blockexp: Summarize your experiment for optimization routines

In PopED: Population (and Individual) Optimal Experimental Design

Description

Create some output to the screen and a text file that summarizes the initial design and the design space you will use to optimize.

Usage

blockexp(
  fn,
  poped.db,
  e_flag = FALSE,
  opt_xt = poped.db$settings$optsw[2],
  opt_a = poped.db$settings$optsw[4],
  opt_x = poped.db$settings$optsw[4],
  opt_samps = poped.db$settings$optsw[1],
  opt_inds = poped.db$settings$optsw[5]
)

Arguments

fn	The file handle to write to.
poped.db	A PopED database.
e_flag	Should output be with uncertainty around parameters?
opt_xt	Should the sample times be optimized?
opt_a	Should the continuous design variables be optimized?
opt_x	Should the discrete design variables be optimized?
opt_samps	Are the number of sample times per group being optimized?
opt_inds	Are the number of individuals per group being optimized?

See Also

Other Helper: blockfinal(), blockheader(), blockopt()

Examples

library(PopED)

############# START #################
## Create PopED database
## (warfarin model for optimization)
#####################################

## Warfarin example from software comparison in:
## Nyberg et al., "Methods and software tools for design evaluation 
##   for population pharmacokinetics-pharmacodynamics studies", 
##   Br. J. Clin. Pharm., 2014. 

## Optimization using an additive + proportional reidual error  
## to avoid sample times at very low concentrations (time 0 or very late samples).

## find the parameters that are needed to define from the structural model
ff.PK.1.comp.oral.sd.CL

## -- parameter definition function 
## -- names match parameters in function ff
sfg <- function(x,a,bpop,b,bocc){
  parameters=c(CL=bpop[1]*exp(b[1]),
               V=bpop[2]*exp(b[2]),
               KA=bpop[3]*exp(b[3]),
               Favail=bpop[4],
               DOSE=a[1])
  return(parameters) 
}

## -- Define initial design  and design space
poped.db <- create.poped.database(ff_fun=ff.PK.1.comp.oral.sd.CL,
                                  fg_fun=sfg,
                                  fError_fun=feps.add.prop,
                                  bpop=c(CL=0.15, V=8, KA=1.0, Favail=1), 
                                  notfixed_bpop=c(1,1,1,0),
                                  d=c(CL=0.07, V=0.02, KA=0.6), 
                                  sigma=c(prop=0.01,add=0.25),
                                  groupsize=32,
                                  xt=c( 0.5,1,2,6,24,36,72,120),
                                  minxt=0.01,
                                  maxxt=120,
                                  a=c(DOSE=70),
                                  mina=c(DOSE=0.01),
                                  maxa=c(DOSE=100))

############# END ###################
## Create PopED database
## (warfarin model for optimization)
#####################################


blockexp("",poped.db, opt_xt=TRUE)

PopED documentation built on May 21, 2021, 5:08 p.m.