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Clinical Trial Inventory Management

You should expect your IRT to perform the essential role of ensuring the right drug is on site at the right time for each patient, but an advanced IRT will do so much more.

Coupling the expertise of our RTSM specialists with robust and advanced inventory management approaches, Calyx IRT helps you:

Reduce your Effort
Calyx IRT reduces the burden of monitoring site stock against patient needs, automatically adapting a site’s stock to its recruitment rate.

Improve your Carbon Footprint
Calyx IRT supports all of your drug supply management aims, from limiting overage and keeping wastage to a minimum, to reducing the number of shipments raised.

Inventory Management Approaches


To ensure the right drug is available at the right time for each patient, Calyx IRT is designed based on assumptions about differing site recruitment rates. Calyx supply experts recommend what range of strategies and associated resupply amounts are appropriate, both of which can easily be changed with immediate effect as real-world data comes in.

Calyx IRT combines this with ‘prediction’ – because the system knows what treatment a patient is assigned, what their current & future treatment options are and what their schedule of assessments is, it can predict exactly what they need & when. And, if the protocol requires changes to patient treatment, the system will automatically change site resupply. For example, when the first patient at a site is approaching an open-label extension phase, or when a treatment arm is dropped.

Advanced Inventory Management

Calyx can optimize site supplies even when we don’t know what a patient will next receive, if the protocol allows dose titrations, modifications, or treatment pauses. This benefit is possible through a range of our standard and advanced inventory management options which include:

Fractional Prediction
Reduces drug wastage when the quantity of one of a range of IP types needed can vary based on trial requirements. Calyx IRT predicts a fraction of each of the possible kits needed for an upcoming visit, thus reducing the overall amount sent to the site.

Automated Supply Strategy Management
Relieves the clinical supply manager’s burden of monitoring site stock by automatically adapting the amount of medication shipped to sites based on the number of patients in screening.

Medication Pooling
Reduces drug wastage and addresses drug availability concerns by sharing medication across different protocols in a single program. Calyx IRT controls the sharing of medication across protocols and facilitates just-in-time labeling, drawing on a wealth of experience supporting a range of different sponsor pooling methods and labeling plans.

Randomization Prediction
Reduces wastage by sending IMP to each site specific to upcoming treatment group assignments, when randomization codes are dedicated to the site

Supply Simulation
A trial supply simulation service available through Calyx’s in-house expert statistical design and trial supplies consultants, will estimate study supply requirements based on sophisticated simulation modeling methodology.

Reducing Drug Wastage

Calyx’s dedicated team of supply experts advise on which inventory management options are best suited for your trial – the more used, the more drug wastage is reduced:

20% reduction

In wastage with patent prediction compared to site buffer

20% reduction

In wastage when adding randomization prediction

40% reduction

When pooling IMP across 3 trials & a shared depot with prediction included

Flexible Inventory Management

Calyx experts recommend optimal inventory management settings based on protocol design, packaging plan, operational needs, and other concerns, such as high shipment costs, short shelf-life, limited supply, a large number of sites, unpredictable patient resupply needs, and the cost of drug.

Let Calyx amend the system’s configurable settings to get the most use out of any available IMP, while minimizing risks to the study, the drug, and the patient. For example, Calyx can support you when a new batch is delayed, getting the maximum use from a current batch, and managing supplies efficiently as you near the end of a trial.

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