for time-based models only. Ignored when "keepSource=TRUE"

Character; Vector of covariate names. Simulation point is added when the covariate value is set. See covariateNames

Character; Vector of dosing compartment names. Simulation point is added when the dose value is set.

Character; String of observed variables names. Simulation point is added when the observation value is set.

Character; List of variables from the model for simulation.

Logical; Set to TRUE to keep the number of rows appearing in the table the same as the number of rows in the input dataset.

Set to TRUE to output time after dose.

Logical; Set to TRUE to output individual residuals. Valid only if whenObs is specified.

Logical; Set to TRUE to output the weight of current observation. Valid only if whenObs is specified.

Logical; Set to TRUE to output individual weighted residuals. Valid only if whenObs is specified.

Character; The mode of output. Options are "all" (default), "unique", "first". Only applicable to non time-based models for the case where only covrSet is defined or the case where only covrSet and variablesList are defined.

Option "all" (default): it outputs all the rows invoked by specified covariates. Option "unique": if the values in a row are the same as the ones in the previous row for the current subject, then the row is omitted; otherwise, it is printed out. Option "first": it outputs only the first row for each subject.

logical. Defining whether the table is for simulation purposes or for postprocessing after fit. Default is FALSE.

Model name to create subdirectory for model output in current working directory.

Working directory to run the model. Current working directory will be used if workingDir not specified.

Input dataset

File path specifying location of test.mdl file

PK/PD model class object.

VPC argument setup. See NlmeVpcParams. If missing, default values generated by NlmeVpcParams() are used.

Engine argument setup. See engineParams. The following arguments are the subject of interest: sort, ODE, rtolODE, atolODE, maxStepsODE. If missing, default values generated by engineParams(model) are used.

Host definition for model execution. See hostParams. If missing, simple local host is used.

Set to TRUE to run in background and return prompt.

Additional class initializer arguments for NlmeVpcParams or hostParams, or arguments available inside engineParams functions. If engineParams arguments are supplied through both params argument and additional argument (i.e., ellipsis), then the arguments in params will be ignored and only the additional arguments will be used with warning. If hostParams arguments are supplied through both hostPlatform argument and additional argument, then its values will be overridden by additional arguments. In addition, if NlmeVpcParams arguments are supplied through both vpcParams argument and additional argument, then its slots will be overridden by additional arguments.

Model object

Dataset to run simulation/fitting on

Simulation Parameters (simulation tables are written to coldef)

NlmeTableDef class object(s)

SortColumns class object used for proper id mapping during individual modeling