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How Optimizing Your Supply Chain Management Can Reduce Trial Cost, Effort and Risk

Today's Supply Chain
We can all recognize that there is a need to better manage the increasingly uncertain and complex drug supply chain, which is affected by the inclusion of more patients, at more sites and in more countries; country-specific regulations and approvals for temperature-controlled drugs, packaging, labeling and logistics; and more intricate protocols. In addition, the high cost of many comparator drugs necessitates accurate supply forecasting to appropriately manage study costs. However, it can be difficult to shift away from the traditional use of spreadsheets and other forecasting tools, despite their limitations, to predict supply both initially and to reforecast based on actual study data. It would also be very helpful to have the ongoing support of an experienced team, which is lacking for many of these tools.

How Optimizer Addresses the Common Challenges in the Supply Chain
Based on our experience with supply chain management, we identified common challenges that lead to significantly increased costs. These often do not exist in isolation, creating a snowball effect that can be particularly difficult to manage. Based on these, we developed Optimizer to help manage the clinical supply chain and answer these unmet needs.

1. Unoptimized logistics strategy
Higher shipping costs result from unoptimized supply lines, and greater shipping frequency occurs because the supply was not appropriately planned for each depot or site. Furthermore, the lack of visibility into enrollment means that high-, low- or non-enrolling sites cannot be identified, and the optimal supply of drug is unknown, potentially resulting in over or understocking.

Optimizer simulates all aspects of the supply chain, including depot-to-site timelines and depot-to-depot transfer times. You can develop unique timelines and cost structures for each supply line and find the minimum floor value needed at each site to avoid stocking out. In addition, you can identify non-enrolling sites to stop supplying unneeded drug.

2. Overproduction of clinical supplies
Often, tools are used that do not allow for flexible comparison of scenarios and adjustments, resulting in the use of poor or inaccurate data to form estimates. If you calculate production using the percentage of overage, the supply is likely to be overproduced or over-purchased because the calculation is based on consumption rather than true demand-based requirements.

With Optimizer, quantities are based on simulations of real-life situations, including screening, randomization and variable dispensing, rather than guesses or overages. You can review the true demand requirements rather than just consumption, and you have access to better data to make planning decisions around procurement and production. Optimizer allows you to simulate the outcome if only x amount of IP is manufactured. Optimizer can also help in the situations where the protocol has difficult or unpredictable demand or if there are long lead times for production or distribution.

3. Over- or under-enrollment
When enrollment is faster than expected, you risk running out of drug sooner than expected and subjects withdrawing because they miss a drug dispensing. This not only extends the study duration but also leads to more drug manufacturing than originally planned. Moreover, potentially expedited production increases production costs.

When enrollment is slower than expected, drug wastage is risked because of expiry, and production and logistics fees can be higher than expected because of the need for additional manufacturing campaigns.

Optimizer tracks the enrollment process and monitors the supply in real time. You can identify enrollment peaks and valleys. Your supply manager is empowered to make quick decisions about where and when to ship drug and how to modify the production plan, if needed.

Providing Value in Four Key Pillars

1. Drug costs
By accurately forecasting the needed drug, the result is less expired or wasted drug, less drug shortage, decreased production costs and decreased purchasing spend for clinical material, label procurement and packaging components.

2. Logistics costs
An optimized resupply strategy leads to fewer depot-to-depot transfers and depot-to-site shipments, resulting in decreased resource time, labor costs and logistics costs.

3. Subject costs
Over- or under-estimating the number of subjects (when and where) in the study can change the overall study drug and logistics costs and can risk stockouts at the sites. This can result in lost subjects because the drug is not where it needs to be.

4. Efficiency
The use of Optimizer reduces the time spent building, managing and updating forecasts. It also acts as a catalyst for building a unified process around forecast planning with cross-departmental collaboration.

By leveraging the efficiencies in these four key pillars, the first subject can be randomized faster, the trial can be conducted with greater confidence in the supply plan and database lock could potentially be reached earlier. When every day equals millions of dollars in potential retail sales, we all strive to reduce risk. Optimizer provides the transparency to allow each customer to better plan procurement and production and gain a clear understanding of the timelines for the needed drug.

Want to learn more about supply chain management and our suite of eClinical solutions? Contact me at Casey.Ferrier@bioclinica.com. I'd love to hear from you!

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