How Exit Strategy Should Shape Clinical Trial Supply Planning

By Mike Sibley, CPA, manufacturing & supply chain specialist, James Moore & Co.

Clinical trial supply chains are often built with a strong focus on initiation and execution — getting studies launched, materials distributed, and patient enrollment supported. But in my experience working with complex regulated supply environments, the most overlooked phase is end-of-study execution, specifically how RTSM shutdown, depot reconciliation, and inventory disposition are coordinated when enrollment stops or a study ends early.

In practice, closeout issues typically surface only after RTSM shutdown has been disabled, when depot systems and site inventories still contain active GxP-controlled stock requiring reconciliation, return, or destruction workflows.

That exit point is where planning discipline is truly tested. It exposes whether RTSM configuration, depot-level inventory allocation logic at depot level, and packaging strategy were designed to support controlled inventory unwinding or whether manual reconciliation and write-offs are required.

Whether you’re dealing with planned study closeout, early termination, or a shift into the next phase, the financial and operational assumptions made at the beginning of the trial are suddenly exposed. And just like in manufacturing supply chains, those assumptions often don’t hold under real-world pressure. In clinical supply systems, these assumptions typically break down when actual system-driven demand modeling diverges from projected enrollment curves, forcing late-stage depot-level adjustments.

In clinical supply operations, this becomes visible when RTSM forecast inputs no longer align with site-level dispensing behavior, and inventory aging reports at storage nodes reveal overstocked or stranded kit lots during reconciliation cycles.

Planning For Both Success And Failure Scenarios

Mature clinical supply models simulate both full environment and early termination scenarios within RTSM forecasting logic, adjusting depot resupply triggers, safety stock thresholds, and packaging demand curves accordingly. The challenge is that most planning models assume linear progression toward success, not disruption.

Operationally, this creates excess depot inventory, nonrecoverable kit production, and delayed reconciliation cycles when demand curves collapse earlier than forecasted in RTSM systems. Overcommitting inventory based on optimistic enrollment curves leads to write-offs, excess stock, and unnecessary destruction costs. Under-estimating, on the other hand, can create urgent resupply needs that are expensive and operationally complex.

The organizations that manage this best build flexibility into their forecasting models — treating supply planning more like working capital management than static forecasting. This flexibility is often implemented through IRT-driven re-forecasting cycles that adjust depot allocation and resupply parameters as actual dispensing data begins to deviate from protocol-assumed enrollment curves.

Where Closeout Breaks Down Most Often

The most common breakdown at study closeout is timing misalignment between inventory, site demand, and documentation.

In many cases, product is still sitting in depots or at sites after patient enrollment has ended. That creates three problems:

• Excess clinical supply that cannot be redeployed
• Increased destruction or return logistics costs
• Delays in final reconciliation and financial closeout

This is similar to what we see in manufacturing environments when production winds down but inventory assumptions lag behind reality. The cost is not just excess supply — it’s operational drag on the entire system.

In clinical trial supply operations, this drag is often compounded by multi-country depot networks where return flows require separate regulatory and quality release checks before inventory can be closed out or destroyed.

How Overproduction And Waste Typically Originate

Overproduction rarely happens because of a single bad decision. It usually stems from compounding assumptions made early in the trial:

• Overly optimistic enrollment projections
• Failure to account for protocol amendments
• Static packaging configurations that don’t flex with demand
• Limited visibility into real-time site consumption

When those assumptions aren’t revisited, supply chains quietly accumulate excess inventory that only becomes visible at the end of the study.

In financial terms, this is a classic working capital inefficiency problem — capital is tied up in inventory that no longer has a defined demand path. In clinical supply systems, this is often masked during the trial because RTSM forecast updates may not fully reflect actual site-level kit utilization until multiple dispensing cycles have completed.

The Downstream Impact Of Early Decisions

Some of the most costly constraints show up long after initial planning decisions are made.

Packaging design, batch sizing, and depot strategy decisions made at study launch can significantly limit flexibility at closeout. For example, large batch production may improve unit economics early on, but it reduces the ability to right-size supply later in the study life cycle.

Similarly, rigid depot strategies can slow redistribution or recovery of unused inventory when trials shift or end early.

In both clinical and manufacturing supply chains, early structural decisions tend to have the longest financial tail.

For example, fixed kit configurations produced early in the trial often cannot be reallocated or repackaged efficiently at study wind-down due to labeling, country-specific regulatory requirements, or expiry date constraints. In practice, even when inventory is physically available at the depot, country-specific import and export return restrictions or quarantine requirements for temperature-excursion-exposed materials can prevent stock from being reallocated or destroyed, delaying final closeout reconciliation.

Why Exit Strategy Needs To Be Part Of The Supply Model From Day One

Exit strategy should not be a final phase consideration; it should be embedded directly into IRT configuration, depot allocation rules, and packaging assumptions at study start, not treated as a post-enrollment planning layer.

That means:

• Building termination scenarios into forecasting assumptions
• Designing packaging and batch strategies with flexibility in mind
• Modeling inventory exposure at both full enrollment and early stop points
• Treating closeout logistics as a planned operational process, not a reactive one

The organizations that do this well don’t eliminate risk, but they make it visible early enough to manage it intentionally.

This also includes building formal closeout workflows into supply plans, including defined triggers for RTSM shutdown, inventory reconciliation cycle timelines, and pre-agreed inventory destruction or return pathways.

Final Perspective

Clinical supply chains, like manufacturing supply chains, are increasingly defined by volatility rather than predictability. The difference between controlled execution and costly inefficiency often comes down to whether exit scenarios were considered at the start, not the end.

Planning for success is necessary. Planning for disruption is what protects value.

In clinical supply operations, that protection only becomes real when forecasting, depot strategy, and IRT execution are treated as a single connected system rather than separate functions.

In today’s environment, both matter equally.

About The Author:

Mike Sibley is a CPA and manufacturing & supply chain specialist at James Moore & Co., where he leads the Manufacturing Services team. With nearly 30 years of experience advising manufacturers, he helps companies turn operations, financial data, and systems into stronger cash flow, improved efficiency, and long-term business value. Mike works closely with clients on-site to connect financial insight with real-world operations, supporting strategic growth, M&A, and transition planning. He also serves in regional manufacturing and business leadership roles, including the Volusia Manufacturers Association and the Daytona Regional Chamber of Commerce, reflecting his deep commitment to the industry.