Knowledge Base for Supply App

Trial master data

Table of contents:

1. Simulation parameters
2. Products
3. Locations
   1. Lot pooled trials
4. Treatment
5. Patient

As with the company Master Data, some concepts will be defined at trial level to be used in trial models afterwards.

Simulation parameters

In the Simulation parameters tab, the user assigns a name to the trial and defines different parameters:

A maximum budget, overage, risk of missed visits and risk of out of stock: these values are only used as references and will trigger a /  messages when inspecting the simulation results if the constraints are not respected.

Products

In the Products tab, the user defines multiple concepts related to the medication used in the trial:

• The package types that will be dispensed to patients during their treatment.
• The label groups that can be applied to all or some of the package types. Label groups will be applied for the whole trial duration.

• The products, that are combinations of stock keeping units, package types and label groups. For example, a package type A for which two label groups can be applied will generate two different products.
• The lot numbers, which are the different lot numbers to be used in the trial: past, present and future. In most cases, most of the future lot numbers will be undefined, which means that the user will have to define their name. It is ok to define only one lot number for the future, and use it for all future productions (except if some future productions have special restrictions on where they can be shipped).

Once created, the lot pooled trials can be associated with site groups/depots in the corresponding table.

Adding site groups/depots is done through the dedicated actions next to the Site groups and Depots tables (see image below).

Clicking on any of those buttons opens a new window where you can select site groups/depots you want to associate with a lot pooled trial. The selected site groups will be added to the site groups table. In case lot pooled trials are also selected, one row will be added for each combination of site group & lot pooled trial, e.g., in the image below, 6 new rows will be created.

The combination of a site group/depot with a lot pooled trial will be considered as a separated site group/depot in the trial as well as in the simulation outputs. Site groups/depots will be displayed with their names defined in the Name column (see image below).

Treatment

In the Treatment tab, the user defines:

• The patient groups to be used for the recruitment. It will be possible to define different recruitment rates per patient group. Typically, this concept can be used to represent cohorts being enrolled separately. There should be at least one patient group defined.

• All the patient visits to consider in the trial, including the (non-dispensing) end-of-treatment visit. Additional visits for safety follow-up treatments will be defined inside the trial setups.
• The treatment arms: there should always be at least one default (e.g. “Not yet randomized”) treatment arm.
• The initial treatment arm, that is, the treatment arm on which patients start. This treatment arm will typically be the “Not yet randomized” treatment arm, if defined above.
• The dose levels: if there are no dose levels, the user has to define a default dose level that will be constant during the whole trial duration.
• The initial dose level, that is, the dose level on which the patients start.

Patient

In the Patient tab, the user defines the patient characteristics that will have an impact on the treatment to be received, namely:

• Characteristics that influence the randomization (e.g. strata).
• Characteristics that influence the medication to be received (e.g. weight groups, BSA groups, age).
• Characteristics that influence the titration/dosage probabilities (e.g. age).

These will be defined as patient attributes, that will each have attribute categories. For example, an attribute can be “strata”, and its categories can be “Female” and “Male”. By default, a trial will be created with two attributes: strata and weight factor, each having one default attribute category.

The user also has to choose a patient attribute to define a pre-randomization factor that will impact the randomization ratio (see Treatment setup – Treatment visits & Randomization ). If there is no patient attribute impacting the randomization, a default patient attribute still has to be chosen.