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, and 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 helping 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.
Key facets of scenario planning
- Packaging design strategy: what is the optimal packaging design? Should you use single-unit or multiple-unit packs in case of repetitive or weight-based or response-based dosing titrations? Package design has a direct impact on shipping costs, expiry management as well as storage on the site.
- Sourcing/manufacturing strategy: what alternative manufacturing plans do you have in case of alternate enrollment and distribution strategies? Are you at risk of waste due to expiry from slow enrollment? Another consideration is in-sourcing versus outsourcing, where each approach has variability in lead times or flexibility in schedule changes, for example.
- Distribution strategy: What is the optimal distribution network? Do I need a global depot or can I work with regional depots only? In which countries do I need local depots due to import complexity or local comparators? Other key questions to consider include the impact of changes in shipping frequency? Or should I apply different strategies to expensive drug products or scarce drug products, for example? What happens if I simplify my depot network after enrollment is completed and demand is more predictable?
- Crisis management: this should not be overlooked. However unlikely the scenario, there need to be contingency plans in place. Using scenario modeling is a useful tool to prepare for the worst. Examples can include losing a manufacturing batch due to quality. What is the impact on the current supply strategy? Should the depot/site supply strategy be adjusted to offset the limited supplies until a new batch arrives? What are the risks?
- Protocol changes or uncertainties: what happens when your clinical study team decides to add six more countries to catch up on enrollment delays? What is the impact on supply and cost?
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.
Benefits of real-time scenario planning
- Balance risk and cost: at the onset of this guide, we touched upon the purpose of scenario planning to choose the best strategy for the organization based on the information available to you today. Not all risks or costs are visible unless you can model various scenarios that each manipulate different variables. The ability to model many scenarios with speed and accuracy can give decision-makers the tools to move down the best path.
- Increase collaboration between supply and operations: clinical supply and operations departments in many cases have competing priorities. Scenario modeling can help drive dialogue between the two groups and ultimately end up with a better result. Ideally, one to one-and-a-half years prior to the study start, there is a conversation discussing the protocol. Having that information, the supply manager can suggest changes (such as in the dispensing plan) based on the key facets discussed within this guide that can reduce cost or increase efficiencies in the study.
- Meaningful data for better trial decisions: scenario planning is not as valuable if it takes weeks to build models. Changes to trials occur rapidly, and the ability to shorten that cycle to one working day (versus two-plus weeks) allows for faster, meaningful data to review with stakeholders to ultimately make better decision-makers.
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.
Sabrina Fei, 4G Clinical Senior Marketing Manager, has 6 years of experience in B2B healthcare marketing. Prior to joining the 4G team, Sabrina worked at a life sciences event organization, where she led a team of marketers to generate and implement impactful, multifaceted marketing strategies.