Just-in-Time (JIT) vs Just-in-Case: The Shift Toward Demand-Led Clinical Supply

Yet, the processes used to manufacture and supply study drugs to trial sites today are stuck in an earlier era, depriving sponsors of clinical supply models with the flexibility, speed, and efficiency their programs demand. Traditional supply chain management in clinical trials is often criticised for being too conservative, lacking agility, and resistant to adopt new ideas and technologies.

Several challenges have been historically prevalent in conventional clinical trial management:

• Discrepancies between API manufacture and downstream trial supply forecasting, leading to drug shortages later in the study
• Inefficient distribution, particularly in global studies where regional forecasting of patient recruitment can be difficult
• Overproduction of final patient kits and overstocking of sites and country depots
• Lack of patient-centricity, with large cumbersome kit designs and indecipherable booklet labels

Added to this are the more recent developments in the industry, which require increased oversight and management, and pose new challenges to clinical supply models:

• Globalisation of trials aim to expand into new locations in search of patient populations
• The rise in popularity and complexity of novel study designs, such as adaptive trials
• Small-scale or niche studies that recruit relatively few participants, focusing on orphan diseases or subpopulations of patients
• The emergence of advanced therapy medicinal products (ATMPs), such as cell and gene therapies, which are patient-specific and focus on genetic or cellular manipulation. These ATMPs can have limited starting materials, lengthy lead times, and high manufacturing cost.

Conventional Clinical Supply Chains

The conventional clinical trial supply chain looks to primary and secondary package the bulk drug, usually in quick succession at one central location. It commonly utilises booklet labels and a predetermined expiry date based on stability data available at the time.

The finished kits are stored at the central depot and shipped to local depots as necessary, well ahead of the first patient visit, and sometimes even prior to local regulatory approval. Clinical sites are usually seeded in time for their initiation visits, often before recruiting any patients. High levels of buffer stock are built into the trial supply management system/interactive response technology, which requests resupply when a predetermined threshold is reached. This relies on large stockpiles of drug at various locations, in case of a patient need.

When using the traditional model of clinical packaging, making changes to expiry dates is an arduous task. Each time that data from a stability study extends the bulk expiry, a labelling exercise to amend the printed expiry date is required on both the inner and outer containers. As some stock may already be at the clinics, this can entail relabelling at the site, returning the material to the packaging facility, or destroying the stock and resupplying the site.

JIT, a variant of the conventional model, also stockpiles material in secondary packaging, but adds the ability to make last-minute simple modifications, such as the name of the investigator, or additional country-specific requirements which do not require an additional release (e.g., qualified person release step in the EU).

However, as the stock has been directed to a specific protocol well ahead of shipping, and the kits created in a set configuration and labelled with the predetermined expiry date, the JIT approach to clinical trial supply only offers limited flexibility. Quite often this is described as late-stage customisation and is considered more of a “nice-to-have” modification, rather than a strategic deployment of material in line with known demand.

Demand-Led Supply in Industry

Demand-led supply (DLS) is a well-established concept outside of the clinical trial arena. In general industry terms, DLS refers to a supply chain management approach where the availability and production of goods or services are driven by customer demand. It focuses on aligning the supply chain with market trends, end-user requirements, and real-time demand signals.

The approach involves accurate demand forecasting, efficient inventory management, and agile manufacturing and distribution processes. By adopting demand-led supply strategies, companies can optimize their operations, reduce costs, minimize waste, and enhance customer satisfaction. The concept is applicable across a range of industrial sectors, including manufacturing, retail, logistics, and technology, as well as healthcare, where the goal is to ensure that supply meets demand in a timely and efficient manner.

Two examples of demand-led supply in other industries:

Example 1: Toyota Production System

A car is made up of more than 30,000 parts. These parts are made not only by Toyota but also at the plants of many of their business partners. All plants must work with complete synchronization to make the vehicles quickly and without waste. All adhere to the principles of JIT to achieve synchronized production:

1. Only make what is needed, when it is needed, and in the amount needed.
2. Don't allow goods and information to be held up during production.
3. Make them at the pace at which they're sold.

It would take many months to fulfil a customer's order if all the parts were made only after receiving it. To avoid this, the minimum number of parts needed are stocked in advance so that a car can be built as soon as the order is received. The preceding process has a store of finished products from which the next process can pick up the parts that it needs. The preceding process is also stocked in advance with the minimum number of parts needed to remake parts picked up by the next process before the next pickup, allowing it to immediately replenish whatever was picked up.

Figure 1: Just-in-Time Kanban process at Toyota

Source: The Toyota Production System (TPS), Kanban Zone, accessed April 7, 2025.

Example 2: Food Delivery Services

Companies such as Uber Eats and DoorDash operate on a demand-led supply chain model. They receive customer orders through their online platforms or mobile apps and then coordinate with restaurants and delivery partners to fulfil those orders. The supply chain is driven by customer demand, with restaurants preparing the food only when an order is received. This approach ensures that the food is fresh and delivered promptly, minimizing wastage and optimizing efficiency in the supply chain.

Demand-Led Supply: Designed for Today’s Clinical Trials

A demand-led clinical supply model is a dynamic, decentralized, continuous good manufacturing practices approach to secondary packaging, labeling, release, and distribution of made-to-order patient kits to clinical sites from regional distribution hubs based upon real-time demand from patients and sponsors. It decouples primary packaging from secondary packaging to drive greater speed, flexibility, and efficiency into the clinical supply chain. Further efficiency is seen in the novel technologies implemented, to allow aggregation of demand and speedier manufacture.

Figure 2: An example of the DLS model versus the conventional supply model.

Under the DLS model, the primary packaging of the bulk drug is performed in a central location, after which the product is shipped to multiple regional facilities based on the location of the clinical sites. These regional hubs store the drug as bright stock in their unlabelled primary packaging, or commercial container in the case of a comparator, until a supply order is raised by the IRT.

Due to the speedy turnaround available from order receipt to distribution, the trigger for initial shipment request to the site can be as late as patient screening.

The relevant language-specific label is printed on demand, containing the variable information relevant to the specific order, such as kit number and lot number, along with the latest (blinded) expiry date applicable to the bulk drug(s) at that time point.

The packaging of the specifically requested kit configuration occurs in a very short time period, usually anywhere between two days to 10 days, before being shipped to the clinic in time for the patient visit. The result is a kit that is tailored to the exact requirements of the patient, containing only the information that they need to know.

Key Components of Demand-Led Supply within Clinical Trials:

1. Demand Forecasting: Accurate prediction of demand based on study protocols, patient enrolment rates, and site requirements is crucial for efficient supply chain management.
2. Inventory Management: Implementing JIT inventory practices, reducing wastage, and ensuring proper storage conditions are essential to meet the demand effectively.
3. Globally Connected Agile Supply Chain: The availability of a global network of regional hubs is key to the success of the DLS model. Without a global view of the clinical trial supply chain, constraints must be built in at each level and stage, leading to overproduction, higher buffers, lack of capacity, and delayed trial start-up.
4. Study Set-Up: All packaging documents (e.g. label proofs, batch records, lot/expiry assignments) should be generated and approved in advance of the shipment requests being received at the regional hub. This enables a quick turnaround in manufacture and shipment. Flexibility in manufacturing, packaging, and distribution processes is necessary to respond promptly to changes in demand and study requirements.
5. Use of New Technology and Processes: Attempting to push a demand-led model through existing ageing systems and operational flows results in inefficient and slow processes. A robust set of operational procedures coupled with systems integrations allow quick turnaround of supply from receipt of order to patient dosing. Linkages between enterprise resource planning (ERP) systems, label print modules, and scan assembly reduce data inputs and potential for errors.

Benefits of Demand-Led Supply:

1. Improved Patient and Site Recruitment: By assuring the availability of investigational products at study sites, patient enrolment rates can be enhanced.
2. Better Patient Retention: Patient-centric, customised approaches to kit design and label proofing make it easier for patients to participate in the study.
3. Waste Reduction/Cost Optimization: Pooling of supply across studies and only supplying kits to clinical sites that recruit patients reduces drug wastage. Reducing the risk of oversupply leads to cost savings for sponsors throughout the supply chain (upstream manufacture of API, comparator procurement, etc.). Typical savings can range from 20 to 200 percent in product/comparator costs.
4. Enhanced Trial Efficiency: Streamlined study start-up activities and having the ability to quickly adapt to changes mid-study improves timelines, reduces risks and costs, and ultimately enables faster product approvals.
5. Regulatory Compliance: Packaging and shipment on demand facilitates compliance with changing regulatory requirements. One example is application of the latest available expiry dates to inner and outer containers in line with updates to Annex IV of the Clinical Trials Regulation regarding expiry dating.
6. Environmental Sustainability: Reduction in primary/secondary packaging component manufacture results in less waste materials, reduced storage requirements, and cost. Only shipping supplies that are required, within regions, means fewer, shorter and smaller shipments. The latter can be coupled with reusable shipper technologies to greatly reduce CO2 emissions.

Summary

Demand-led supply in global clinical trials offers significant advantages in terms of patient recruitment, cost optimization, study efficiency, and regulatory compliance when compared to more traditional approaches. Embracing this methodology has the potential to revolutionize the way clinical trials are conducted, benefiting patients, sponsors, and the healthcare industry as a whole.

Disclaimer: The examples of demand-led supply in other industries are intended to be used and must be used for informational purposes only. The views and opinions expressed in this article are those of the individual author and do not necessarily reflect the views or positions of any of the companies that are given as examples of demand-led supply. The author is not responsible for any errors or omissions, or for the results obtained from the use of this information. All information is provided ‘as is,’ with no guarantee of completeness, accuracy, timeliness or of the results obtained from the use of this information.