The ospsuite package provides an interface to the PK-Sim physiology database to create parameter sets describing a certain individual. By applying these parameter values to a simulation, it is possible to simulate different individuals based on one exported *.pkml simulation. This functionality is only available when PK-Sim is installed on the system.

The easier way to get started is to install the OSPSuite Setup. This will link PK-Sim to your ospsuite installation automatically. If the portable version of PK-Sim is used instead, one must specify the path to the PK-Sim folder by calling the function initPKSim().

## Creating individuals

The physiology of an individual is defined by the values of the simulation parameters. To simulate a specific individual, one has to generate a set of parameter values and apply these values to the model. NOTE: Currently, only individuals of the same species as in the original *.pkml simulation can be applied. I.e., if the simulation exported from PK-Sim represents a human individual, it is possible to simulate another human individual of different race, gender, etc., but it is not possible to simulate a rat. Though it is technically possible, and the simulation will produce some results, these will not valid.

The first step is creating an object describing individual characteristics. To see the list of available values for the arguments species, population (only for human), and gender (only for human), use the enums Species, HumanPopulation, and Gender, respectively. This object is then passed to the function createIndividual to generate a set of parameter values. The algorithm behind is the same used in PK-Sim when creating an Individual-Building Block.

library(ospsuite)
#> Loaded Common Language Runtime version 4.0.30319.42000

# If no unit is specified, the default units are used. For "weight" it is "kg", for "age" it is "year(s)".
individualCharacteristics <- createIndividualCharacteristics(
species    = Species$Human, population = HumanPopulation$Japanese_Population,
gender     = Gender$Female, weight = 75, height = 1.75, heightUnit = "m", age = 43 ) print(individualCharacteristics) #> IndividualCharacteristics: #> Species: Human #> Population: Japanese_Population #> Gender: FEMALE #> Age: 43.00 [year(s)] #> Gestational age: 40.00 [week(s)] #> Weight: 75.00 [kg] #> Height: 1.75 [m] individual <- createIndividual(individualCharacteristics = individualCharacteristics) # we will not be printing this given the long length of the output, but you can # see the details by running: # print(individual) The output contains two lists of parameters: • distributedParameters: parameters that differ between the individuals of the selected species • derivedParameters: parameters defined by formulas in the simulation When applying the generated individual parameter set to a simulation in R, only parameters from the distributedParameters should be overwritten, otherwise formula dependencies may be destroyed. Generated parameter values can be conveniently applied using the setParameterValuesByPath method: library(ospsuite) # Load simulation simFilePath <- system.file("extdata", "Aciclovir.pkml", package = "ospsuite") print(simFilePath) #> [1] "C:/Users/IndrajeetPatil/AppData/Local/Temp/RtmpovMBfA/temp_libpath5ff4183a3ad7/ospsuite/extdata/Aciclovir.pkml" sim <- loadSimulation(simFilePath) # Apply individual parameters setParameterValuesByPath( parameterPaths = individual$distributedParameters$paths, values = individual$distributedParameters$values, simulation = sim ) ## Adding enzyme ontogenies The PK-Sim database includes ontogeny information for some proteins (see (PK-Sim Ontogeny Database)[https://github.com/Open-Systems-Pharmacology/OSPSuite.Documentation/blob/master/PK-Sim%20Ontogeny%20Database%20Version%207.3.pdf]). For a protein molecule present in the simulation, it is possible to add the ontogeny information on one of the pre-defined proteins. For example, it is possible to set the ontogeny of the protein MyProtein to the value of the ontogeny of a CYP3A4 enzyme for the specified individual. The list of supported ontogenies is stored in the StandardOntogeny-list. library(ospsuite) # All supported ontogenies print(StandardOntogeny) #>$CYP1A2
#> [1] "CYP1A2"
#>
#> $CYP2C18 #> [1] "CYP2C18" #> #>$CYP2C19
#> [1] "CYP2C19"
#>
#> $CYP2C8 #> [1] "CYP2C8" #> #>$CYP2C9
#> [1] "CYP2C9"
#>
#> $CYP2D6 #> [1] "CYP2D6" #> #>$CYP2E1
#> [1] "CYP2E1"
#>
#> $CYP3A4 #> [1] "CYP3A4" #> #>$CYP3A5
#> [1] "CYP3A5"
#>
#> $CYP3A7 #> [1] "CYP3A7" #> #>$UGT1A1
#> [1] "UGT1A1"
#>
#> $UGT1A4 #> [1] "UGT1A4" #> #>$UGT1A6
#> [1] "UGT1A6"
#>
#> $UGT1A9 #> [1] "UGT1A9" #> #>$UGT2B4
#> [1] "UGT2B4"
#>
#> $UGT2B7 #> [1] "UGT2B7" # Create the ontogeny for the protein "MyProtein" based on ontology of CYP3A4 myProteinOntogeny <- MoleculeOntogeny$new(molecule = "MyProtein", ontogeny = StandardOntogeny$CYP3A4) print(myProteinOntogeny) #> MoleculeOntogeny: #> Molecule: MyProtein #> Ontogeny: CYP3A4 # Add this ontogeny to the individual characteristics used to create the individual parameters set individualCharacterstics <- createIndividualCharacteristics( species = Species$Human,
population         = HumanPopulation$Japanese_Population, gender = Gender$Female,
weight             = 75,
height             = 1.75,
heightUnit         = "m",
age                = 43,
moleculeOntogenies = myProteinOntogeny
)
print(individualCharacterstics)
#> IndividualCharacteristics:
#>    Species: Human
#>    Population: Japanese_Population
#>    Gender: FEMALE
#>    Age: 43.00 [year(s)]
#>    Gestational age: 40.00 [week(s)]
#>    Weight: 75.00 [kg]
#>    Height: 1.75 [m]
#>    Molecule MyProtein with ontogeny CYP3A4:

individual <- createIndividual(individualCharacteristics = individualCharacterstics)