Description Usage Arguments Value Author(s) References See Also Examples
This function can be used to generate and store PK and toxicity data in order to be used for simulation according to the dose-finding model.
1 2 |
PKparameters |
Subject's pharmacokinetic's (PK) parameters from the population distributions defined by the population mean. |
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 sampling time points. |
N |
The total sample size per trial. |
TR |
The total number of simulated datasets. |
seed |
The seed of the random number generator that is used at the beginning of each trial; defaults to 190591. |
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 from the population distributions defined by the population mean. |
nPK |
The length of the time points. |
time |
The sampling time points. |
idtr |
The id number of the corresponding simulated dataset. |
N |
The total sample size per trial. |
doses |
A vector with the doses panel. |
preal |
The prior toxicity probabilities. |
limitTox |
The tocixity threshold. |
omegaIIV |
The inter-individual variability for the clearance and the volume of distribution. |
omegaAlpha |
The patient's sensitivity parameter. |
conc |
The concentration computed at the PK population values. |
concPred |
The concentration values with proportional errors for each patient at each dose. |
tox |
The toxicity outcome. |
parameters |
The simulated PK parameters of each patient. |
alphaAUC |
A vector with the computed AUC values of each patient. |
tab |
A summary matrix containing the sampling time points at the first row followed by concPred, parameters and alphaAUC.
It used by the simulation function |
Artemis Toumazi artemis.toumazi@gmail.com, Moreno Ursino moreno.ursino@inserm.fr, Sarah Zohar sarah.zohar@inserm.fr
Ursino, M., et al, (2017) Dose-finding methods for Phase I clinical trials using pharmacokinetics in small populations, Biometrical Journal, <doi:10.1002/bimj.201600084>.
Toumazi, A., et al, (2018) dfpk: An R-package for Bayesian dose-finding designs using pharmacokinetics (PK) for phase I clinical trials, Computer Methods and Programs in Biomedicine, <doi:10.1016/j.cmpb.2018.01.023>.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | 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]])
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