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ShakulJugran
Product and Topic Expert
Product and Topic Expert

According to McKinsey, the median waste level for investigational medicinal product (IMP) kits was a...


Challenges during Planning


Patients and the clinical sites dispensing the patients’ medication are an essential element of each clinical trial. However, keeping track of different variables such as patient visits, dispensation schedules, and inventory fluctuations, makes clinical supply planning a complex balancing act.

This blog post will talk about commonly faced challenges during the planning and forecasting stages of a clinical trial, and how SAP Intelligent Clinical Supply Management solution can help.

To effectively plan a clinical trial, a trial sponsor must overcome these commonly faced challenges:

Demand Volatility


Demand volatility remains one of the key influencing factors in a clinical supply chain and has the potential to become a bottleneck during a clinical trial. A stock out (not having enough drug for the subjects) is a nightmare scenario for any clinical trial team, because of how important each subject is to the trial; not to mention putting the subject’s health at risk by interrupting their treatment plan. Therefore, trial sponsors and their Interactive Response Technology (IRT) vendors constantly battle demand uncertainty by supplying the clinical sites with significant buffer stock.

This often results in drug wastage and has a negative impact on both the financial and environmental sustainability of the clinical trial process. Unused drugs can represent a significant financial burden for the sponsor, as they must be disposed-off properly, and the cost of drug waste is passed on to patients, insurers, or taxpayers. Additionally, the disposal of drugs can have a negative impact on the environment, as some drugs can be toxic and can contaminate soil and water supplies.

According to McKinsey, the median waste level for investigational medicinal product (IMP) kits was a troubling 50 percent, primarily due to poor forecasting and planning and represents a significant opportunity to capture value. For instance, a pharmaceutical company spending $10 billion a year on R&D could reap annual savings of more than $100 million by improving its waste performance to best in class.

Ineffective Subject Enrollment Forecasting


Subject enrollment forecasting is one of the main obstacles that derail the success of clinical trials. Sites, patient populations, and sponsors continue to be troubled by difficulties in the enrollment of representative samples for clinical trials.

An important prerequisite for a successful clinical trial is the adequate enrollment of properly matched research subjects. Challenges in subject enrollment and matching results in extension of enrollment deadlines, delays the submission of the trial protocols for regulatory approvals and ultimately hinders the product launch. By some estimates, a product delay costs a company an average of $15 million dollars per drug, per d...

Lack of Transparency in Site Inventory


Traditional integrations between clinical supply and IRT systems range from simple to complex, depending on the sponsor’s requirements and system landscape. Most integrations focus on make (batch data) and deliver processes (drug shipments), but often lack sharing information about site inventory levels.

For a clinical supply system, site inventory data is critical in forecasting accurate demand, decreasing the cycle time, and lowering drug waste.

SAP and Tenthpin, together with an industry consortium led by Roche have recognized these challenges and developed an industry standard solution for clinical supplies.

SAP Intelligent Clinical Supply Management leverages the power of SAP S/4HANA software together with SAP Industry Cloud technology to address life sciences organizations’ unmet market need for a transparent, flexible, integrated, and efficient clinical trial supply management solution. This solution helps life sciences companies gain end-to-end visibility of clinical supplies, from planning to production to subject.

It consists of several modules covering the whole clinical supply chain: from Study Design, to Planning and Forecasting, Manufacturing and Packaging, and Distribution of the medication to the study sites.


Fig. 1: SAP Intelligent Clinical Supply Management - End to end clinical supplies planning, operations and integration into clinical supply ecosystem


 

How SAP Intelligent Clinical Supply Management Can Help


SAP Intelligent Clinical Supply Management offers advanced clinical demand planning and forecasting to the sponsors so that they can plan accurately and ensure that the right amount of medication is available at the necessary sites to execute the trial smoothly without interruption.

With its integrated demand planning process, SAP Intelligent Clinical Supply Management offers the following value drivers:

Manage Demand Volatility and Reduce Cycle Times through Better Forecasts


Plan Demand as Soon as You Have a Use Case


SAP Intelligent Clinical Supply Management offers the rough demand forecast app to plan project-wide demand for an investigational product on drug substance or bulk drug product level. You can start to plan demand as soon as a use case for a drug substance emerges and a plan or a program is drafted that includes one or more potential clinical studies. At this point it is known that some quantity of the drug substance needs to be reserved for conducting clinical studies and for other purposes, such as process development, toxicity studies, or stability studies.

The dedicated demand forecasting process begins with the planning stage by using the study’s master data and multiple planning scenarios to perform these calculations:

  • Enrollment – a forecast of the number of subjects to be enrolled in the study, broken down into weekly time buckets, beginning with the planned First Subject First Visit (FSFV) per site.

  • Visits – total number of visits by study subjects to a clinical site to receive treatments in accordance with the treatment schedule.

  • Demand – a forecast of demand quantities and buffer per kit type, based on the planned enrollment data, treatment schedule, and other study-specific data. The figures are broken down into weekly time buckets for accurate supply planning.


Support for Multiple ‘What-If’ Scenarios


Another feature is scenario level demand planning, which enables the clinical supply manager to simulate and compare multiple scenarios based on different parameters like treatment arms, treatment schedules, enrollment speed, and site events.

This results in a better demand plan based on the most optimal scenario, which then feeds the manufacturing plan for medication kit production. An accurate forecast reduces the time it takes for a kit to reach from the depot to the site and be eventually dispensed to the subject by pre-empting the need to order on an ad-hoc basis.


Fig.2: Multiple scenarios per study



Fig. 3: Planned Enrollment v/s Actual Enrollment


This is the detailed view of the Demand Forecast application categorized by enrollment, visits, and demand. Note that there are different tabs on the top and we are currently in Enrollment. What we see here is the graphical view of the key-figures Planned enrollment v/s Actual enrollment (pulled in from IRT or through file upload).

Adjust and Recalculate Forecast


The demand forecast app offers a quick and easy way to make changes to the values of the planned and actual key-figures. The user can overwrite values in the app and recalculate demand based on the latest inputs. This means that the forecast can be revised as soon as SAP Intelligent Clinical Supply Management receives new actual enrollment data from Interactive Response Technology (IRT) systems, thus making the demand forecast application very agile and powerful, both from the perspective of accuracy and simulation. The trial manager can run simulations multiple times before deciding to push this demand to the supply planning module in SAP S/4 HANA. They can also recalculate and update the supply plan mid-way through the trial with the latest demand forecast values.

Schedule Automatic Replanning


Another handy feature is the possibility to schedule demand recalculation based on pre-defined recalculation schedules. The system looks through the existing schedules, picks up the relevant scenarios and triggers the demand calculation automatically instead of waiting for a demand planner to do this manually.

Import Enrollment Data


If a sponsor’s IRT vendors are not integrated with SAP Intelligent Clinical Supply Management for enrollment data and the trial is extensive with many sites and subjects, the actual enrollment data can also be imported into its demand planning process using a pre-defined spreadsheet. This offers flexibility to the sponsors who don’t want to front-load the decision to integrate with IRT immediately or want to use third-party tools to forecast enrollment values instead of SAP Intelligent Clinical Supply Management.

Monitor Events as Soon as They Happen


SAP Intelligent Clinical Supply Management can also be configured to raise an alert when a planned key-figure diverges from the actual values beyond a pre-defined threshold. The threshold is completely customizable and acts as the trigger for the alert which can be seen here in the Demand Forecast app.

Increase Transparency and Collaboration


Integrate Easily with IRT


IRT systems are widely used in clinical trials and SAP Intelligent Clinical Supply Management offers standards based IRT integration to share information about subject enrollment, treatment visits, and changes in site inventory. It exchanges site level data with IRT vendors through multiple interfaces for shipment receipt confirmation, dispensing drug notifications and kit status change notifications.

A study can be marked as IRT relevant by setting the study setting attribute Use of Actuals to Use IRT Actuals (see the screenshot below).


Fig. 4: IRT Switch inside Study Settings


SAP Intelligent Clinical Supply Management supports the GS1 standard for clinical trials, meaning that its IRT APIs can be easily implemented by any IRT vendor who already has experience with GS1’s clinical trials message structure.

Therefore, the mapping effort on the sponsor side is cut down drastically while the integration effort at the vendor systems becomes quite straight forward and predictable, thereby helping the sponsors and their IRT vendors become mission ready faster than a fully customized solution. Using an industry standard for the APIs provides a big advantage to IRT vendors by allowing them to leverage one integration package for multiple other sponsors that use SAP Intelligent Clinical Supply Management.

Furthermore, an IRT vendor can also create, publish, and monetize their own integration content after registering with the SAP Partner Edge program.

The picture below enlists the already available integration APIs necessary to connect SAP Intelligent Clinical Supply Management system to an IRT system.


Fig. 5: IRT APIs in SAP Intelligent Clinical Supply Management



Reduce Risk of Overages


The ability to integrate actual enrollment data from an IRT system makes the forecast more accurate and allows the supply planning in SAP S/4 HANA to rapidly adapt to the latest demand figures. This reduces the risk of significant overages in a clinical trial and drastically cuts down drug wastage.

Planning and forecasting module at a glance


To reiterate, SAP Intelligent Clinical Supply Management helps Life Sciences companies plan and run clinical trials better by:

  • offering rough demand forecasts for early planning

  • planning with actual enrollment data

  • simulating and comparing demand planning for multiple scenarios

  • adapting planning key figures online or via spreadsheet upload

  • providing thresholds, alerts, and automatic replanning capabilities

  • standardizing and harmonizing integrations to IRT systems through GS1 standards


Engage with us


If you are interested in learning more about SAP Intelligent Clinical Supply Management, please consider following the new tag “SAP Intelligent Clinical Supply Management” and also read the previously published blog post in this series here.

We are happy to receive your feedback, questions or thoughts about SAP Intelligent Clinical Supply Management in a comment.
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