Protecting the Blind in Clinical Trial Shipments

The Challenge:

Striking a balance between effective study drug inventory control and efficient management of shipping costs is not always easy – especially when faced with the real-life complexities of clinical trials.

The most efficient ways to manage drug supply are:

  1. Automated “Predictive Resupply”  These algorithms are used for studies which have high enrollment, fewer days between visits, titration and or other complexities.
  2. “Static Resupply”  These algorithms are used when studies have lower enrollment, longer periods of time between visits and simple dosing assignments.  

However, there are varying degrees of effectiveness when it comes to optimizing shipment efficiencies. Not only are shipment costs at issue with all shipment algorithms, but another concern is also protecting the blind. This becomes especially critical to small studies or studies with limited amounts of drug.

It is generally agreed that a minimum resupply of two kits is good industry practice for avoiding “partial unblinding” that can occur from allowing one-kit replacement shipments. The issue may arise when the first subject is in for the randomization visit and receives their kit.  A shipment request is subsequently generated the same day for just one kit.  The site coordinator sees there are presently two kits in the inventory and suspects the next subject to be assigned the kit on the new shipment request will be on the same treatment arm as the first subject randomized.  

The Solution:

In the Veracity Logic CORE system, disallowing one-kit shipments regardless of whether predictive or static algorithms are used, is a configuration setting that can be determined by the client. When the setting is set to TRUE, the system will ensure that an additional treatment kit is randomly selected and added to any shipment that would otherwise include only one treatment kit.  


Do you have questions on how your IRT can help balance drug inventory and shipping costs while protecting randomization?  Please contact us for more information