The availability of investigational product often determines the success of a clinical trial's randomization and trial supply management (RTSM) solution. RTSM solutions are a key component of the clinical supply chain, the purpose of which is to ensure that the correct investigational product is at the right site at the right time for a subject. When the clinical supply chain fails to achieve this goal, the subjects as well as the entire study are affected.
Maintaining the right balance between having sufficient stock for all sites and subjects and avoiding overstocking and wastage of investigation product is challenged by the many complex processes across multiple organizations the characterize clinical trials today. Clinical teams work hard to avoid stock out situations, in particular, because of the significant financial and operational pain they create.
Challenges with Today's Clinical Trial Supply Chain
Protocol complexity, partially driven by the increasing pressure to achieve multiple outcomes from a single protocol to combat rising costs of clinical development, often requires a more sophisticated approach to protocol randomization and visit and dispensing schedules. With this complexity comes risk – risk that needs to be well understood and controlled to avoid supply chain failures. This is placing an even greater burden on clinical teams to find RTSM solutions to control the risk and continue to accurately randomize subjects per the protocol-defined study design, assign the appropriate investigational product consistent with the randomized treatment assignment, stock enough investigational product at a site to ensure noninterrupted treatment and maintain blinding until final analysis.
Despite these challenges and the cost associated with failure, we, as an industry, have been slow to move away from manual, spreadsheet-based methods of managing clinical supply. These methods are cumbersome to manage, take considerable amounts of time to try to forecast supply needs and make it virtually impossible to incorporate changes to those needs throughout the study. Take a common recruitment issue – if recruitment is slower than expected early in the study, you end up with expiry issues with the early batches, increasing wastage and cost; if recruitment picks up and demand increases, stock out situations are likely, compromising the subject’s treatment and the study outcomes.
How to Address These Challenges
It's time to rethink how we approach our supply chain – after all, your RTSM is only as good as the amount of inventory with which you fuel it. At Bioclinica, we believe that a modern and complete RTSM solution should do more, enabling optimization of your trial via data transfer and scenario modeling– we consider this a unified RTSM and trial supply optimization (TSO) solution.
Through modeling of complex scenarios in a validated tool, TSO creates an understanding of how the randomization and supply chain components of the study design translate into risk from a subject dispensation perspective. "What if" scenarios can be analyzed using assumptions and unknowns in the modeling. Critical questions can be addressed via the results:
- What is the extent of stock out risk? Where?
- Should manual shipments be generated? Should dispatch be expedited?
- What are the optimal IRT resupply parameters for making optimal use of available supplies?
- Will I hit an expiry challenge?
- Should I consider new packaging runs? When and in what quantities?
- When should new shipments be triggered to minimize probability of stock out?
During the study, actual RTSM data is transferred to the TSO application in real time, which can then be used to adjust the supply chain configuration mid-study to optimize for future risk mitigation based on past performance of the supply chain. Using actual data to challenge the assumptions and demand projections you made before the study significantly enhances the accuracy of your forecast in addition to your decisions based on that forecast.
A suboptimal supply chain costs money and compromises patient and study outcomes. If you are looking to move beyond your current solution, review the available solutions for one that can provide simulation analysis at the start and then truly integrate real-time data for re-forecasting purposes. However, also be aware that the pre-study supplies forecasting is only as valid as the accuracy of the assumptions used. So, if you are not confident in your abilities to provide the right assumptions, find an RTSM partner that can provide guidance and the experience needed to extract the correct assumptions for your study.
To learn more about this topic and, in particular, contemporary unified RTSM and TSO solutions, join me for a webinar titled "The Importance of Fueling Your Clinical Supply Chain" on Tuesday, October 2, 2018.