diff --git a/R/plotBounds.R b/R/plotBounds.R
index 4e956771..4b5e9794 100644
--- a/R/plotBounds.R
+++ b/R/plotBounds.R
@@ -27,9 +27,18 @@
 #' @example examples/plotBounds.R
 #' @export
 #' @keywords graphics
-plotBounds <- function(z, area = TRUE, grid = TRUE, yt = "x", add = FALSE,
-                       cols = c("green", "red", "darkgreen", "orange"),
-                       lwds = c(3, 3), ltype = "l", lpch = 16, lcex = 1, gy = 20) {
+plotBounds <- function(
+    z,
+    area = TRUE,
+    grid = TRUE,
+    yt = "x",
+    add = FALSE,
+    cols = c("green", "red", "darkgreen", "orange"),
+    lwds = c(3, 3),
+    ltype = "l",
+    lpch = 16,
+    lcex = 1,
+    gy = 20) {
   n <- nrow(z)
   nmin <- min(z$looks)
   nmax <- max(z$looks)
@@ -51,40 +60,71 @@ plotBounds <- function(z, area = TRUE, grid = TRUE, yt = "x", add = FALSE,
     stop("yt can only be x or p")
   }
   if (add) {
-    graphics::lines(z$looks, z2,
-      lwd = lwds[1], col = cols[3], type = ltype,
-      pch = lpch, cex = lcex
+    graphics::lines(
+      z$looks,
+      z2,
+      lwd = lwds[1],
+      col = cols[3],
+      type = ltype,
+      pch = lpch,
+      cex = lcex
     )
-    graphics::lines(z$looks, z1,
-      lwd = lwds[2], col = cols[4], type = ltype,
-      pch = lpch, cex = lcex
+    graphics::lines(
+      z$looks,
+      z1,
+      lwd = lwds[2],
+      col = cols[4],
+      type = ltype,
+      pch = lpch,
+      cex = lcex
     )
     return(invisible())
   }
-  graphics::plot(z$looks, rep(0, n),
-    xlim = c(0, max(z$looks)), ylim = c(0, yU), type = "n",
-    xlab = "n", ylab = ylabel
+  graphics::plot(
+    z$looks,
+    rep(0, n),
+    xlim = c(0, max(z$looks)),
+    ylim = c(0, yU),
+    type = "n",
+    xlab = "n",
+    ylab = ylabel
   )
   if (grid) {
     graphics::abline(h = gridy, col = "gray")
   }
   if (area) {
-    graphics::polygon(c(z$looks, nmax, nmin), c(z2, yU, yU2),
+    graphics::polygon(
+      c(z$looks, nmax, nmin),
+      c(z2, yU, yU2),
       lwd = lwds[1],
-      col = cols[1], border = cols[1]
+      col = cols[1],
+      border = cols[1]
     )
-    graphics::polygon(c(z$looks, nmax, nmin), c(z1, 0, 0),
+    graphics::polygon(
+      c(z$looks, nmax, nmin),
+      c(z1, 0, 0),
       lwd = lwds[2],
-      col = cols[2], border = cols[2]
+      col = cols[2],
+      border = cols[2]
     )
   } else {
-    graphics::lines(z$looks, z2,
-      lwd = lwds[1], col = cols[1], type = ltype,
-      pch = lpch, cex = lcex
+    graphics::lines(
+      z$looks,
+      z2,
+      lwd = lwds[1],
+      col = cols[1],
+      type = ltype,
+      pch = lpch,
+      cex = lcex
     )
-    graphics::lines(z$looks, z1,
-      lwd = lwds[2], col = cols[2], type = ltype,
-      pch = lpch, cex = lcex
+    graphics::lines(
+      z$looks,
+      z1,
+      lwd = lwds[2],
+      col = cols[2],
+      type = ltype,
+      pch = lpch,
+      cex = lcex
     )
   }
   return(invisible())
diff --git a/design/design_doc_plotBounds.qmd b/design/design_doc_plotBounds.qmd
new file mode 100644
index 00000000..6cc2a0eb
--- /dev/null
+++ b/design/design_doc_plotBounds.qmd
@@ -0,0 +1,315 @@
+---
+title: "Design Doc for plotBounds"
+format: revealjs
+editor: visual
+---
+
+Statisticians can display boundaries of Go, Stop and GreyZone decisions graphically in terms of response rates required by desired samples sizes or looks. This is the purpose of the  `plotBounds` function. Coordinates are the points where the polygon should be drawn and reflect the possible values for a go and stop decision respectively.
+
+ Note that for the predictive probability case, decision 1 rules are chosen. See `ocPredprob` for rules. This design document aims to refactor the previous function, in particular to use `ggplot2` and reduce the length of the function. 
+
+# Packages that aid
+
+```{r}
+library(flextable)
+library(ggplot2)
+```
+
+# Vintage function
+
+```{r}
+vintage_plotBounds <- function(
+    z,
+    area = TRUE,
+    grid = TRUE,
+    yt = "x",
+    add = FALSE,
+    cols = c("#009E73", "#FF0046", "#7F55B1", "#F0A04B"),
+    lwds = c(3, 3),
+    ltype = "l",
+    lpch = 16,
+    lcex = 1,
+    gy = 20) {
+  n <- nrow(z)
+  nmin <- min(z$looks)
+  nmax <- max(z$looks)
+  if (yt == "x") {
+    z1 <- z$xL
+    z2 <- z$xU
+    yU <- nmax
+    yU2 <- nmin
+    ylabel <- "Number of Responses"
+    gridy <- seq(0, yU, by = floor(yU / gy))
+  } else if (yt == "p") {
+    z1 <- z$pL
+    z2 <- z$pU
+    yU <- 1
+    yU2 <- 1
+    ylabel <- "Response Rate"
+    gridy <- seq(0, yU, by = yU / gy)
+  } else {
+    stop("yt can only be x or p")
+  }
+  if (add) {
+    graphics::lines(
+      z$looks,
+      z2,
+      lwd = lwds[1],
+      col = cols[3],
+      type = ltype,
+      pch = lpch,
+      cex = lcex
+    )
+    graphics::lines(
+      z$looks,
+      z1,
+      lwd = lwds[2],
+      col = cols[4],
+      type = ltype,
+      pch = lpch,
+      cex = lcex
+    )
+    return(invisible())
+  }
+  graphics::plot(
+    z$looks,
+    rep(0, n),
+    xlim = c(0, max(z$looks)),
+    ylim = c(0, yU),
+    type = "n",
+    xlab = "n",
+    ylab = ylabel
+  )
+  if (grid) {
+    graphics::abline(h = gridy, col = "gray")
+  }
+  if (area) {
+    graphics::polygon(
+      c(z$looks, nmax, nmin),
+      c(z2, yU, yU2),
+      lwd = lwds[1],
+      col = cols[1],
+      border = cols[1]
+    )
+    graphics::polygon(
+      c(z$looks, nmax, nmin),
+      c(z1, 0, 0),
+      lwd = lwds[2],
+      col = cols[2],
+      border = cols[2]
+    )
+  } else {
+    graphics::lines(
+      z$looks,
+      z2,
+      lwd = lwds[1],
+      col = cols[1],
+      type = ltype,
+      pch = lpch,
+      cex = lcex
+    )
+    graphics::lines(
+      z$looks,
+      z1,
+      lwd = lwds[2],
+      col = cols[2],
+      type = ltype,
+      pch = lpch,
+      cex = lcex
+    )
+  }
+  return(invisible())
+}
+```
+
+# Vintage example that should work with new function
+
+```{r}
+plotBounds(
+  boundsPostprob(
+    looks = c(10, 20, 30, 40),
+    p0 = 0.20,
+    tL = 0.10,
+    tU = 0.90,
+    parE = c(1, 1)
+  ),
+  yt = "p",
+  add = TRUE
+)
+```
+
+# Vintage function output
+
+```{r}
+vintage_plotBounds(
+  boundsPredprob(
+    looks = c(10, 20, 30, 40),
+    p0 = 0.20,
+    tT = 0.80,
+    phiL = 0.10,
+    phiU = 0.90,
+  ),
+  yt = "x"
+)
+```
+
+# New call function
+
+There are two good options to graph polygons to reflect the purpose of this function. The use of base r's `polygon()` is slightly more laborious; once minimum and maximum coordinates are established, approximation of these points are then required to draw the borders of this polygon. This step can be removed using the `geom_ribbon` call from the package `ggplot2`. Furthermore, the base r approach require the initial plot area to be created, and axes, axes labels, and points to be overlayed. There are additional steps that are also taken in the `ggplot2` approach, however done within a code chunk rather than separated calls. While it can be argued that these additional calls from the base r approach would anyway be encapsulated in one function, that is `plotbound`, the number of code lines is substantially reduced using the `ggplot` approach. 
+
+```{r}
+new_plotBounds <- function(coords,
+                           go_colour = "#1B9E77",
+                           stop_colour = "#E41A1C",
+                           alpha = 1) {
+  assert_data_frame(coords, any.missing = FALSE, types = "numeric")
+  assert_character(go_colour)
+  assert_character(stop_colour)
+  assert_number(alpha, lower = 0, upper = 1)
+
+  go_data <- data.frame(
+    n = coords$looks,
+    ymin_go = coords$xU,
+    ymax_go = coords$looks
+  )
+  stop_data <- data.frame(
+    n = coords$looks,
+    ymin_stop = c(rep(0, length(coords$looks))),
+    ymax_stop = coords$xL
+  )
+  plot <- ggplot2::ggplot() +
+    ggplot2::geom_ribbon(
+      data = stop_data,
+      ggplot2::aes(x = n, ymin = ymin_stop, ymax = ymax_stop),
+      fill = stop_colour, alpha = alpha
+    ) +
+    ggplot2::geom_ribbon(
+      data = go_data,
+      ggplot2::aes(x = n, ymin = ymin_go, ymax = ymax_go),
+      fill = go_colour, alpha = alpha
+    ) +
+    ggplot2::scale_x_continuous(
+      name = "n",
+      breaks = go_data$n
+    ) +
+    ggplot2::scale_y_continuous(
+      breaks = seq(from = 0, to = max(go_data$n), by = 2)
+    ) +
+    ggplot2::geom_point(
+      data = go_data,
+      ggplot2::aes(x = n, y = ymin_go),
+      size = 3,
+      shape = 16,
+      colour = "#16C47F",
+    ) +
+    ggplot2::geom_point(
+      data = stop_data,
+      ggplot2::aes(x = n, y = ymax_stop),
+      size = 3,
+      shape = 16,
+      colour = "#FF748B", # "#DC3C22",FF748B
+    ) +
+    ggplot2::xlab("Sample Size (n)") +
+    ggplot2::ylab("Number of Responders") +
+    ggplot2::theme_minimal()
+
+  plot + ggplot2::ggtitle(
+    "Boundaries of Go and Stop Responders per sample size"
+  )
+}
+```
+
+# creating plot using new function with output from `boundsPredprob()`
+
+The following output show that important coordinates needed as input to create these plots. 
+
+As a premise, we establish the criteria:
+
+Interim
+Go : P(success) > 90 %
+Stop : P(success) > 10 %
+
+Final
+Go : P(RR > 0.20 | data) > 80 %
+Stop : P(RR > 0.20 | data) < 10 %
+
+The criteria for interim analyses are from predictive probability calculation.
+
+The criteria for final analyses are from posterior probability calculation. 
+
+which translates to boundaries :
+
+- When n = 10, 4 responders and above is a Go, 0 responders and below is a stop.
+- When n = 20, 7 responders and above is a Go, 2 responders and below is a stop
+- When n = 30, 9 responders and above is a Go, 5 responders and below is a stop
+- When n = 40, 10 responders and above is a Go, 9 responders and below is a stop
+
+```{r}
+coords <- boundsPredprob(
+  looks = c(10, 20, 30, 40),
+  p0 = 0.20,
+  tT = 0.80,
+  phiL = 0.10,
+  phiU = 0.90,
+)
+print(coords)
+```
+
+
+```{r}
+coords <- boundsPredprob(
+  looks = c(10, 20, 30, 40),
+  p0 = 0.20,
+  tT = 0.80,
+  phiL = 0.10,
+  phiU = 0.90,
+)
+new_plotBounds(
+  coords = coords,
+  go_colour = "blue",
+  alpha = 1
+)
+```
+
+# creating plots with new function with output from `boundsPostprob()`
+
+The following output show which inputs from a posterior probability design are needed to create these plots.
+
+As a premise, we establish the criteria:
+Go : P(RR > 0.20 | data) > 90 %
+Stop : P(RR > 0.20 | data) > 10 %
+which translates to boundaries :
+
+- When n = 10, 4 responders and above is a Go, 3 responders and below is a stop.
+- When n = 20, 7 responders and above is a Go, 6 responders and below is a stop
+- When n = 30, 9 responders and above is a Go, 8 responders and below is a stop
+- When n = 40, 12 responders and above is a Go, 11 responders and below is a stop
+
+
+```{r}
+coords1 <- boundsPostprob(
+  looks = c(10, 20, 30, 40),
+  p0 = 0.20,
+  tL = 0.10,
+  tU = 0.90,
+  parE = c(1, 1)
+)
+new_plotBounds(coords1)
+```
+
++ggplot2 vs base R
++https://r-graphics.org/CHAPTER-GGPLOT2.html
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/examples/plotBounds.R b/examples/plotBounds.R
index c39fc05b..4c84dbd5 100644
--- a/examples/plotBounds.R
+++ b/examples/plotBounds.R
@@ -1,16 +1,32 @@
 # examples
 plotBounds(
   boundsPostprob(
-    looks = c(10, 20, 30, 40), p0 = 0.20,
-    tL = 0.10, tU = 0.90, parE = c(1, 1)
+    looks = c(10, 20, 30, 40),
+    p0 = 0.20,
+    tL = 0.10,
+    tU = 0.90,
+    parE = c(1, 1)
   ),
-  yt = "p", add = TRUE
+  yt = "p",
+  add = TRUE
+)
+plotBounds(
+  boundsPredprob(
+    looks = c(10, 20, 30, 40),
+    p0 = 0.20,
+    tT = 0.80,
+    phiL = 0.10,
+    phiU = 0.90,
+  ),
+  yt = "x"
+)
+plotBounds(
+  boundsPredprob(
+    looks = c(10, 20, 30, 40),
+    p0 = 0.20,
+    tT = 0.80,
+    phiL = 0.10,
+    phiU = 0.90,
+  ),
+  yt = "p"
 )
-plotBounds(boundsPredprob(
-  looks = c(10, 20, 30, 40), p0 = 0.20, tT = 0.80,
-  phiL = 0.10, phiU = 0.90,
-), yt = "x")
-plotBounds(boundsPredprob(
-  looks = c(10, 20, 30, 40), p0 = 0.20, tT = 0.80,
-  phiL = 0.10, phiU = 0.90,
-), yt = "p")
diff --git a/man/plotBounds.Rd b/man/plotBounds.Rd
index 0caf508c..5b6ab385 100644
--- a/man/plotBounds.Rd
+++ b/man/plotBounds.Rd
@@ -58,18 +58,34 @@ and \code{\link{boundsPostprob}}
 # examples
 plotBounds(
   boundsPostprob(
-    looks = c(10, 20, 30, 40), p0 = 0.20,
-    tL = 0.10, tU = 0.90, parE = c(1, 1)
+    looks = c(10, 20, 30, 40),
+    p0 = 0.20,
+    tL = 0.10,
+    tU = 0.90,
+    parE = c(1, 1)
   ),
-  yt = "p", add = TRUE
+  yt = "p",
+  add = TRUE
+)
+plotBounds(
+  boundsPredprob(
+    looks = c(10, 20, 30, 40),
+    p0 = 0.20,
+    tT = 0.80,
+    phiL = 0.10,
+    phiU = 0.90,
+  ),
+  yt = "x"
+)
+plotBounds(
+  boundsPredprob(
+    looks = c(10, 20, 30, 40),
+    p0 = 0.20,
+    tT = 0.80,
+    phiL = 0.10,
+    phiU = 0.90,
+  ),
+  yt = "p"
 )
-plotBounds(boundsPredprob(
-  looks = c(10, 20, 30, 40), p0 = 0.20, tT = 0.80,
-  phiL = 0.10, phiU = 0.90,
-), yt = "x")
-plotBounds(boundsPredprob(
-  looks = c(10, 20, 30, 40), p0 = 0.20, tT = 0.80,
-  phiL = 0.10, phiU = 0.90,
-), yt = "p")
 }
 \keyword{graphics}