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General context

The core module of CT-FAST is the data model that allows for the defining of any type of trial design, from the simplest to the most complex, in a generic and straightforward manner. The following parameters are covered:

General trial parameters:

Trial stopping criteria (total patients enrolled / randomized / complete, event counting)
Enrollment type (competitive at trial/country level, non-competitive)
Randomization level (trial / region / country / site)

Treatment parameters:

Enrollment predictions (trial / country / site level)
Stratification/prognostic factors
Factors used to define variable dispensing (e.g. patient’s weight)

 

Visits, visit intervals and visit windows
Treatment groups, randomization ratio
Dose levels
Dispensing plan
Titration, trial phases

Supply network parameters: (Stochastic model only)

Distribution centers
Countries
Depots/affiliates
Label/language groups
Sites
Shipping lead times
Package types, shelf-life, packaging form (bottle/vial/blister pack, …)
Production schedule

 
 

The CT-FAST core module also contains a reporting engine that allows for the generation of a ready-to-print report in the industry standard format, PDF, The report summarizes all input data and presents simulation results with tables and graphics. Results may also be exported in a spreadsheet format to allow for further analysis.

Reports can be extensively customized to the specific needs of the simulation. They may include:

All input parameters and assumptions
Forecasted enrollment, total trial duration
Medication usage for each kit type and label group, with associated variability

 

Production plan (dates and quantities) for each kit type and label group
IVRS inventory management parameters for each location in the distribution network (distribution centers, local depots, investigational sites)
General indicators related to the supply chain performance presented along with their empirical probability:

- Shipment frequency and volume
- Amount of medication kits wasted, Overages
- Probability of undersupply

 
 
   

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