diff --git a/DESCRIPTION b/DESCRIPTION
index a337023c..463c91ba 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -62,6 +62,7 @@ Imports:
     tidyr,
     tools,
     utils,
+    units,
     rlang,
     yaml,
     zip
diff --git a/NAMESPACE b/NAMESPACE
index 42d7eec8..4030400e 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -18,6 +18,7 @@ export(g_pkconc_ind_log)
 export(general_lineplot)
 export(general_meanplot)
 export(geometric_mean)
+export(get_conversion_factor)
 export(get_label)
 export(has_label)
 export(lambda_slope_plot)
@@ -122,6 +123,7 @@ importFrom(tern,g_ipp)
 importFrom(tidyr,pivot_longer)
 importFrom(tidyr,pivot_wider)
 importFrom(tools,file_ext)
+importFrom(units,set_units)
 importFrom(utils,read.csv)
 importFrom(utils,write.csv)
 importFrom(yaml,read_yaml)
diff --git a/R/calculate_summary_stats.R b/R/calculate_summary_stats.R
index 57e1a89b..3e168feb 100644
--- a/R/calculate_summary_stats.R
+++ b/R/calculate_summary_stats.R
@@ -61,15 +61,15 @@ calculate_summary_stats <- function(res_pknca, input_groups = "DOSNO") {
     group_by(across(all_of(c(input_groups, "PPTESTCD")))) %>%
     unique() %>%
     summarise(
-      geomean = exp(mean(log(PPORRES), na.rm = TRUE)), # nolint
-      geocv = (sd(PPORRES, na.rm = TRUE) / exp(mean(log(PPORRES), na.rm = TRUE))) * 100,
-      mean = mean(PPORRES, na.rm = TRUE),
-      CV = (sd(PPORRES, na.rm = TRUE) / mean(PPORRES, na.rm = TRUE)) * 100,
-      sd = sd(PPORRES, na.rm = TRUE),
-      min = min(PPORRES, na.rm = TRUE),
-      max = max(PPORRES, na.rm = TRUE),
-      median = median(PPORRES, na.rm = TRUE),
-      count.missing = sum(is.na(PPORRES)),
+      geomean = exp(mean(log(PPSTRES), na.rm = TRUE)),
+      geocv = (sd(PPSTRES, na.rm = TRUE) / exp(mean(log(PPSTRES), na.rm = TRUE))) * 100,
+      mean = mean(PPSTRES, na.rm = TRUE),
+      CV = (sd(PPSTRES, na.rm = TRUE) / mean(PPSTRES, na.rm = TRUE)) * 100,
+      sd = sd(PPSTRES, na.rm = TRUE),
+      min = min(PPSTRES, na.rm = TRUE),
+      max = max(PPSTRES, na.rm = TRUE),
+      median = median(PPSTRES, na.rm = TRUE),
+      count.missing = sum(is.na(PPSTRES)),
       count.total = n()
     ) %>%
     ungroup() %>%
diff --git a/R/export_cdisc.R b/R/export_cdisc.R
index 583b0b5f..e1b8f9df 100644
--- a/R/export_cdisc.R
+++ b/R/export_cdisc.R
@@ -128,7 +128,7 @@ export_cdisc <- function(res_nca) {
         unname(unlist(res_nca$data$conc$columns$groups)), "start", "end", "PPTESTCD"
       )))
     )  %>%
-    arrange(USUBJID, DOSNO, !is.na(PPORRES)) %>%
+    arrange(USUBJID, DOSNO, !is.na(PPSTRES)) %>%
     # Identify all dulicates (fromlast and fromfirst) and keep only the first one
     filter(!duplicated(paste0(USUBJID, DOSNO, PPTESTCD))) %>%
     ungroup() %>%
@@ -166,14 +166,14 @@ export_cdisc <- function(res_nca) {
       # Specific ID variables
       PPSPID = "TBD",
       # TODO Results in Standard Units if ORRESU is not in standard units
-      PPSTRESN = as.numeric(PPORRES),
-      PPSTRESC = as.character(PPORRES),
-      PPSTRESU = PPORRESU,
+      PPSTRESN = as.numeric(PPSTRES),
+      PPSTRESC = as.character(PPSTRES),
+      PPSTRESU = PPSTRESU,
       # Status and Reason for Exclusion
-      PPSTAT = ifelse(is.na(PPORRES) | (PPORRES == 0 & PPTESTCD == "CMAX"), "NOT DONE",  ""),
+      PPSTAT = ifelse(is.na(PPSTRES) | (PPSTRES == 0 & PPTESTCD == "CMAX"), "NOT DONE",  ""),
       PPREASND = case_when(
         !is.na(exclude) ~ exclude,
-        is.na(PPORRES) ~ "Unspecified",
+        is.na(PPSTRES) ~ "Unspecified",
         TRUE ~ ""
       ),
       # Datetime
diff --git a/R/flexible_violinboxplot.R b/R/flexible_violinboxplot.R
index 2ff12ca2..d8864453 100644
--- a/R/flexible_violinboxplot.R
+++ b/R/flexible_violinboxplot.R
@@ -61,12 +61,12 @@ flexible_violinboxplot <- function(boxplotdata,
 
   # ylabel of violin/boxplot
   ylabel <- {
-    if (box_data$PPORRESU[1] == "unitless" ||
-          is.na(box_data$PPORRESU[1]) ||
-          is.null(box_data$PPORRESU)) {
+    if (box_data$PPSTRESU[1] == "unitless" ||
+          is.na(box_data$PPSTRESU[1]) ||
+          is.null(box_data$PPSTRESU)) {
       parameter
     } else {
-      paste(parameter, " [", box_data$PPORRESU[1], "]")
+      paste(parameter, " [", box_data$PPSTRESU[1], "]")
     }
   }
 
@@ -75,7 +75,7 @@ flexible_violinboxplot <- function(boxplotdata,
     data = box_data %>% arrange(!!!syms(colorvars)),
     aes(
       x = interaction(!!!syms(xvars), sep = "\n"),
-      y = PPORRES,
+      y = PPSTRES,
       color = interaction(!!!syms(colorvars))
     )
   )
diff --git a/R/get_conversion_factor.R b/R/get_conversion_factor.R
new file mode 100644
index 00000000..1d886c68
--- /dev/null
+++ b/R/get_conversion_factor.R
@@ -0,0 +1,28 @@
+#' Transform Units
+#'
+#' This function transforms a value from an initial unit to a target unit.
+#'
+#' @param initial_unit A character string representing the initial unit.
+#' @param target_unit A character string representing the target unit.
+#' @returns A numeric value for the conversion factor from the initial to the target unit,
+#' or NA if the units are not convertible.
+#' @examples
+#' get_conversion_factor("meter", "kilometer")
+#' get_conversion_factor("sec", "min")
+#' @importFrom units set_units
+#' @export
+get_conversion_factor <- Vectorize(function(initial_unit, target_unit) {
+  tryCatch({
+    conversion <- units::set_units(
+      units::set_units(1, initial_unit, mode = "standard"),
+      target_unit, mode = "standard"
+    )
+    unname(as.numeric(conversion))
+  }, error = function(e) {
+    if (initial_unit == target_unit) {
+      1
+    } else {
+      NA
+    }
+  })
+}, USE.NAMES = FALSE)
diff --git a/R/pivot_wider_pknca_results.R b/R/pivot_wider_pknca_results.R
index e7d36941..58ef28b9 100644
--- a/R/pivot_wider_pknca_results.R
+++ b/R/pivot_wider_pknca_results.R
@@ -21,24 +21,24 @@ pivot_wider_pknca_results <- function(myres) {
 
   # Get all names with units and make a dictionary structure
   dict_pttestcd_with_units <- myres$result %>%
-    select(PPTESTCD, PPORRESU) %>%
+    select(PPTESTCD, PPSTRESU) %>%
     distinct() %>%
-    pull(PPORRESU, PPTESTCD)
+    pull(PPSTRESU, PPTESTCD)
 
   # Filter out infinite AUCs and pivot the data to incorporate
   # the parameters into columns with their units
   infinite_aucs_vals <- myres$result %>%
     distinct() %>%
     filter(type_interval == "main")  %>%
-    select(-PPORRESU, -exclude, -type_interval) %>%
-    pivot_wider(names_from = PPTESTCD, values_from = PPORRES)
+    select(-PPSTRESU, -PPORRES, -PPORRESU, -exclude, -type_interval) %>%
+    pivot_wider(names_from = PPTESTCD, values_from = PPSTRES)
 
   infinite_aucs_exclude <- myres$result %>%
     distinct() %>%
     filter(type_interval == "main") %>%
-    select(-PPORRES, -PPORRESU, -type_interval)  %>%
-    mutate(PPTESTCD = paste0("exclude.", PPTESTCD)) %>%
-    pivot_wider(names_from = PPTESTCD, values_from = exclude)
+    select(-PPSTRES, -PPSTRESU, -PPORRES, -PPORRESU, -type_interval)  %>%
+    mutate(exclude.PPTESTCD = paste0("exclude.", PPTESTCD)) %>%
+    pivot_wider(names_from = exclude.PPTESTCD, values_from = exclude)
 
   infinite_aucs <- inner_join(infinite_aucs_vals, infinite_aucs_exclude)
 
@@ -70,10 +70,10 @@ pivot_wider_pknca_results <- function(myres) {
         interval_name = paste0(signif(start), "-", signif(end)),
         interval_name_col = paste0(PPTESTCD, "_", interval_name)
       ) %>%
-      select(-exclude, -PPORRESU, -start, -end,
+      select(-exclude, -PPSTRESU, -PPORRES, -PPORRESU, -start, -end,
              -PPTESTCD, -interval_name, -type_interval) %>%
       pivot_wider(names_from = interval_name_col,
-                  values_from = PPORRES)
+                  values_from = PPSTRES)
 
     interval_aucs_exclude <- myres$result %>%
       filter(type_interval == "manual", startsWith(PPTESTCD, "aucint")) %>%
@@ -81,7 +81,7 @@ pivot_wider_pknca_results <- function(myres) {
         interval_name = paste0(signif(start), "-", signif(end)),
         interval_name_col = paste0("exclude.", PPTESTCD, "_", interval_name)
       )  %>%
-      select(-PPORRES, -PPORRESU, -start, -end,
+      select(-PPSTRES, -PPSTRESU, -PPORRES, -PPORRESU, -start, -end,
              -PPTESTCD, -interval_name, -type_interval) %>%
       pivot_wider(names_from = interval_name_col, values_from = exclude)
 
@@ -93,7 +93,7 @@ pivot_wider_pknca_results <- function(myres) {
         .x
       ))
 
-    all_aucs <- inner_join(infinite_aucs_with_lambda, interval_aucs, all = TRUE)
+    all_aucs <- inner_join(infinite_aucs_with_lambda, interval_aucs)
   } else {
     all_aucs <- infinite_aucs_with_lambda
   }
diff --git a/inst/shiny/data/DummyRO_ADNCA.csv b/inst/shiny/data/DummyRO_ADNCA.csv
index 4d85ce9c..7d8b031f 100644
--- a/inst/shiny/data/DummyRO_ADNCA.csv
+++ b/inst/shiny/data/DummyRO_ADNCA.csv
@@ -536,4 +536,4 @@
 "XX01",25201,"Analyte01","SERUM","EVERY 3 WEEKS",1,7.96166666666667,7.96166666666667,8,8,5.83,"Analyte01","ug/mL","intravascular",35,51,"M","WHITE",1.53,"Hours","mg",0,"Analyte01","Cycle 1 Day 1",5.83,"ug/mL",0,"2022-09-13 11:34:00",339203,"Dummy Treatment Arm A","Dummy Treatment Arm P","2022-08-23 11:59:00",176.5,81.6,"kg","cm",1.58,0
 "XX01",25201,"Analyte01","SERUM","EVERY 3 WEEKS",1,25.3016666666667,25.3016666666667,48,48,4.28,"Analyte01","ug/mL","intravascular",35,51,"M","WHITE",1.53,"Hours","mg",0,"Analyte01","Cycle 1 Day 2",4.28,"ug/mL",0,"2022-09-13 11:34:00",339203,"Dummy Treatment Arm A","Dummy Treatment Arm P","2022-08-23 11:59:00",176.5,81.6,"kg","cm",1.53,0
 "XX01",25201,"Analyte01","SERUM","EVERY 3 WEEKS",1,75.6816666666667,75.6816666666667,144,144,1.95,"Analyte01","ug/mL","intravascular",35,51,"M","WHITE",1.53,"Hours","mg",0,"Analyte01","Cycle 1 Day 4",1.95,"ug/mL",0,"2022-09-13 11:34:00",339203,"Dummy Treatment Arm A","Dummy Treatment Arm P","2022-08-23 11:59:00",176.5,81.6,"kg","cm",1.54,0
-"XX01",25201,"Analyte01","SERUM","EVERY 3 WEEKS",1,171.701666666667,171.701666666667,336,336,0.258,"Analyte01","ug/mL","intravascular",35,51,"M","WHITE",1.53,"Hours","mg",0,"Analyte01","Cycle 1 Day 8",0.258,"ug/mL",0,"2022-09-13 11:34:00",339203,"Dummy Treatment Arm A","Dummy Treatment Arm P","2022-08-23 11:59:00",176.5,81.6,"kg","cm",1.5,0
+"XX01",25201,"Analyte01","SERUM","EVERY 3 WEEKS",1,171.701666666667,171.701666666667,336,336,0.258,"Analyte01","ug/mL","intravascular",35,51,"M","WHITE",1.53,"Hours","mg",0,"Analyte01","Cycle 1 Day 8",0.258,"ug/mL",0,"2022-09-13 11:34:00",339203,"Dummy Treatment Arm A","Dummy Treatment Arm P","2022-08-23 11:59:00",176.5,81.6,"kg","cm",1.5,0
\ No newline at end of file
diff --git a/inst/shiny/global.R b/inst/shiny/global.R
index 99abbd5c..bc9bc5e7 100644
--- a/inst/shiny/global.R
+++ b/inst/shiny/global.R
@@ -4,6 +4,8 @@ LABELS <- read.csv(system.file("shiny/data/adnca_labels.csv", package = "aNCA"))
 
 source("modules/slope_selector.R")
 
+source("modules/units_table.R")
+
 source("functions/partial_auc_input.R")
 
 source("modules/tlg_plot.R")
diff --git a/inst/shiny/modules/slope_selector.R b/inst/shiny/modules/slope_selector.R
index cbd6bfff..c318d7aa 100644
--- a/inst/shiny/modules/slope_selector.R
+++ b/inst/shiny/modules/slope_selector.R
@@ -123,6 +123,7 @@ slope_selector_server <- function(
     observeEvent(list(
       plot_data(), res_nca(), input$plots_per_page, input$search_patient, current_page()
     ), {
+      req(res_nca())
       log_trace("{id}: Updating displayed plots")
 
       # Make sure the search_patient input is not NULL
diff --git a/inst/shiny/modules/tab_visuals.R b/inst/shiny/modules/tab_visuals.R
index 5b2a1ead..92e87065 100644
--- a/inst/shiny/modules/tab_visuals.R
+++ b/inst/shiny/modules/tab_visuals.R
@@ -391,6 +391,7 @@ tab_visuals_server <- function(id, data, grouping_vars, res_nca) {
     # Reactive expression for summary table based on selected group and parameters
     summary_stats <- reactive({
       req(input$summary_groupby, input$select_display_parameters)
+      req(res_nca())
 
       # Calculate summary stats and filter by selected parameters
       calculate_summary_stats(res_nca(), input$summary_groupby) %>%
@@ -444,7 +445,7 @@ tab_visuals_server <- function(id, data, grouping_vars, res_nca) {
     # Create formatted Box plot data: PKNCA + PP results, linking DOSEA + PPTESTCD
     boxplotdata <- reactive({
       group_columns <- unname(unlist(res_nca()$data$conc$columns$groups))
-
+      req(res_nca())
       left_join(
         res_nca()$result %>%
           filter(
diff --git a/inst/shiny/modules/units_table.R b/inst/shiny/modules/units_table.R
new file mode 100644
index 00000000..b15d5aa4
--- /dev/null
+++ b/inst/shiny/modules/units_table.R
@@ -0,0 +1,198 @@
+units_table_ui <- function(id) {
+  ns <- NS(id)
+  # Button to open a module message with the parameter units table #
+  tagList(
+    actionButton(
+      ns("open_units_table"),
+      icon = icon("scale-balanced"),
+      label = "Parameter Units",
+      disabled = TRUE
+    )
+  )
+}
+
+units_table_server <- function(id, mydata, res_nca = reactiveVal(NULL)) {
+  moduleServer(id, function(input, output, session) {
+    ns <- session$ns
+
+    #' Allow user to open the units table when data is available
+    observeEvent(mydata(), {
+      updateActionButton(session = session,
+                         inputId = "open_units_table",
+                         disabled = FALSE)
+    })
+
+    # Define the modal message displayed with the parameter units table #
+    observeEvent(input$open_units_table, {
+
+      # Keep in a variable all analytes available
+      analyte_choices <- unique(mydata()$conc$data[[mydata()$conc$columns$groups$group_analyte]])
+
+      # Show the modal message with the units table and an analyte selector
+      showModal(modalDialog(
+        title = tagList(
+          span("Units of NCA parameter results")
+        ),
+        selectInput(
+          inputId = ns("select_unitstable_analyte"),
+          multiple = TRUE,
+          label = "Select Analyte:",
+          choices = analyte_choices,
+          selected = analyte_choices
+        ),
+        DTOutput(ns("modal_units_table")),
+        footer = tagList(
+          modalButton("Close"),
+          actionButton(ns("save_units_table"), "Save Units Table")
+        ),
+        size = "l"
+      ))
+    })
+
+    # Define the parameter units table and how is displayed to the user #
+    modal_units_table <- reactiveVal(NULL)
+    observeEvent(list(mydata(), input$select_unitstable_analyte), {
+      req(mydata())
+      req(input$select_unitstable_analyte)
+      analyte_column <- mydata()$conc$columns$groups$group_analyte
+      modal_units_table_data <- mydata()$units %>%
+        group_by(PPTESTCD, PPORRESU, PPSTRESU, conversion_factor) %>%
+        filter(!!sym(analyte_column) %in% input$select_unitstable_analyte) %>%
+        rename(`Parameter` = PPTESTCD,
+               `Default unit` = PPORRESU,
+               `Conversion Factor` = conversion_factor,
+               `Custom unit` = PPSTRESU) %>%
+        mutate(Analytes = paste(!!sym(analyte_column), collapse = ", ")) %>%
+        ungroup() %>%
+        select(`Analytes`, `Parameter`, `Default unit`, `Custom unit`, `Conversion Factor`)
+      modal_units_table(modal_units_table_data)
+    })
+
+    # Define which parameters where choosen by the user
+    params_to_calculate <- reactive({
+      names(purrr::keep(mydata()$intervals, ~ is.logical(.x) && any(.x)))
+    })
+
+    params_to_calculate_array_str <- reactive({
+      paste0("['", paste(params_to_calculate(), collapse = "','"), "']")
+    })
+
+    #' Rendering the modal units table
+    output$modal_units_table <- DT::renderDT({
+      datatable(
+        data = modal_units_table() %>%
+          mutate(`Conversion Factor` = signif(`Conversion Factor`, 3)),
+        escape = FALSE,
+        class = "table table-striped table-bordered",
+        rownames = FALSE,
+        editable = list(
+          target = "cell",
+          disable = list(
+            columns = c(0, 1, 2)
+          )
+        ),
+        options = list(
+          order = list(2, "desc"),
+          paging = FALSE,
+          searching = TRUE,
+          autoWidth = TRUE,
+          dom = "ft",
+          # Display only rows with the parameters to run for the NCA
+          rowCallback = htmlwidgets::JS(
+            paste0("
+              function(row, data, index) {
+              var paramsToCalculate = ", params_to_calculate_array_str(),
+              ";
+              if (paramsToCalculate.indexOf(data[1]) === -1) {
+              $(row).hide();
+              }
+              }"
+            )
+          ),
+          columnDefs = list(
+            list(
+              visible = FALSE,
+              targets = c()
+            )
+          )
+        )
+      )
+    })
+
+    # Accept user modifications in the modal units table
+    observeEvent(input$modal_units_table_cell_edit, {
+      info <- input$modal_units_table_cell_edit
+      modal_units_table <- modal_units_table()
+      modal_units_table[info$row, info$col + 1] <- info$value
+
+      if (names(modal_units_table)[info$col + 1] == "Custom unit") {
+        def_unit <- modal_units_table[info$row, "Default unit"]
+        cust_unit <- modal_units_table[info$row, "Custom unit"]
+        modal_units_table[info$row, "Conversion Factor"] <- get_conversion_factor(def_unit,
+                                                                                  cust_unit)
+      }
+
+      modal_units_table(modal_units_table)
+    })
+
+    # When save button is pressed substitute the original units table based on the modal one
+    observeEvent(input$save_units_table, {
+
+      # Make sure there are no missing entries (no NA in conversion factor)
+      if (any(is.na(modal_units_table()$`Conversion Factor`))) {
+
+        invalid_entries <- modal_units_table() %>%
+          filter(is.na(`Conversion Factor`)) %>%
+          mutate(entry = paste0(Parameter, " (", Analytes, ")")) %>%
+          pull(entry)
+
+        showNotification(
+          paste0("Please, make sure to use only recognised convertible units in `Custom Unit`",
+                 "(i.e, day, hr, min, sec, g/L).",
+                 " If not, introduce yourself the corresponding `Conversion Factor` value in: ",
+                 paste(invalid_entries, collapse = ", ")),
+          duration = NULL,
+          closeButton = TRUE,
+          type = "warning"
+        )
+        return()
+      }
+
+      # Tranforms the modal units table back to the original one
+      modal_units_table <- modal_units_table() %>%
+        mutate(Analytes = strsplit(Analytes, ", ")) %>%
+        unnest(Analytes) %>%
+        rename(ANALYTE = `Analytes`,
+               PPTESTCD = `Parameter`,
+               PPORRESU = `Default unit`,
+               PPSTRESU = `Custom unit`,
+               conversion_factor = `Conversion Factor`)
+
+      # Close the modal message window for the user
+      removeModal()
+
+      # Updates units table of mydata and res_nca according to the user's changes
+      mydata <- mydata()
+      mydata$units <- modal_units_table
+      mydata(mydata)
+
+      # If there are already results produced, make sure they are also adapted
+      if (!is.null(res_nca())) {
+        res_nca <- res_nca()
+        res_nca$data$units <- modal_units_table
+        res_nca$result <- res_nca$result %>%
+          select(-PPSTRESU, -PPSTRES) %>%
+          left_join(
+            modal_units_table,
+            by = intersect(names(.), names(modal_units_table))
+          ) %>%
+          mutate(PPSTRES = PPORRES * conversion_factor) %>%
+          select(-conversion_factor)
+        res_nca(res_nca)
+
+      }
+
+    })
+
+  })
+}
diff --git a/inst/shiny/tabs/nca.R b/inst/shiny/tabs/nca.R
index d3498a91..b82db7a0 100644
--- a/inst/shiny/tabs/nca.R
+++ b/inst/shiny/tabs/nca.R
@@ -240,6 +240,13 @@ observeEvent(input$submit_analyte, priority = 2, {
     )
   )
 
+  # Redefine units for each analyte and for potential customizations
+  unique_analytes <- unique(mydata$conc$data[[mydata$conc$columns$groups$group_analyte]])
+  analyte_column <- mydata$conc$columns$groups$group_analyte
+  mydata$units <- tidyr::crossing(mydata$units,
+                                  !!sym(analyte_column) := unique_analytes)  %>%
+    dplyr::mutate(PPSTRESU = PPORRESU, conversion_factor = 1)
+
   mydata(mydata)
 })
 
@@ -353,8 +360,10 @@ observeEvent(input$removeAUC, {
     auc_counter(auc_counter() - 1)
   }
 })
+
 # NCA button object
 myres <- reactiveVal(NULL)
+
 observeEvent(input$nca, {
   req(mydata())
 
@@ -447,7 +456,8 @@ observeEvent(input$nca, {
   updateTabsetPanel(session, "ncapanel", selected = "Results")
 })
 
-res_nca <- eventReactive(pk_nca_trigger(), {
+res_nca <- reactiveVal(NULL)
+observeEvent(pk_nca_trigger(), {
   req(mydata())
   withProgress(message = "Calculating NCA...", value = 0, {
     myres <- PKNCA::pk.nca(data = mydata(), verbose = FALSE)
@@ -463,10 +473,15 @@ res_nca <- eventReactive(pk_nca_trigger(), {
       dplyr::select(names(myres$result))
 
     # Return the result
-    return(myres)
+    res_nca(myres)
   })
 })
 
+# Parameter unit changes option: Opens a modal message with a units table to edit
+# It updates $units table of mydata & res_nca when the user saves their changes
+units_table_server("units_table_preNCA", mydata, res_nca)
+units_table_server("units_table_postNCA", mydata, res_nca)
+
 # TABSET: Results ==============================================================
 
 # In the result tabset we can view the NCA results, slope caclulation und exclusions table.
@@ -479,7 +494,7 @@ final_res_nca <- reactiveVal(NULL)
 
 # creative final_res_nca, aiming to present the results in a more comprehensive way
 observeEvent(res_nca(), {
-
+  req(res_nca())
   # Create a reshaped object that will be used to display the results in the UI
   final_res_nca <- pivot_wider_pknca_results(res_nca())
 
@@ -503,9 +518,9 @@ observeEvent(res_nca(), {
 
   # Include units for all column names
   dict_pttestcd_with_units <- res_nca()$result %>%
-    select(PPTESTCD, PPORRESU) %>%
+    select(PPTESTCD, PPSTRESU) %>%
     unique() %>%
-    pull(PPORRESU, PPTESTCD)
+    pull(PPSTRESU, PPTESTCD)
 
   final_res_nca <- final_res_nca %>%
     rename_with(~ifelse(
diff --git a/inst/shiny/ui.R b/inst/shiny/ui.R
index 3ca5472c..9e461980 100644
--- a/inst/shiny/ui.R
+++ b/inst/shiny/ui.R
@@ -69,6 +69,7 @@ fluidPage(
                   ),
                   selected = "lin up/log down"
                 ),
+                units_table_ui("units_table_preNCA"),
                 h4("Data imputation"),
                 tags$div(
                   checkboxInput(
@@ -152,7 +153,7 @@ fluidPage(
                 fluidRow(
                   column(
                     width = 6,
-                    checkboxInput("rule_aucpext_pred", "AUCPEP (% ext.predicted): "),
+                    checkboxInput("rule_aucpext_pred", "AUCPEP (% ext.predicted): ")
                   ),
                   column(
                     width = 6,
@@ -176,7 +177,7 @@ fluidPage(
                 fluidRow(
                   column(
                     width = 6,
-                    checkboxInput("rule_span_ratio", "SPAN: "),
+                    checkboxInput("rule_span_ratio", "SPAN: ")
                   ),
                   column(
                     width = 6,
@@ -198,7 +199,7 @@ fluidPage(
                 )
               ),
 
-              tabPanel("Slope Selector", slope_selector_ui("slope_selector")),
+              tabPanel("Slope Selector", slope_selector_ui("slope_selector"))
 
             )
           ),
@@ -216,10 +217,11 @@ fluidPage(
                   multiple = TRUE,
                   options = list(`actions-box` = TRUE)
                 ),
+                units_table_ui("units_table_postNCA"),
                 DTOutput("myresults"),
                 tableOutput("summaryTable"),
                 actionButton("download", "Download the NCA Data"),
-                downloadButton("local_download_NCAres", "Download locally the NCA Data"),
+                downloadButton("local_download_NCAres", "Download locally the NCA Data")
               ),
               tabPanel(
                 "Slopes",
diff --git a/man/get_conversion_factor.Rd b/man/get_conversion_factor.Rd
new file mode 100644
index 00000000..00277899
--- /dev/null
+++ b/man/get_conversion_factor.Rd
@@ -0,0 +1,24 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/get_conversion_factor.R
+\name{get_conversion_factor}
+\alias{get_conversion_factor}
+\title{Transform Units}
+\usage{
+get_conversion_factor(initial_unit, target_unit)
+}
+\arguments{
+\item{initial_unit}{A character string representing the initial unit.}
+
+\item{target_unit}{A character string representing the target unit.}
+}
+\value{
+A numeric value for the conversion factor from the initial to the target unit,
+or NA if the units are not convertible.
+}
+\description{
+This function transforms a value from an initial unit to a target unit.
+}
+\examples{
+get_conversion_factor("meter", "kilometer")
+get_conversion_factor("sec", "min")
+}
diff --git a/tests/testthat/test-get_conversion_factor.R b/tests/testthat/test-get_conversion_factor.R
new file mode 100644
index 00000000..32a74f68
--- /dev/null
+++ b/tests/testthat/test-get_conversion_factor.R
@@ -0,0 +1,51 @@
+describe("get_conversion_factor", {
+  it("handles simple time units", {
+    expect_equal(get_conversion_factor("hr", "minute"), 60)
+    expect_equal(get_conversion_factor("minute", "second"), 60)
+    expect_equal(get_conversion_factor("day", "hour"), 24)
+    expect_equal(get_conversion_factor("second", "minute"), 1 / 60)
+    expect_equal(get_conversion_factor("hour", "second"), 3600)
+    expect_equal(get_conversion_factor("minute", "hour"), 1 / 60)
+    expect_equal(get_conversion_factor("day", "minute"), 1440)
+  })
+
+  it("handles simple concentration units", {
+    expect_equal(get_conversion_factor("mg/L", "g/L"), 0.001)
+    expect_equal(get_conversion_factor("g/dL", "kg/L"), 0.01)
+    expect_equal(get_conversion_factor("ug/mL", "mg/L"), 1)
+    expect_equal(get_conversion_factor("kg/L", "g/L"), 1000)
+    expect_equal(get_conversion_factor("mg/dL", "g/L"), 0.01)
+    expect_equal(get_conversion_factor("g/L", "mg/L"), 1000)
+    expect_equal(get_conversion_factor("kg/L", "mg/L"), 1e6)
+  })
+
+  it("handles combined units", {
+    expect_equal(get_conversion_factor("Hours*ug/mL", "Hours*mg/L"), 1)
+    expect_equal(get_conversion_factor("Hours^2*ug/mL", "Hours^2*mg/L"), 1)
+    expect_equal(get_conversion_factor("(Hours*ug/mL)/mg", "(Hours*mg/L)/g"), 1000)
+    expect_equal(get_conversion_factor("mg/(Hours*ug/mL)", "g/(Hours*mg/L)"), 0.001)
+    expect_equal(get_conversion_factor("(ug/mL)/(Hours*ug/mL)", "(mg/L)/(Hours*mg/L)"), 1)
+    expect_equal(get_conversion_factor("Hours*mg/L", "Hours*ug/mL"), 1)
+    expect_equal(get_conversion_factor("Hours^2*mg/L", "Hours^2*ug/mL"), 1)
+    expect_equal(get_conversion_factor("Hours*kg/L", "Hours*g/L"), 1000)
+    expect_equal(get_conversion_factor("Hours*mg/L", "Hours*kg/L"), 1e-6)
+  })
+
+  it("returns NA for non-convertible units", {
+    expect_true(is.na(get_conversion_factor("meter", "second")))
+    expect_true(is.na(get_conversion_factor("kg", "hour")))
+    expect_true(is.na(get_conversion_factor("liter", "gram")))
+    expect_true(is.na(get_conversion_factor("meter", "liter")))
+    expect_true(is.na(get_conversion_factor("second", "gram")))
+    expect_true(is.na(get_conversion_factor("hour", "meter")))
+  })
+
+  it("handles vector inputs", {
+    expect_equal(get_conversion_factor(c("hr", "minute"), c("minute", "second")), c(60, 60))
+    expect_equal(get_conversion_factor(c("day", "mg/L"), c("hour", "g/L")), c(24, 0.001))
+    expect_equal(get_conversion_factor(c("second", "kg/L"), c("minute", "g/L")), c(1 / 60, 1000))
+    expect_equal(get_conversion_factor(c("hour", "ug/mL"), c("second", "mg/L")), c(3600, 1))
+    expect_equal(get_conversion_factor(c("minute", "day"), c("second", "hour")), c(60, 24))
+    expect_equal(get_conversion_factor(c("g/L", "kg/L"), c("mg/L", "g/L")), c(1000, 1000))
+  })
+})