examples/design-method-simulate-DADesign.R

In Roche/crmPack: Object-Oriented Implementation of CRM Designs

# nolint start

# Define the dose-grid and PEM parameters
emptydata <- DataDA(
  doseGrid = c(0.1, 0.5, 1, 1.5, 3, 6, seq(from = 10, to = 80, by = 2)),
  Tmax = 60
)

# Initialize the mDA-CRM model
npiece_ <- 10
Tmax_ <- 60

lambda_prior <- function(k) {
  npiece_ / (Tmax_ * (npiece_ - k + 0.5))
}

model <- DALogisticLogNormal(
  mean = c(-0.85, 1),
  cov = matrix(c(1, -0.5, -0.5, 1), nrow = 2),
  ref_dose = 56,
  npiece = npiece_,
  l = as.numeric(t(apply(as.matrix(c(1:npiece_), 1, npiece_), 2, lambda_prior))),
  c_par = 2
)
# Choose the rule for dose increments
myIncrements <- IncrementsRelative(
  intervals = c(0, 20),
  increments = c(1, 0.33)
)

myNextBest <- NextBestNCRM(
  target = c(0.2, 0.35),
  overdose = c(0.35, 1),
  max_overdose_prob = 0.25
)

# Choose the rule for the cohort-size
mySize1 <- CohortSizeRange(
  intervals = c(0, 30),
  cohort_size = c(1, 3)
)
mySize2 <- CohortSizeDLT(
  intervals = c(0, 1),
  cohort_size = c(1, 3)
)
mySize <- maxSize(mySize1, mySize2)

# Choose the rule for stopping
myStopping1 <- StoppingTargetProb(
  target = c(0.2, 0.35),
  prob = 0.5
)
myStopping2 <- StoppingMinPatients(nPatients = 50)

myStopping <- (myStopping1 | myStopping2)

# Choose the safety window
mysafetywindow <- SafetyWindowConst(c(6, 2), 7, 7)

# Initialize the design
design <- DADesign(
  model = model,
  increments = myIncrements,
  nextBest = myNextBest,
  stopping = myStopping,
  cohort_size = mySize,
  data = emptydata,
  safetyWindow = mysafetywindow,
  startingDose = 3
)

## set up truth curves
myTruth <- probFunction(model, alpha0 = 2, alpha1 = 3)
curve(myTruth(x), from = 0, to = 100, ylim = c(0, 1))

exp_cond.cdf <- function(x, onset = 15) {
  a <- pexp(28, 1 / onset, lower.tail = FALSE)
  1 - (pexp(x, 1 / onset, lower.tail = FALSE) - a) / (1 - a)
}

# set up simulation settings
options <- McmcOptions(
  burnin = 10,
  step = 1,
  samples = 200
)

mySims <- simulate(design,
  args = NULL,
  truthTox = myTruth,
  truthSurv = exp_cond.cdf,
  trueTmax = 80,
  nsim = 2,
  seed = 819,
  mcmcOptions = options,
  firstSeparate = TRUE,
  deescalate = FALSE,
  parallel = FALSE
)

# nolint end