sim.data: Generate and store PK and toxicity data.

In artemis-toumazi/dfpk: Bayesian Dose-Finding Designs using Pharmacokinetics (PK) for Phase I Clinical Trials

Generate and store PK and toxicity data.

Description

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.

Usage

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

Arguments

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.

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 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 nsim.

Author(s)

Artemis Toumazi [e-mail], Moreno Ursino [e-mail], Sarah Zohar [e-mail]

References

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>.

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]])

artemis-toumazi/dfpk documentation built on Sept. 5, 2023, 2:44 a.m.