Many facets of a clinical trial are unpredictable. Patient enrollment can vary widely within regions, countries and sites due to competitive enrollment and other variables such as discontinuation rate, titration probabilities, weight or body surface area (BSA) of patients that directly impacts dispensing. It is also not uncommon for protocol amendments to add new treatment arms, countries, or introduce changes to the depot/supply network. This unpredictability increases the complexity of clinical supply planning.
Think about all the key assumptions that are made at the onset of a clinical trial surrounding packaging design, sourcing/manufacturing and distribution. What if those assumptions shift? Do you know with a certain level of confidence how changes in those assumptions impact the clinical supply strategy? Would you be able to show your operations or financial counterparts the impact of those decisions in a timely and efficient manner?
This is why scenario planning is so valuable, and critical to help manage the variability in clinical trial supply decisions. Scenario planning puts the power back into your hands to explore possible outcomes based on a specific combination of events. Simply put, it enables you to find the best strategy while balancing risks and costs as well as gives you the ability to arm your internal stakeholders with impact assessment data based on plausible scenarios.
However, the value of scenario planning is not just comparing two detailed data sets. To be meaningful for the decision-maker, scenario planning must enable a high-level impact assessment of the key parameters of the trial, and even to the compound and network level.
By following the guide below, you will have the in-depth information needed to inform your clinical demand and supply planning (D&SP) strategy.
Now that we’ve focused on the five major areas to apply scenario planning, let’s shift the focus to the value of having this data in real time. Here are the top three benefits of leveraging scenario modeling to inform clinical supply decisions.
The technology now exists to enable real-time scenario planning. With the use of natural language processing (NLP), supply managers have the power to model as many scenarios as needed to enable better decision-making, all within a single working day.