Christine Milligan and Paul Ingram, Catalent Pharma Solutions, review the evolution of clinical supply models from traditional supply-led to demand-led and hybrid models
Clinical trial bottle labelling
Clinical supply chain models have evolved in step with factors such as the increasingly global marketing ambitions of sponsor companies, regulations, technologies and trial designs. There has also been significant change in the past couple of decades from a more traditional model of ‘supply-led’ clinical fulfilment, to today’s new and emerging ‘demand-led’ supply approach. Types of products historically supplied were typically small-molecule drugs in bottles and blisters.
The past decade, however, has seen a move towards more biologics, potent and controlled substances, in a diverse array of primary packaging – vials, inhalers and syringes. There have also been a number of country-specific clinical trial guidelines introduced and a move towards mutual agreements that are necessitating changes in how clinical supplies are packaged and managed. Advances in technologies have resulted in the Interactive Response Technology (IRT) revolution, which allows for the automation of clinical supply and trial management, and flexibility in product labelling has been enhanced by the innovation of booklet/extended content labelling.
Adjusting supply plans and meeting ever-shortening timelines are critical within the clinical packaging and supply market. However, there are many challenges to ensure the right drug is handled appropriately and supplied to the right place, on time and on budget.
Adjusting supply plans and meeting ever-shortening timelines are critical within the clinical packaging and supply market
At a recent industry conference, a panel of experts predicted that biologically-derived therapeutics may account for 19 out of 20 products in development by 2020.1 Supply chains will need to respond with more extensive and even better cold chain management to handle these products, many of which will be both time- and temperature-sensitive. And since many of these products may have the potential to be first-in-class therapies, it will also be necessary to consider speed and efficiency again.
The ability to reduce supply-related delays and the downstream issues they can cause, such as poor patient retention due to a treatment being unavailable, can translate into clinical studies that get underway and conclude sooner, so technology and trial management need to evolve continuously.
The most important factor is the patient – i.e. patient recruitment, retention, compliance, safety, access and data management. Stakeholders within the clinical supply chain have recognised that the actual medication kit has an impact upon both the patient experience and patient compliance, and also has the potential to influence patient retention. Patient recruitment and retention are the biggest cost drivers of clinical trials, so this is vital for successful trial management.
Traditional push supply chain: The traditional clinical supply model, or supply-led packaging, suggests a static, linear centralised stock-based approach that uses discrete primary and secondary packaging runs to bulk-ship finished patient kits to clinical sites and depots based on estimated demand.
In this push supply chain model some/much of the stock in the chain may never be used
Primary and secondary packaging is undertaken at centralised GMP packaging facilities where stock is built up well in advance of actual need. Then, as determined by forecast estimates of whether a site and/or country will be a high, medium or low recruiter, initial bulk stock is sent to regional facilities, third-party depots, or directly to investigator sites where it is again held in anticipation of future need. In this push supply chain model some/much of the stock in the chain may never be used. Variations in patient recruitment rates and retention outside the demand forecast, used to guide the initial supply and subsequent re-supply of kits, can cause one investigator site to prematurely run out of stock while another may have too much. Often the issue is compounded by pre-determined resupply trigger levels.
The model requires long packaging runs, particularly around secondary packaging – which can take an average of six to eight weeks to complete – and is vulnerable to variability, for example in patient recruitment rates. This makes traditional supply challenging as it lacks flexibility to meet complex, changing demands, uses resources inefficiently, and can result in drug waste in excess of 200%.
For some applications, the traditional model can be useful, such as studies using large patient pools, and particularly where studies are expected to use fixed clinical sites and countries. There are still plenty of protocols that are country-specific and low in cost, including large studies that run in just one country, particularly in North America.
Just-in-Time Late-Stage Labelling: This model is a static stock-based approach that uses discrete primary and secondary packaging runs to produce partially-finished, base-labelled patient kits held within a central physical inventory to await final labelling. As in the traditional model, primary packaging is accomplished through the use of large-batch runs that account for high waste percentages. Secondary packaging comprises base- or partially-labelled kits, released in a central location where final, additional labelling is added upon receipt of a site ‘order’ at the drug distribution stage.
One of the most significant benefits of the ‘Just-In-Time’ concept is the reduced risk of stock-outs due to inventory misalignment
The process involves smaller, more frequent, ad hoc shipments but is advantageous because less stock is held at clinical sites, resulting in greatly improved responsiveness to variability in patient recruitment, as well as faster supply to any additional sites added to the trial. As a result, one of the most significant benefits of the ‘Just-In-Time’ concept is the reduced risk of stock-outs due to inventory misalignment. It is particularly efficient when the study involves materials requiring expiry update management.
There are disadvantages with this method too, however, especially the associated lead times and the very nature of the procedure, meaning that work may be performed in sub-optimal packaging environments or in a non-GMP manner. In addition, during times of high-volume demand, especially where several studies are being supplied more or less simultaneously, the potential for bottlenecks at the release stage is higher. Inventory problems may include the creation of a centralised inventory and greater risk of supply chain failure in the case of an unforeseen disruption and, as with the traditional model, inventory age and storage costs are often concerns too.
This model works best when multiple studies are running in parallel within the same geographic region, and using the same kit type. It is also more appropriate when the finished patient kits are simple in design. The Just-in-Time approach can be a more judicious choice over the traditional model when wide variability in the patient recruitment rate is expected and when the study drug(s) are expected or known to be in short supply or difficult to acquire.
Assembing blister cards into wallets for clinical trials
Direct-to-Patient high-efficiency supply: A more recent innovation is the ‘Direct-to-Patient’ model with its two major variations: Investigator site-to-Patient, and Depot-to-Patient. The regulations around implementing a Direct-to-Patient approach are challenging and vary between countries. A review paper, published in 2014 by the International Society for Pharmaceutical Engineering (ISPE), highlights the challenges and benefits, and what is clear is that patients are very interested in this approach, so suppliers should continue to drive adoption of this model where appropriate2.
Demand Led Supply (DLS): This more recent approach is a dynamic, continuous GMP approach to secondary packaging, labelling, release and distribution. Under this model, made-to-order patient kits are shipped to clinical sites from regional facilities based on actual patient demand or seed stock requests. Primary packaging takes place at a centralised, full-service packaging facility where a supply of unlabelled but uniquely coded ‘bright stock’ is placed into primary packaging. Then, based on forecasted demand, this bright stock is distributed to regional GMP facilities where it awaits further processing. Secondary packaging is completed and the finished patient kit is shipped to the investigator site where it is needed within a matter of days in response to on-demand orders received via IRT.
As the orders are based on demand, the stocks held at the investigator sites are generally equal to the site’s new and enrolled patients’ needs. This means orders are fulfilled based on what is actually needed by the sites, leading to more efficient use of stock, significantly reduced risk of stock-outs, and virtually eliminating the need to update expiry labelling at the investigator site.
Decoupling the location of primary and secondary packaging activities allows for better inventory management and lowers overall supply chain risk.
Variations in labelling requirements can be accommodated because the labelling is not being done until just before the material is to be sent to the site: the latest expiry date can be used and it is certain that the latest regulations are still met. However, it should be noted that management via global Standard Operating Procedures is crucial to ensure regional demands and protocols conform within a global supply infrastructure.
Variations in labelling requirements can be accommodated because the labelling is not being done until just before the material is to be sent to the site
The model easily adapts to mid-study changes and the incorporation of new countries or sites is not as problematic as it would be under a traditional approach, and even potentially under a Just-In-Time approach too. Booklet labels (needed under the older supply models) become unnecessary as labels can be applied in the language appropriate to sites and patients.
The DLS model should be considered when accelerating study start-up time is a critical requirement, as well as when minimal drug waste is essential to the overall feasibility of the clinical trial. For studies requiring a comparator drug that is difficult to source, very expensive, or in short supply, the DLS approach can be very beneficial to help maximise the efficient use of that scarce resource. It is an obvious option when complex or multi-layered clinical kits are unsuitable for distribution via a Just-In-Time approach. The model is particularly applicable when significant variations in patient recruitment rates are expected, or when the option to make mid-study changes in clinical sites or introductions of new countries is necessary.
The cost savings associated with a demand-led approach are affected by a number of factors which vary by study but can nonetheless be significant: ranging from the order of about 20% for drug product costs, to about 67% for clinical storage, and a full 100% cost reduction for booklet labels.
No single model is a perfect fit for all studies, but with a demand-led model now available, there are more options than ever before. When evaluating clinical supply strategies, partners that can support a variety of models, including Just-In-Time and DLS, are in the best position to be able to maximise the options and create customised approaches suited to the study sponsor’s needs. For example, in a multi-country study the combination of the static, supply-led, traditional model with the highly flexible demand-led model results in a hybrid method that enables customised solutions to be employed to meet challenging requirements, such as supplying countries that are known to present difficulties, supplying small quantities of clinical product when small seed stocks of inventory are held, optimising the supply model according to the country being served, and the need to remove clinical sites or countries without affecting the overall supply chain.
|Table 1: Each model is fundamentally different: applicability varies based on the nature of the study|
|Implementation effort||Low||Moderate to High||High|
|Supply chain predictability||Low||Moderate||High|
|Potential drug waste||20% or more||20% or more||Less than 20%|
|Responsiveness to study changes||Low||Moderate||High|
|Time-saving and cost-saving potential||Low||Moderate||High|
The industry will continue to embrace new systems that will enable it to support and advance new models. Systems integration will allow logistics to continue to become flexible and improve supply chain visibility, and through extensions to IRT and other technologies, there will be better forecasting and simulation tools to maximise efficiency. In the most advanced models, the supply chain now runs through the whole of the distribution process, including manufacture of the investigational medical product (IMP) and throughout the clinical trial’s phases, including packaging, distribution, dispensing and use of patient kits.
The models of tomorrow will definitely build upon the principles of what is currently being developed in demand-led, just-in-time and direct-to-patient options. These models are likely to rely heavily on real-time data to drive even greater efficiency and a truly personalised experience for the patient.
1. FierceBiotech Executive Summit: London, 12 October 2015
2. M. Eli, C. Hall, M. Oth, et al, Pharmaceutical Engineering, 2014, 34, 6