Dosing events

Dosing Events

The Dosing Events section offers an interactive workspace for visualising dose administration patterns across subjects. Whether you need a quick overview of how many doses each participant received, a detailed look at infusion times, or a check on intervals between administrations, this section provides an array of pre-configured plots that can be customised to your needs.

Figure 1. Path to the Dosing events section in the Data Management module.

Five tabs are available, each devoted to a specific view of twelve events:

  1. Number – total doses per subject
  2. Amount – dose amounts per subject
  3. Interval – spacing between doses
  4. Times – actual dosing timestamps
  5. Infusion – infusion-duration profiles

1. Number (Number of doses)

Select the dose-amount column (default AMT) in “Choose your Dose column:” and click .

Configure the plot:

  • Axis names (x name, y name)
  • Flip coordinates (optional)
  • Filter: Apply conditional filters to display a data subset of subjects
  • facet by: Create subplots based on any column in the dataset
  • Free scales: Enable individual y-axis scaling for each facet
  • color by: Assign line colors using any column (e.g., treatment group, gender)
  • line type by: Assign line styles based on a selected column (max 5 levels recommended for clarity)

Click . A bar chart appears showing each Subject ID against the number of doses received.

Figure 2. Number tab displaying the plot configuration panel and the resulting plot with number of doses per Subject ID. In this example, a faceted by VKORC1_genotype has been applied with free axis scales enabled for each facet. Bars colored by the SEX column.

Use to export the figure to the working directory set in Data section.

2 Amount (Dose amount)

Steps mirror the Number tab, with one extra toggle: Show dose amount. The resulting plot displays dose amounts per subject (optionally overlaid as text if the toggle is on). Save with .

Figure 3. Amount tab displaying the plot configuration panel and the resulting plot with dose amount per Subject ID. Bars colored by the SEX column with Show dose amount option selected.

3 Interval (Interval between doses)

Again select the dose column, confirm, and configure using the same options as the Number tab. This graph is only available for treatments with more than one dose per Subject ID. On , a box-and-whisker plot appears, illustrating the distribution of inter-dose intervals for every subject. Save via .

Figure 4. Interval tab displaying the plot configuration panel and the resulting box plot with interval between doses per Subject ID, colored by the SEX column. This example uses a dataset with more than one dose per subject.

4 Times (Time of doses)

After selecting and confirming the dose column, a streamlined set of options appears:

  • Axis names, Free scales, Filter ID, color by.

Press . The output is a faceted panel—one facet per Subject ID—containing vertical bars at every dosing time, making shifts in scheduling easy to spot.

Figure 5. Times tab displaying the plot configuration panel and the resulting vertical bars plot with time of doses per Subject ID with free scales, colored by the SEX column. This example uses a dataset with more than one dose per subject.

Save with .

5 Infusion (Duration of dose)

Choose the infusion-duration column (default DUR) and click .

Configure the plot, identical controls to the Number tab, with one extra toggle: Show infusion time. Click . A bar chart appears showing infusion durations per subject.

Save with .

Figure 6. Infusion tab displaying the plot configuration panel and the resulting plot with infusion duration per Subject ID. Bars colored by the SEX column with Show infusion time option selected.This example uses a dataset with intravenous dose and its corresponding DUR column.

The Dosing Events section delivers quick, visually rich insights into dosing schedules, quantities, and infusion characteristics—key information for understanding treatment exposure before modelling. After verifying dosing patterns here, you can proceed confidently to further exploratory analyses or pharmacometric modelling steps.