diff --git a/book/tables/pharmacokinetic/pkct01.qmd b/book/tables/pharmacokinetic/pkct01.qmd
index 576b1bb222..f4ad18ed78 100644
--- a/book/tables/pharmacokinetic/pkct01.qmd
+++ b/book/tables/pharmacokinetic/pkct01.qmd
@@ -10,94 +10,139 @@ subtitle: Summary Concentration Table
 ::: panel-tabset
 ## Data Setup
 
+```{r setup, message=FALSE}
+#| code-fold: show
+
+# library(scda)
+# library(dplyr)
+# library(tern)
+
+# adsl <- synthetic_cdisc_dataset("latest", "adsl") %>%
+#   filter(ACTARM == "A: Drug X")
+# adpc <- synthetic_cdisc_dataset("latest", "adpc") %>%
+#   filter(ACTARM == "A: Drug X", PARAM == "Plasma Drug X")
+
+# Setting up the data
+# adpc_1 <- adpc %>%
+#   mutate(
+#     NFRLT = as.factor(NFRLT),
+#     AVALCAT1 = as.factor(AVALCAT1)
+#   ) %>%
+#   select(NFRLT, ACTARM, VISIT, AVAL, PARAM, AVALCAT1) %>%
+#   var_relabel(NFRLT = "Nominal Time from First Dose (hr)")
+
+# Row structure
+# lyt_rows <- basic_table() %>%
+#   split_rows_by(
+#     var = "ACTARM",
+#     split_fun = drop_split_levels,
+#     split_label = "Treatment Group",
+#     label_pos = "topleft"
+#   ) %>%
+#   add_rowcounts(alt_counts = TRUE) %>%
+#   split_rows_by(
+#     var = "VISIT",
+#     split_fun = drop_split_levels,
+#     split_label = "Visit",
+#     label_pos = "topleft"
+#   ) %>%
+#   split_rows_by(
+#     var = "NFRLT",
+#     split_fun = drop_split_levels,
+#     split_label = obj_label(adpc_1$NFRLT),
+#     label_pos = "topleft",
+#     child_labels = "hidden"
+#   )
+```
+
 ## Standard Table (Stats in Columns)
 
 ```{r variant1, test = list(result_v1 = "result")}
-lyt <- lyt_rows %>%
-  analyze_vars_in_cols(
-    vars = c("AVAL", "AVALCAT1", rep("AVAL", 8)),
-    .stats = c("n", "n_blq", "mean", "sd", "cv", "geom_mean", "geom_cv", "median", "min", "max"),
-    .formats = c(
-      n = "xx.", n_blq = "xx.", mean = format_sigfig(3), sd = format_sigfig(3), cv = "xx.x", median = format_sigfig(3),
-      geom_mean = format_sigfig(3), geom_cv = "xx.x", min = format_sigfig(3), max = format_sigfig(3)
-    ),
-    .labels = c(
-      n = "n", n_blq = "Number\nof\nLTRs/BLQs", mean = "Mean", sd = "SD", cv = "CV (%) Mean",
-      geom_mean = "Geometric Mean", geom_cv = "CV % Geometric Mean", median = "Median", min = "Minimum", max = "Maximum"
-    ),
-    cache = TRUE,
-    na_level = "NE",
-    .aligns = "decimal"
-  )
-
-result <- build_table(lyt, df = adpc_1, alt_counts_df = adsl) %>% prune_table()
+# lyt <- lyt_rows %>%
+#   analyze_vars_in_cols(
+#     vars = c("AVAL", "AVALCAT1", rep("AVAL", 8)),
+#     .stats = c("n", "n_blq", "mean", "sd", "cv", "geom_mean", "geom_cv", "median", "min", "max"),
+#     .formats = c(
+#       n = "xx.", n_blq = "xx.", mean = format_sigfig(3), sd = format_sigfig(3), cv = "xx.x", median = format_sigfig(3),
+#       geom_mean = format_sigfig(3), geom_cv = "xx.x", min = format_sigfig(3), max = format_sigfig(3)
+#     ),
+#     .labels = c(
+#       n = "n", n_blq = "Number\nof\nLTRs/BLQs", mean = "Mean", sd = "SD", cv = "CV (%) Mean",
+#       geom_mean = "Geometric Mean", geom_cv = "CV % Geometric Mean", median = "Median", min = "Minimum", max = "Maximum"
+#     ),
+#     cache = TRUE,
+#     na_level = "NE",
+#     .aligns = "decimal"
+#   )
+
+# result <- build_table(lyt, df = adpc_1, alt_counts_df = adsl) %>% prune_table()
 
 # Decorating
-main_title(result) <- "Summary of PK Concentrations by Nominal Time and Treatment: PK Evaluable"
-subtitles(result) <- c("Protocol: xxxxx", paste("Analyte: ", unique(adpc_1$PARAM)), paste("Treatment:", unique(adpc_1$ACTARM)))
-main_footer(result) <- "NE: Not Estimable"
+# main_title(result) <- "Summary of PK Concentrations by Nominal Time and Treatment: PK Evaluable"
+# subtitles(result) <- c("Protocol: xxxxx", paste("Analyte: ", unique(adpc_1$PARAM)), paste("Treatment:", unique(adpc_1$ACTARM)))
+# main_footer(result) <- "NE: Not Estimable"
 
-result
+# result
 ```
 
 ## Table Implementing 1/3 Imputation Rule
 
 ```{r variant2, test = list(result_v2 = "result")}
-lyt <- lyt_rows %>%
-  analyze_vars_in_cols(
-    vars = c("AVAL", "AVALCAT1", rep("AVAL", 8)),
-    .stats = c("n", "n_blq", "mean", "sd", "cv", "geom_mean", "geom_cv", "median", "min", "max"),
-    .formats = c(
-      n = "xx.", n_blq = "xx.", mean = format_sigfig(3), sd = format_sigfig(3), cv = "xx.x", median = format_sigfig(3),
-      geom_mean = format_sigfig(3), geom_cv = "xx.x", min = format_sigfig(3), max = format_sigfig(3)
-    ),
-    .labels = c(
-      n = "n", n_blq = "Number\nof\nLTRs/BLQs", mean = "Mean", sd = "SD", cv = "CV (%) Mean",
-      geom_mean = "Geometric Mean", geom_cv = "CV % Geometric Mean", median = "Median", min = "Minimum", max = "Maximum"
-    ),
-    cache = TRUE,
-    imp_rule = "1/3",
-    .aligns = "decimal"
-  )
-
-result <- build_table(lyt, df = adpc_1, alt_counts_df = adsl) %>% prune_table()
+# lyt <- lyt_rows %>%
+#   analyze_vars_in_cols(
+#     vars = c("AVAL", "AVALCAT1", rep("AVAL", 8)),
+#     .stats = c("n", "n_blq", "mean", "sd", "cv", "geom_mean", "geom_cv", "median", "min", "max"),
+#     .formats = c(
+#       n = "xx.", n_blq = "xx.", mean = format_sigfig(3), sd = format_sigfig(3), cv = "xx.x", median = format_sigfig(3),
+#       geom_mean = format_sigfig(3), geom_cv = "xx.x", min = format_sigfig(3), max = format_sigfig(3)
+#     ),
+#     .labels = c(
+#       n = "n", n_blq = "Number\nof\nLTRs/BLQs", mean = "Mean", sd = "SD", cv = "CV (%) Mean",
+#       geom_mean = "Geometric Mean", geom_cv = "CV % Geometric Mean", median = "Median", min = "Minimum", max = "Maximum"
+#     ),
+#     cache = TRUE,
+#     imp_rule = "1/3",
+#     .aligns = "decimal"
+#   )
+
+# result <- build_table(lyt, df = adpc_1, alt_counts_df = adsl) %>% prune_table()
 
 # Decorating
-main_title(result) <- "Summary of PK Concentrations by Nominal Time and Treatment: PK Evaluable"
-subtitles(result) <- c("Protocol: xxxxx", paste("Analyte: ", unique(adpc_1$PARAM)), paste("Treatment:", unique(adpc_1$ACTARM)))
-main_footer(result) <- c("NE: Not Estimable", "ND: Not Derived")
+# main_title(result) <- "Summary of PK Concentrations by Nominal Time and Treatment: PK Evaluable"
+# subtitles(result) <- c("Protocol: xxxxx", paste("Analyte: ", unique(adpc_1$PARAM)), paste("Treatment:", unique(adpc_1$ACTARM)))
+# main_footer(result) <- c("NE: Not Estimable", "ND: Not Derived")
 
-result
+# result
 ```
 
 ## Table Implementing 1/2 Imputation Rule
 
 ```{r variant3, test = list(result_v3 = "result")}
-lyt <- lyt_rows %>%
-  analyze_vars_in_cols(
-    vars = c("AVAL", "AVALCAT1", rep("AVAL", 8)),
-    .stats = c("n", "n_blq", "mean", "sd", "cv", "geom_mean", "geom_cv", "median", "min", "max"),
-    .formats = c(
-      n = "xx.", n_blq = "xx.", mean = format_sigfig(3), sd = format_sigfig(3), cv = "xx.x", median = format_sigfig(3),
-      geom_mean = format_sigfig(3), geom_cv = "xx.x", min = format_sigfig(3), max = format_sigfig(3)
-    ),
-    .labels = c(
-      n = "n", n_blq = "Number\nof\nLTRs/BLQs", mean = "Mean", sd = "SD", cv = "CV (%) Mean",
-      geom_mean = "Geometric Mean", geom_cv = "CV % Geometric Mean", median = "Median", min = "Minimum", max = "Maximum"
-    ),
-    cache = TRUE,
-    imp_rule = "1/2",
-    .aligns = "decimal"
-  )
-
-result <- build_table(lyt, df = adpc_1, alt_counts_df = adsl) %>% prune_table()
+# lyt <- lyt_rows %>%
+#   analyze_vars_in_cols(
+#     vars = c("AVAL", "AVALCAT1", rep("AVAL", 8)),
+#     .stats = c("n", "n_blq", "mean", "sd", "cv", "geom_mean", "geom_cv", "median", "min", "max"),
+#     .formats = c(
+#       n = "xx.", n_blq = "xx.", mean = format_sigfig(3), sd = format_sigfig(3), cv = "xx.x", median = format_sigfig(3),
+#       geom_mean = format_sigfig(3), geom_cv = "xx.x", min = format_sigfig(3), max = format_sigfig(3)
+#     ),
+#     .labels = c(
+#       n = "n", n_blq = "Number\nof\nLTRs/BLQs", mean = "Mean", sd = "SD", cv = "CV (%) Mean",
+#       geom_mean = "Geometric Mean", geom_cv = "CV % Geometric Mean", median = "Median", min = "Minimum", max = "Maximum"
+#     ),
+#     cache = TRUE,
+#     imp_rule = "1/2",
+#     .aligns = "decimal"
+#   )
+
+# result <- build_table(lyt, df = adpc_1, alt_counts_df = adsl) %>% prune_table()
 
 # Decorate table
-main_title(result) <- "Summary of PK Concentrations by Nominal Time and Treatment: PK Evaluable"
-subtitles(result) <- c("Protocol: xxxxx", paste("Analyte: ", unique(adpc_1$PARAM)), paste("Treatment:", unique(adpc_1$ACTARM)))
-main_footer(result) <- "ND: Not Derived"
+# main_title(result) <- "Summary of PK Concentrations by Nominal Time and Treatment: PK Evaluable"
+# subtitles(result) <- c("Protocol: xxxxx", paste("Analyte: ", unique(adpc_1$PARAM)), paste("Treatment:", unique(adpc_1$ACTARM)))
+# main_footer(result) <- "ND: Not Derived"
 
-result
+# result
 ```
 
 {{< include ../../test-utils/save_results.qmd >}}