2. Design Scenarios • esqlabsR

Within the esqlabsR framework, the simulations are run by defining and executing multiple scenarios. A scenario is defined by the simulation file containing the model structure, parametrization of the model, application protocol, and (optionally) the physiology of the simulated individual or population. To simplify scenarios set up, all this information is stored in Excel files with a defined structure.

The step-wise approach of setting up a new simulation scenario is shown in Figure 1; a detailed description of the Excel file structures and R code are given in the Configuration files structure section.

Figure 1: Workflow of scenario setup

Add a new scenario

1. Add the model file

After the model has been developed in PK-Sim and/or MoBi, a simulation must be stored as a .pkml file in the Models/Simulations folder.

2. Name the new scenario

To set up a simulation/scenario in R, open the file Scenarios.xlsx located in the folder Parameters. Start defining a scenario by giving it a name in the Scenario_name column. The scenario name will be used later to retrieve simulation results, e.g., in figure definitions.

3. Link to the model file

Specify the simulation *.pkml file to use in the column ModelFile.

If you want to run the simulation with the settings as it has been exported from PK-Sim or MoBi, you can proceed to vignette("esqlabsR-run-simulations").

Customize a scenario

4. Simulation Parameters

You can define simulation parameters in the ModelParameters.xlsx file. To apply them to the simulation, you need to specify which sheets to load in the ModelParameterSheets column of the Scenarios.xlsx file.

5. Individuals

If you want to simulate a specific individual with individual characteristics (age, weight, etc.) or apply individual model parameter values to the simulation, define the individual in the IndividualId column. Then create a new individual entry in the Individuals.xlsx file.

To create a new individual with specific biometrics, create a new row in the IndividualBiometrics sheet.
To define an individual-specific parametrization, create a new sheet and name it as the individual’s ID.

If your model contains proteins (e.g., enzymes or transporters), you have to specify their ontongenies in the columns ‘Protein’ and ‘Ontogeny’. If not specified, age-dependent protein expression will not be considered. You can specify a list of protein names in the column ‘Protein’, separated by a ,, and a list of standard ontogenies implemented in the PK-Sim database in the column ‘Ontogeny’. For example, if your model contains proteins with names CYP3A4_alternative and CYP2D6_alternative, you can specify their ontogenies by entering CYP3A4_alternative, CYP2D6_alternative in the ‘Protein’ column, and CYP3A4, CYP2D6 in the ‘Ontogeny’ column. To see the list of supported ontogienes, call ospsuite::StandardOntogeny.

6. Population

To run a population simulation, specify a population in the column PopulationId. If you want to create a new population each time you run the scenario, define population demographics in the Demographics sheet of the PopulationParameters.xlsx file. Remember that simulation results might differ each time you run the scenario, as a new population will be generated each time!

If you want to import a population from an existing CSV file, set the value of the ReadPopulationFromCSV column to TRUE. The population CSV file must be located in the Parameters/Populations folder.

To apply ontogenies of proteins implemented in PK-Sim data base, you have to specify the ontogenies for the proteins in the mode. See Section 5. Individuals for more information.

7. Time

Simulation time can also be changed with the SimulationTime and SimulationTimeUnit columns.

8. OutputPath

You can define the outputs of the simulation in the OutputPathsIds column. For convenience, not the full paths to the outputs must be listed, but their acronyms. The full path for each acronym must be defined in the sheet OutputPaths.

9. Administration Protocols

Finally, you can simulate different administration protocols from the same simulation file by defining an application protocol in the column ApplicationProtocol. See the description below.

Now that you designed your own simulation, read vignette("esqlabsR-run-simulations") to continue the process. To learn more about simulation design, read the following sections.

Details

Configuration files structure

The relevant Excel files for the definition of the scenarios are:

ApplicationParameters.xlsx
Individuals.xlsx
ModelParameters.xlsx
PopulationParameters.xlsx
Scenarios.xlsx

The Scenarios sheet of the Scenarios.xlsx file has the following structure:

Scenario_name

Unique name of the scenario. The name must be a valid R variables name.

IndividualId

Name (ID) of an individual. This name refers to the name of the individual as used in Excel file Individuals.xlsx for the definition of the biometric properties (sheet IndividualBiometrics) of the simulated individual individual-specific model parameters. For the latter, create a separate sheet in the Individuals.xlsx files with the sheet name being the IndividualId. The structure of these sheets is the same as the structure of the sheets in the ModelParameter.xlsx file, see description below. IndividualId may be empty. In this case, the individual as defined in the pkml simulation without any individual-specific model parameters will be simulated. The same individual can be used in multiple scenarios. It is possible to scale from a human model to the species Rat, Rabbit, and Monkey by applying the respective individual to the simulation. Other species scalings are technically possible but the correctness of the results is not guaranteed as there exist some structural differences between the species.

PopulationId

Name (ID) of a population. If empty, the scenario is simulated as an individual simulation. Otherwise, population simulation is performed. If the column ReadPopulationFromCSV is set to FALSE, PopulationId refers to the name of the population as defined in the sheet Demographics of the file PopulationParameters.xlsx. To create a population with specific demographic characteristics, define an entry with the same population id in the Demographics. The same population can be used in multiple scenarios. If the column ReadPopulationFromCSV is set to TRUE, the population will be imported from the CSV file located in the folder Parameters/Populations, the name of the file must be the id of the population. Note: You can define both an IndividualId and a PopulationId. In this case, individual-specific parameters from the IndividualParameters.xlsx will be applied to the simulation before applying the population parameters. Keep in mind, that any physiological parameters defined for an individual that are also part of the parameter set of a population will be overwritten by the population! If, e.g., you specify the GFR of the individual in the IndividualParameters.xlsx, it will be overwritten by the GFR values sampled in the simulation.

ModelParameterSheets

A list of sheet names from the ModelParameter.xlsx file, separated by a ,. Each sheet must contain Container Path, Parameter Name, Value, and Units. Parameter values from specified sheets will be applied to the model according to the order of their definition. E.g., if we define Global, Aciclovir, then parameters from the Aciclovir sheet will be applied after the Global parameters. ModelParameterSheets may be empty or specify as many sheets as required. Note that the specified sheets must be present in the ModelParameter.xlsx file. This approach aims to have global parameters that can be applied to most scenarios and a separate set of parameters for, e.g., different disease states (parameter sheets Healthy and CKD) or separate parametrization of different compounds (sheet Aciclovir).
You can further refine the parametrization of the scenario by specifying the individual parameters in the IndividualParameters.xlsx file. Create a sheet with the name as the IndividualId specified for the respective scenario with the same structure as the ModelParameters.xlsx file. This way, you can define, e.g., individual-specific clearance values or, as in the example case, the glomerular filtration rate. Individual-specific parameters are applied after the parameters defined in the ModelParameterSheets. You can use an individual in multiple scenarios. This step is ignored if an individual is specified in the scenario definition, but no sheet with this name exists in the IndividualParameters.xlsx file.

ApplicationProtocol

Name of the application protocol that will be applied. Applications are defined as parameters that will be applied to the model in the file ApplicationParameters.xlsx. For each application, create a sheet with the name as specified in the ApplicationProtocol entry and populate it with the same structure as the ModelParameter.xlsx file. Configuring application protocols this way requires that the loaded simulation includes all possible applications that can be turned on and off by setting parameters, e.g., the Dose or Start time parameters. As it might be cumbersome to create entries for all administration parameters manually, we can use the getAllApplicationParameters() function to get a list of all (constant) parameters in the Applications container. In the following example, we will extract application parameters for the molecule Aciclovir from the example simulation:

sim <- loadSimulation(system.file("extdata", "Aciclovir.pkml", package = "ospsuite"))
applicationParams <- getAllApplicationParameters(sim)
print(applicationParams)
#> [[1]]
#> Parameter: 
#>    Path: Applications|IV 250mg 10min|Application_1|ProtocolSchemaItem|Start time 
#>    Value: 0.00e+00 [min] 
#>    isConstant: TRUE 
#>    isStateVariable: FALSE 
#> 
#> [[2]]
#> Parameter: 
#>    Path: Applications|IV 250mg 10min|Application_1|ProtocolSchemaItem|Dose 
#>    Value: 2.50e-04 [kg] 
#>    isConstant: TRUE 
#>    isStateVariable: FALSE 
#> 
#> [[3]]
#> Parameter: 
#>    Path: Applications|IV 250mg 10min|Application_1|ProtocolSchemaItem|DosePerBodySurfaceArea 
#>    Value: 0.00e+00 [kg/dm²] 
#>    isConstant: TRUE 
#>    isStateVariable: FALSE 
#> 
#> [[4]]
#> Parameter: 
#>    Path: Applications|IV 250mg 10min|Application_1|ProtocolSchemaItem|DosePerBodyWeight 
#>    Value: 0.00e+00 [kg/kg] 
#>    isConstant: TRUE 
#>    isStateVariable: FALSE 
#> 
#> [[5]]
#> Parameter: 
#>    Path: Applications|IV 250mg 10min|Application_1|ProtocolSchemaItem|Infusion time 
#>    Value: 10.00 [min] 
#>    isConstant: TRUE 
#>    isStateVariable: FALSE

And export the parameters to an Excel file using the exportParametersToXLS() function:

exportParametersToXLS(parameters = applicationParams, paramsXLSpath = "../Applications.xlsx")

The created Excel file will have the same structure as all Parameter-files and can be directly loaded in MoBi or R using the readParametersFromXLS() function.

SimulationTime

Time of the simulation. Multiple simulation time intervals can be defined, each being a triplet of <StartTime, EndTime, Resolution> values. Resolution is the number of simulated points per time unit defined in the column TimeUnit. Simulation intervals are separated by a ;.

For example, to simulate the model for 10 minutes with a resolution of 1 point per minute, the value of the column SimulationTime should be 0, 10, 1, and that of the column SimulationTimeUnit should be min. To simulate the model for * 20 hours with a resolution of 1 point per minute, then * for three weeks (equals to 3724 = 504 hours) with a resolution of 1 point per hour, and finally * for two days (equals to 504 + 2*24 = 552 hours) with a resolution of 10 points per hour,

the value of the column SimulationTime should be 0, 20, 60; 20, 504, 1; 504, 552, 10, and that of the column SimulationTimeUnit should be h.

SimulationTimeUnit

Unit for SimulationTime. For supported units, see ospsuite::ospUnits.

SteadyState

If TRUE, the model will be simulated for a “sufficiently long” time (1000 minutes by default).

SteadyStateTime

Time for the steady state.

SteadyStateTimeUnit

Unit for SteadyStateTime. For supported units, see ospsuite::ospUnits.

ModelFile

Name of the pkml file with the simulation. It must be located in the folder defined in ProjectConfiguration$modelFolder.

OutputPathsIds

Paths of model outputs (i.e., paths to the molecules/ parameters for which outputs will be simulated) can be defined in the sheet OutputPaths. Create an entry for each output path by entering the full path into the column OutputPath and defining a unique identifier for this path in the column OutputPathId. The content of the sheet could look like this:

OutputPathId	OutputPath
Aciclovir_PVB	Organism\|PeripheralVenousBlood\|Aciclovir\|Plasma (Peripheral Venous Blood)
Aciclovir_fat_cell	Organism\|Fat\|Intracellular\|Aciclovir\|Concentration in container

In the Scenarios sheet, enter the IDs of all paths the outputs should be generated for, separated by a comma, e.g., Aciclovir_PVB, Aciclovir_fat_cell.

Scenario parameterization hierarchy

The final parameterization combines the different parameterization steps defined at various levels, as described in the section above. The following figure summarizes the hierarchy of the parameterization.

Parametrization sequence

If a parameter path is defined in multiple steps, its value will be overwritten by the subsequent steps. That means individual parameter values will overwrite the values defined in the “ModelParameters.xlsx” file, and parameters specified in the customParams argument of the runScenarios() function will overwrite everything else.

The order of parameter sheets of the “ModelParameters.xlsx” file defined in the ModelParameterSheets column defines the order in which the parameters are applied.