Drug Pooling: Power and Pitfalls

April 1, 2008

Applied Clinical Trials

Applied Clinical Trials, Applied Clinical Trials-04-01-2008, Volume 0, Issue 0

When done right, pooling clinical supplies can increase efficiency and contain costs, but limitations exist.

Drug pooling's potential to reduce waste and minimize supply outage is of keen interest to biopharmaceutical companies. Yet confusion persists about what pooling can and cannot do—and about how pooling can and cannot be done.1

Pooling, which is employed in conjunction with IVRS/IWRS, is possible when more than one protocol operating at the same depot and/or clinical site uses the same drug. By treating identical supplies as commutable among pooled protocols, pooling allows supply and safety stock to be shared. With pooling, dispensing units are interchangeable (indistinguishable in content, count, and container/closure system) and while in their pooled state, they are protocol independent, with a single, shared IVRS definition.

There are three basic levels of pooling that might be of interest to clinical trial designers and managers. First, a fairly obvious one: pooling a set of packaged kits or kit components that are not yet labeled. We might call this "Pooling Prior to Labeling." This method is uncontroversial and is out of the scope of this article.

A second method is to deliver packaged and labeled goods to depots without a protocol number on the label. This is useful for a variety of different simultaneous clinical trials in the same program (or at least using the same kit types). We might call this method "Pooling at Depots."

Pooling at Depots is somewhat more controversial because it requires that the protocol number be written or affixed to the label of all kits prior to shipping, but after being requested by clinical sites (usually via IVRS) for particular trials. Both the process around this activity and the regulations in various countries—especially in Europe—are rather unclear. However, Pooling at Depots represents a significant clinical supply advantage over Pooling Prior to Labeling, and is thus worth consideration.

The third method of pooling encompasses Pooling at Depots but also makes the assumption that some clinical sites may be running multiple "pooled" protocols at more or less the same time. In this type of pooling, kits may actually be shipped from the depot without a single protocol number, although sometimes they do show a set of protocols, or a program code. In any case, the kits remain protocol independent, even at the clinical site, until they are dispensed. At dispensing time, the IVRS marries the protocol to the kit number and any required label modifications may be made at the site. We might call this method "Pooling at Sites."

Pooling at Sites, done when there is more than one protocol operating at the same investigative site, is actually far more commonly applicable than may be apparent at first blush. Although in earlier phase studies it is uncommon to have multiple studies sharing the same formulation, in later Phase III and IV studies it is not uncommon at all. However, many clinical supply managers interpret various European or other regulations as prohibiting the shipment of drug to sites without a protocol number on the label. Others note that exceptions are made in cases where centralized randomization systems are used. Others still note that regardless of the letter of the law, certain regulatory agencies will never allow pooling at sites. A common reaction to the notion of pooling at sites is "good luck."

Nevertheless, Pooling at Sites does indeed occur in the biopharmaceutical world, and has indeed been shown to save significant supply when used. We will assume that the reader accepts on some level the regulatory viability of Pooling at Sites, even if the concept is neither universally endorsed nor applicable to all geographies. The remainder of this article will address specific pitfalls and requirements of Pooling at Sites both in terms of electronic records and of actual labeling.

Pooling for Europe

As noted above, in Pooling at Sites, the IVRS does not marry any particular kit to a protocol or subject ID until the kit is disbursed. This allows the IVRS/IWRS to tally stock against the future needs of all the protocols at a particular location: All projected shortfalls can be covered with a single, nonprotocol-specific shipment. That shipment will equal the location's projected need for a specified period (minus at location and en route unexpired/ing stock). Each patient in a pooled protocol may be dispensed the appropriate kit type from the common supply.

Traditionally, clinical supply managers package lot for a particular protocol. In a pooling scenario, they may naturally assume that they can and should package or electronically earmark the drug for the set of protocols for which it is to be used. However, marking drug for use electronically or on the label for a specific protocol—or even for a subset or specific group of protocols—can compromise pooling. Only if kits are protocol independent until dispensed can an IVRS resupply algorithm consider the needs of all protocols using a particular kit at a single location as a whole.

Murphy's ABC protocols

Consider, as an illustration, the predicament of Murphy, a clinical supply specialist. His protocols, A, B, and C all use a dispensing unit type called "10mg Samplovir." In this example, we will focus on only one physical location, "Fenway," where all three protocols are being conducted.

Doing what he's always done, Murphy packages "Lot 1" of 10mg Samplovir, labels, electronically marks it in the database for protocols A, B, and C, and distributes it to his supply chain.

In marking for specific protocols, Murphy has broken pooling's fundamental principle that dispensing units must be protocol independent. But the protocols for which he has labeled happen to be the only protocols that use 10mg Samplovir, so all drug need calculations—for plotted subject consumption, safety stock, floor/ceiling—are successfully totaled.

Now, however, Murphy packages a "Lot 2" of 10mg Samplovir. He feels that protocol C is just about wrapped up and does not want to dedicate any new supply to it. So this time he only marks it for protocols A and B. Murphy distributes Lot 2, and some ends up at Fenway alongside Lot 1.

Murphy's supply at Fenway is now comprised of 17 total dispensing units of 10mg Samplovir: two units of 10mg Samplovir from Lot 1 and 15 units of 10mg Samplovir from Lot 2. Lot 1 is usable for protocols A, B, and C, but Lot 2 is only usable for protocols A and B. In this example, he still has subjects enrolled and active at this location for all three protocols.

That night, Murphy's resupply algorithm now begins counting his supply at Fenway. When it counts drugs at location, it can no longer count all 17 units of 10mg Samplovir together in a single bucket. At a minimum, it needs to count once for protocols A, B, and C (two units) and again for protocols A and B together (15 units). There is no way for the algorithm to represent the stock with a single number for the location. At the moment, however, this is little more than an inconvenience.

The following week, Murphy needs to supply drugs for projected subject need. Protocols A, B, and C have two subjects each scheduled to arrive in the next week; each subject is scheduled to receive one 10mg Samplovir. Ordinarily, a pooled supply algorithm would compare this summed need (six units) against stock at the site (17 units), but since Murphy broke the absolute nature of the pool, the algorithm must count the needs against the stock at site separately.

If the algorithm does this for each protocol separately, it may predict that the needs of protocols A and B for two each will be easily supplied by their total available stock of 17 and 17, respectively, and that protocol C's need for two will also be covered by the remaining Lot 1 supply of two. But the algorithm's prediction may not necessarily be correct.

Consider the drug consumption for randomized subjects scheduled to have dispensing visits at Fenway during the following week. If both subjects from protocol C arrive earlier than subjects from protocols A and B, one should see something like what appears in Table 1.

Scheduled Dispensing Visits at Fenway

The order of the last four subjects, in this case, does not really matter; it matters only that the subjects from protocols A and B all arrive after the subjects from protocol C. But what happens if a subject from protocols A or B arrives prior to a subject from protocol C? The dispensing algorithm should be dispensing the oldest usable medication first so Lot 1 will be consumed by subjects in protocols A and/or B (see Table 2).

Fenway Encounters Dispensing Problems

Algorithm vs. IVRS

The more subjects are intermingled at a location and the more stock is labeled for different subsets of protocols, the worse the problem gets. Even in this example, if subjects from A or B arrive in the first two dispensing positions, both subjects from protocol C will encounter stock-outs and be lost. Losing subjects in this manner is clearly unacceptable. Why can't an algorithm figure out on the fly which lots are for which sets of protocols and do the math accordingly?

While it may seem intuitive that the algorithm should be able to do modified calculations to rescue Murphy, or at least to set aside the Lot 1 stock for the protocol C subjects, in fact the algorithm is ill suited to the task. To preserve certain drugs for the projected need of specific incoming subjects, the dispensing algorithm would need to be linked to the predictive resupply algorithm, and the two functions are mismatched.

Dispensing in IVRS studies is an uncomplicated operation: The algorithm looks at the dispensing unit type(s) required by the subject, chooses the earliest expiring usable unit(s) from stock at the site, and dispenses. This simple process is carried out in real time many times a day to provide drugs to subjects. A resupply algorithm, by contrast, is a very complex process that usually runs once a day and considers numerous factors and projections in its decision making.

Conclusion

All in all, drug pooling has the potential to increase supply efficiency in an unexpectedly wide range of scenarios, although its limits may be unexpected. As the inherent flexibilities and inflexibilities of the technique—and the breadth of situations in which it can help contain costs—become more commonly understood, the use of drug pooling will undoubtedly continue to expand.

Dave Riege is associate research fellow in supply chain management at Pfizer. Ed Tourtellotte* is the founder and chief executive officer of Tourtellotte Solutions, 321 Commonwealth Road, Suite 303, Wayland, MA 01778, email: etourtel@tci9.com

*To whom all correspondence should be addressed.

References

1. L. George, "Investigational Medicinal Products—Optimizing the Supply Chain," Applied Clinical Trials, April 2005, 42–48.

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