- Overview
- Design evaluation
- Create two PFIM projects:
- Create the statistical model
- Get
the PK model
`Linear1InfusionSingleDose_ClV`

from the library of models - Assign the PK model the statistical model
- Set mu and omega for each parameter
- Assign the model parameters to the statistical model
- Create
and add the error model to the response PK
`RespPK`

and create and add the response PK to the statistical model - Assign the statistical model to the PFIM projects
- Create a design called
`Design`

- Create an arm
called
`Bras test`

of size 150 - For
each arm create and add the sampling times for the response PK
`RespPK`

- For
the arm
`brasTest`

create and add the administration parameters of the response PK - Add the arm
`brasTest`

to the design`MyDesign`

- Add
the design
`MyDesign`

to the PFIM project`MyProject`

- Evaluate the population, individual and Bayesian FIMs
- Display the results of the design evaluation
- Create and save the report for the design evaluation

- Design optimization
- Create
and add the design
`MyDesign2`

to the project`MyProject_optimization`

- Define design constraints
- Add the arm to the design
- Add the design to the project
- Set the the parameters of the PSO algorithm and run the algorithm for the design optimization with a population FIM
- Run the PSO algorithm for the optimization with a population FIM
- Display the results of the design optimization
- Create and save the report for the design optimization

- Create
and add the design
- References

In this example, we simulate an 1-compartment model with linear elimination for IV infusion over 1 hour (inspired by (Sukeishi et al. 2022)). One hundred and fifty (150) subjects receive a 400mg loading dose on the first day, followed by 4 daily doses of 200mg. Blood samples are taken at the end of the \(1^{st}\) infusion (H1), H20, H44, H66 and H120. By evaluating this design, we will then select 4 sampling times on intervals (0,48) and (72,120) for an optimal design using PSO (Particle Swarm Optimization) algorithm.

Reports of the design evaluation and optimization are available at https://github.com/iame-researchCenter/PFIM

`MyProject_evaluation`

: project for the design evaluation
named `eval_PK_Sukeishi-2021-GS441524`

`MyProject_optimization`

: project for the design
optimization named `opti_PK_Sukeishi-2021-GS441524`

```
= PFIMProject( name = "eval_PK_Sukeishi-2021-GS441524" )
MyProject_evaluation = PFIMProject( name = "opti_PK_Sukeishi-2021-GS441524" ) MyProject_optimization
```

`= StatisticalModel() MyStatisticalModel `

`Linear1InfusionSingleDose_ClV`

from the
library of models`= getModel( PFIMLibraryOfModels, "Linear1InfusionSingleDose_ClV" ) MyPKModel `

`= defineModelEquations( MyStatisticalModel, MyPKModel ) MyStatisticalModel `

```
= ModelParameter( "V", mu = 50, omega = sqrt( .26 ), distribution = LogNormalDistribution() )
pV = ModelParameter( "Cl", mu = 5, omega = sqrt( .34 ), distribution = LogNormalDistribution() ) pCl
```

```
= defineParameter( MyStatisticalModel, pV )
MyStatisticalModel = defineParameter( MyStatisticalModel, pCl ) MyStatisticalModel
```

`RespPK`

and create and add the response PK to the
statistical model```
= Combined1( sigma_inter = 0.5, sigma_slope = sqrt( 0.15 ) )
errorModelresponsePK
= Response( "RespPK", errorModelresponsePK )
responsePK
= addResponse( MyStatisticalModel, responsePK ) MyStatisticalModel
```

```
= defineStatisticalModel( MyProject_evaluation, MyStatisticalModel )
MyProject_evaluation = defineStatisticalModel( MyProject_optimization, MyStatisticalModel ) MyProject_optimization
```

`Design`

`= Design( "Design" ) MyDesign `

`Bras test`

of size 150`= Arm( name = "Bras test", arm_size = 150 ) brasTest `

`RespPK`

`= addSampling( brasTest, SamplingTimes( outcome = "RespPK", sample_time = c( 1,12,24,44,72,120 ) ) ) brasTest `

`brasTest`

create and add the administration
parameters of the response PK```
= Administration( outcome = "RespPK", Tinf = rep( 1, 5 ), time_dose = seq( 0, 96, 24 ) , amount_dose = c( 400, rep( 200, 4 ) ) )
administration_brasTest
= addAdministration( brasTest, administration_brasTest ) brasTest
```

`brasTest`

to the design
`MyDesign`

`= addArm( MyDesign, brasTest ) MyDesign `

`MyDesign`

to the PFIM project
`MyProject`

`= addDesign( MyProject_evaluation, MyDesign ) MyProject_evaluation `

```
= EvaluatePopulationFIM( MyProject_evaluation )
evaluationPop = EvaluateIndividualFIM( MyProject_evaluation )
evaluationInd = EvaluateBayesianFIM( MyProject_evaluation ) evaluationBay
```

```
show( evaluationPop )
show( evaluationInd )
show( evaluationBay )
```

```
# set the path and name of the report to save the report
= "....."
outputPath
= list( unitTime=c("hour"), unitResponses= c("mcg/mL","DI%") )
plotOptions
reportPFIMProject( evaluationPop,
outputPath = outputPath, plotOptions = plotOptions )
reportPFIMProject( evaluationInd,
outputPath = outputPath, plotOptions = plotOptions )
reportPFIMProject( evaluationBay,
outputPath = outputPath, plotOptions = plotOptions )
```

`MyDesign2`

to the project
`MyProject_optimization`

```
= Design( name = "MyDesign2")
MyDesign2 = addDesign( MyProject_optimization, MyDesign2 ) MyProject_optimization
```

```
= SamplingConstraint( response = "RespPK", continuousSamplingTimes = list( c( 1,48 ), c( 72,120 ) ) )
samplingBoundsConstraintRespPK = SamplingConstraint( response = "RespPK", min_delay = 5 )
samplingMinimalDelayConstraintRespPK
= DesignConstraint()
Constr1
= addSamplingConstraint( Constr1, samplingBoundsConstraintRespPK )
Constr1 = addSamplingConstraint( Constr1, samplingMinimalDelayConstraintRespPK )
Constr1 = addSamplingConstraints( brasTest2, Constr1 ) brasTest2
```

`= addArm( MyDesign2, brasTest2 ) MyDesign2 `

`= addDesign( MyProject_optimization, MyDesign2 ) MyProject_optimization `

`= PSOAlgorithm( maxIteration = 100, populationSize = 10, personalLearningCoefficient = 2.05, globalLearningCoefficient = 2.05, showProcess = TRUE ) psoOptimizer `

`= OptimizeDesign( MyProject_optimization, psoOptimizer, PopulationFim() ) optimization_populationFIM `

`show( optimization_populationFIM )`

```
# set the path to save the report
= "....."
outputPath
= list( unitTime=c("hour"), unitResponses= c("mcg/mL","DI%") )
plotOptions
reportPFIMProject( optimization_populationFIM, outputPath = outputPath, plotOptions = plotOptions )
```

Sukeishi, Asami, Kotaro Itohara, Atsushi Yonezawa, Yuki Sato, Katsuyuki
Matsumura, Yoshiki Katada, Takayuki Nakagawa, et al. 2022.
“Population Pharmacokinetic Modeling of GS-441524, the Active
Metabolite of Remdesivir, in Japanese COVID-19 Patients with Renal
Dysfunction.” *CPT: Pharmacometrics & Systems
Pharmacology* 11 (1): 94–103.