dfpk (version 3.3.0)

sim.data: Generate new PK and toxicity data.

Description

This function can be used to generate/simulate new data from several measurements simulations.

Usage

sim.data(PKparameters, omegaIIV, omegaAlpha, sigma, doses, limitTox, 
         timeSampling, N, TR, seed=190591)

Arguments

PKparameters

Subject's pharmacokinetic's (PK) parameters.

omegaIIV

The inter-individual variability for the clearance and the volume of distribution; possible values may be 70% or 30% in different simulated data.

omegaAlpha

The patient's sensitivity parameter.

sigma

The additive or proportional error.

doses

A vector with the doses panel.

limitTox

The toxicity threshold.

timeSampling

The time sampling.

N

The total number of enrolled patients.

TR

The total number of simulated datasets.

seed

Seed of the random number generator. Default value is set at 190591.

Value

An object of class "scen" is returned, consisting of simulated PK and toxicity data. Objects generated by sim.data contain at least the following components:

PKparameters

Subject's pharmacokinetic's (PK) parameters.

nPK

The length of the time points.

time

The time sampling.

idtr

The id number of the corresponding simulated dataset.

N

The total number of enrolled patients.

doses

A vector with the doses panel.

preal

Prior toxicity probabilities.

limitTox

Tocixity threshold.

omegaIIV

The inter-individual variability for the clearance and the volume of distribution.

omegaAlpha

The patient's sensitivity parameter.

conc

The concentration of the drug in blood plasma.

concPred

The predicted concentration of the drug in blood plasma.

tox

The toxicity outcome.

tab

A summarized matrix consisting of the predicted concentration of the drug and the time sampling for each patient.

parameters

The estimated PK parameters of each patient.

alphaAUC

A vector with the computed AUC values of each patient.

References

Ursino, M., et al, (2017) Dose-finding methods for Phase I clinical trials using pharmacokinetics in small populations, Biometrical Journal.

See Also

nsim

Examples

TR = 10
N = 30
limitTox <- 10.96                                                
PKparameters <- c(2,10,100)       # PK parameters ka,CL,V
omegaIIV <- 0.7                   # Inter-individual
omegaAlpha <- 0                    
doses <- c(12.59972,34.65492,44.69007,60.80685,83.68946,100.37111)
timeSampling <- seq(0,24,length.out=48)    
sigma <- rep(0.2,length(timeSampling))  # sigma: Additive or proportional error

gen.scen <- sim.data(PKparameters,omegaIIV,omegaAlpha,sigma,doses,
                     limitTox,timeSampling, N, TR, seed=190591) 
gen.scen[[1]]     # returns the first simulated dataset. 


#### Graphical representation of the first simulated data
# plot(gen.scen[[1]])