Clinical Trial Supply Challenges In Alzheimer's Trials
A Conversation Between Rick van der Vegte, Senior Managing Director, Healthcare Business Transformation, at FTI Consulting, Abbie Noble, Director, Healthcare Business Transformation, at FTI Consulting and Elizabeth Urbanek, Executive Editor, Clinical Supply Leader
Alzheimer’s trials can make clinical supply planning harder than it looks on paper. Enrollment can be difficult to predict, studies can run for years, and keeping both patients and caregivers engaged can affect the assumptions behind the supply plan. At the same time, newer Alzheimer’s therapies bring different requirements for storage, transportation, packaging and administration.
That creates a supply model that has to keep changing as the trial changes. A shift in enrollment can affect inventory and manufacturing. A change in a patient’s treatment schedule can affect site supply or, in the case of PET imaging, the timing of a short-half-life radioligand. Expanding into new countries can introduce another set of questions around import requirements, infrastructure and logistics.
Elizabeth Urbanek, Executive Editor of Clinical Supply Leader, spoke with Rick van der Vegte, Senior Managing Director, Healthcare Business Transformation, at FTI Consulting, and Abbie Noble, Director, Healthcare Business Transformation, at FTI Consulting, about what these challenges mean for clinical supply teams in practice. They discuss forecasting, real-time supply planning, global distribution, increasingly complex therapies and how sponsors can build supply models that are easier to adjust as a trial evolves.
1. Alzheimer’s trials can require large patient populations, long study durations and highly specific eligibility criteria. How do those factors affect the way clinical supply teams forecast investigational product demand?
You’ve called out a few of the key challenges that make it difficult to accurately forecast Alzheimer’s trial supply and demand. Many Alzheimer’s trials also fail to meet their enrollment targets and retain participants throughout the study, making inputs to the clinical supply forecast even more volatile. For example, according to the World Alzheimer Report 2026, over 70% of screened participants are ineligible. An additional complexity of Alzheimer’s trials is that they require not only the patient but also their caregiver to enroll and stay engaged throughout the study. Caregiver availability becomes a limiting factor for enrollment, and this significant burden adds to high dropout rates and needs to be accounted for. These less predictable inputs make risk-based forecasting and real-time data that much more valuable for managing the clinical supply.
Another complicating factor is that Alzheimer’s trials typically span longer periods of time compared to other trials. This means that the demand is not only more volatile, but also spread out over a longer period of time.
A larger trial population and spreading supply forecasting needs over a longer period of time prompts clinical supply teams to use even more data-driven and statistical forecasting methods. There is more data available, which could be overwhelming and difficult to manage, but the data also makes statistical models more accurate. We believe that clinical supply teams should increasingly rely on these statistical forecasting methods over more manual forecasting, like in rare disease. However, statistical models are only as good as the quality of their input data. At the beginning of a trial, when data is limited, the reliability of statistical models must be confirmed with expertise and judgement before proceeding.
2. Recruitment can be one of the biggest sources of uncertainty in a clinical trial. How should supply teams adjust inventory, manufacturing and distribution plans when enrollment is slower or more variable than expected?
Due to the unpredictable and volatile nature of supply forecasting inputs, clinical trial planning needs to be managed and adjusted much closer to the start of the trial and in real time. Interactive response technology (IRT), also known as clinical trial randomization and trial supply management (RTSM), allows you to adapt supply based on real-time enrollment. The key here is to leverage historical enrollment, screening failure, dropout and site activation data and trends to inform frequent recalibrations of the supply forecast. Adjusting to these recruitment challenges in near real time with predefined manufacturing, safety stock, inventory and site supply adjustments helps to translate uncertainties into more realistic plans.
It is simply not sufficient anymore to perform a monthly, or maybe biweekly, planning cycle, make adjustments to the plan and move on. It has almost become inevitable that teams apply real-time forecasting approaches to ‘recalculate’ plans as the trial population evolves.
3. Alzheimer’s trials are increasingly global and may involve sites with very different infrastructure, storage capabilities and import requirements. What supply considerations need to be addressed before those sites are activated?
Global expansion of sites requires local knowledge and expertise of not only the import authorization process, customs, and any qualified person release requirements, but also who the most reliable partners such as couriers are in those countries and the ports of entry that are most efficient for customs clearance. Network design to comply with all of these supply chain and logistics considerations needs to be addressed before site activation, in addition to facilitate thorough onboarding and training of sites, minimize risk and ensure products can be delivered to all sites and administered on time and under strict cold chain, storage, shelf life and stability window requirements. In addition to logistics, the diagnostic infrastructure needed for Alzheimer’s trials varies significantly by region, for example, PET imaging capacity versus reliance on cerebrospinal fluid testing. This variability impacts which sites are viable for activation even before supply chain planning.
Additionally, the collection of biomarker data throughout the trial is also more complicated than with many other trials. Alzheimer’s trials require the use of radioactive materials with a very short half-life to complete brain scans and measure disease progression over time. A manufacturer or trial sponsor who takes responsibility for managing this demand (and setting the cadence at which scans need to happen) will also need to determine how to source these materials.
Managing all of these aspects in parallel across geographies and large patient populations requires increased education and training of clinical trial sites. With multiple clinical trials operating similarly across the globe, it is critical that strict trial protocols are followed in order to collect the right information during the trial.
4. As Alzheimer’s therapies become more complex, what changes in the way investigational products need to be packaged, stored, transported and tracked from manufacturing through the clinical site?
Alzheimer’s therapies are transitioning from the existing oral small-molecule standard of care to newer approved drugs such as monoclonal antibody biologics and investigational therapies like siRNA therapeutics. However, these increasingly complex therapeutics have more stringent shelf life and cold chain temperature-control requirements. Everything from logistics lanes to cold chain shippers, packaging configuration, temperature and GPS monitoring devices and more will need to be tested and qualified to meet the required temperature, time, tracking and traceability requirements. Thorough preparation and risk mitigation through logistics lane analyses, mock shipments and exception planning will be critical for identifying risks and mitigations before patient shipments and supply are impacted. As Alzheimer’s drugs also move toward at-home administration, packaging, labeling and storage will need to be simple and usable for patients and their caregivers.
5. Where do you see technology making the biggest practical difference in clinical trial supply today, particularly when it comes to visibility into inventory, shipments, temperature conditions and patient or site demand?
Clinical trial randomization and trial supply management (RTSM) systems for inventory and assignment management can add an additional layer of oversight through a control tower and offer increased shipment visibility. A control tower allows you to manage and coordinate across your full network through one centralized data hub and proactively identify risks, respond and mitigate them. However, a control tower requires a strong foundation of manufacturing, warehouse and shipment tracking data feeding into it to produce the aggregate insights to act upon. Without an integrated network of timely and accurate data or clearly defined decision flows and predictive modeling, a control tower will be severely limited.
Latency of information is crucial to making these technology solutions successful. Since information is provided by so many sources, a good technology environment is required to capture this. More and more, technology providers are providing agents that can process data in any format and ingest that into a standardized environment for further processing. Looking at an example specific to Alzheimer’s, a patient needs to reschedule their PET scan appointment unexpectedly. This means the short-half-life radioligand order and the site’s dosing calendar both need to shift in lockstep. This information typically is shared verbally, in an email or any other non-standardized format. It is critical that the information is captured as quickly as possible to allow for schedule updates in the centralized system. This will drastically impact overall trial performance and cost if done properly.
6. Looking ahead, what should sponsors be doing differently in the planning stages of Alzheimer’s trials to build a clinical supply model that can adapt when enrollment, protocol requirements or treatment demand change?
The first step is to proactively plan for potential modifications to the trial design, such as sample size, and specify those in the protocol and statistical analysis plan before the trial begins in order to establish an adaptive trial design that allows clinical supply models to change. Second, forecasting supply models using various assumptions and adjusting the inventory, safety stock and more as those assumptions are validated or change helps to provide initial visibility into the scenarios at play and allow you to more readily adjust when needed.
Scenarios for Alzheimer’s trials at the patient level would likely include lower starting doses or pauses in dosing. Decentralized elements, such as home nursing visits and direct-to-patient shipping, can be built into models from the start to ease the burden on patients and caregivers and reflect the need for a fundamentally different depot and packaging strategies compared to site-based studies. Lastly, making sure your teams are prepared to act on those triggers with the processes, procedures, decision-making rights and appropriate escalations in place will turn this from a scenario planning exercise into operational reality. This requires low-latency information processing and utilizing technology to operate even quicker. Ultimately, many of these supply chain challenges come from protecting a patient population that is often elderly, cognitively impaired and dependent on a caregiver for treatment. Keeping the patient at the center of the plan is what separates a good clinical supply model across any disease from a great one.
About The Experts:
Rick van der Vegte serves as the leader for the Life Sciences Core Operations practice and is known for his ability to solve highly complex operational challenges across the people, process and technology domains, while bringing deep international experience.
Mr. van der Vegte has been an active member of C-level advisory teams during major events, including new product launches, restructuring and bankruptcy, governmental regulatory intervention and mergers, integrations and carve-outs. He has worked in many CMC and GxP environments to create nimble and cost-focused operations. Mr. van der Vegte has worked in many of the operational nuances that make life sciences operations unique, such as GxP compliance, cold chain management, vaccine manufacturing operations, solid dose manufacturing, personalized medicine including CAR-Tand gene therapy, CDMO management, generics profitability management and beyond.
Abbie Noble has experience supporting life sciences organizations through strategic transformations, commercial launch initiatives, and operational improvements. She focuses on developing practical, sustainable solutions that enable organizations to improve operational effectiveness, enhance patient outcomes, and drive measurable business impact across core operational areas, including supply chain, logistics, pharmacovigilance, patient engagement, commercial functions, and more.
Abbie has supported across a variety of cross-functional transformation engagements, with significant experience spanning the end-to-end cell and gene therapy (CGT) lifecycle. Her commercialization experience includes process design and improvement, functional playbook development, mock operations exercises, patient support program assessments, and treatment center experience improvement initiatives. She has also supported manufacturers, including CDMOs, vaccine manufacturers, and generics organizations, across a variety of supply chain and operational transformation initiatives.