defineResponseGroups = function(lpd) {

  # quiets concerns of R CMD check "no visible binding for global variable"

  x=NULL; ibrutinib=NULL; everolimus=NULL;

  selumetinib=NULL

  z_factor <- qnorm(0.05, lower.tail = FALSE)

  drugnames <- c( "ibrutinib", "everolimus", "selumetinib")

  ib  <- "D_002_4:5" 

  ev  <- "D_063_4:5" 

  se  <- "D_012_4:5"

  stopifnot(identical(fData(lpd)[c(ib, ev, se), "name"], drugnames))

  df  <- Biobase::exprs(lpd)[c(ib, ev, se), lpd$Diagnosis=="CLL"] %>%

    t %>% data.frame %>% `colnames<-`(drugnames)

  df$PatientID=rownames(df)

  mdf <- melt(df)

  # Determine standard deviation using mirror method

  pmdf = mdf[mdf$value >= 1,]

  ssd  <- mean( (pmdf$value - 1) ^ 2 ) ^ 0.5

  # Normal density

  dn <- tibble(

    x = seq(min(mdf$value), max(mdf$value), length.out = 100),

    y = dnorm(x, mean = 1, sd = ssd) * 2 * nrow(pmdf) / nrow(mdf) 

  )

  # Setting up the threshold

  thresh   <- 1 - z_factor * ssd

  # Decision rule

  df <- mutate(df,

               group = ifelse(ibrutinib < thresh, "BTK",

                              ifelse(everolimus < thresh, "mTOR",

                                     ifelse(selumetinib < thresh, "MEK",

                                     "none")))

  )

  return(data.frame(df[,c("ibrutinib","everolimus","selumetinib","group")],

                    row.names=df$PatientID))

}