Wayne R. Kubick

Often combined with related topics like enterprise resource management and customer relationship management, supply chain automation involves a holistic look at the overall manufacturing and distribution process from cradle to grave, ensuring that all raw materials and components arrive just in time from suppliers for processing in manufacturing plants, that finished products are shipped just in time to customers to be sold, and sold items are quickly replaced without maintaining large inventories on hand at any point in the chain.

Supply chain automation involves the use of advanced planning, simulation, and management software, and has spurred adoption of new technologies for tracking, such as barcode tracking and, more recently, radio frequency identification (RFID).

We typically think of supply chain management within manufacturing and retailing, where companies such as Wal-Mart and Dell Computers are known as best practitioners—continuously improving their overall processes not only within their own companies but with their suppliers and customers as well. Wal-Mart, in particular, was one of the first large-scale adopters of RFID. And when you place an order for a new Dell computer, this triggers a complex series of events where individual components are requisitioned and immediately replaced in the Dell supply chain.

The logistics field offers other role models: We can monitor the progress of our package in real time by checking the Federal Express or UPS Web sites.

Assembly line precision

In many cases the supply chain model is already partly in place—for managing the flow of experimental drug supply to the investigative site, perhaps using an interactive voice response system that includes inventory management and just in time resupply capabilities. But drug supply is only one of many requirements for conducting a clinical study.

If we considered a clinical trial as a manufacturing process, the inputs would also include investigators, patients, specimens, regulatory documents, data collection tools, and data. Suppliers include sites, regulatory authorities, oversight committees, labs, drug manufacturing, CROs, and technology vendors. Our finished product output is a clinical trial database and report, which is assembled into yet another product—a regulatory submission.

Without too much exercise of the imagination, we should be able to see several parallels with the supply chain management model applied in other industries. Yet few of us expect to see a trial run with the same clockwork precision as a Dell assembly line.

Since most pharmaceutical manufacturers are already employing supply chain management systems to produce drug products, it's tempting to imagine an SAP for clinical research. But implementing such a complex software solution is an expensive proposition even for the relatively finite and predictable links in the typical manufacturing supply chain. And the business case in clinical trials is unlikely to be very compelling for technology and consulting companies.

My friends at CDISC would say such a vision is possible if we just used CDISC standards, and CDISC together with the Gartner Group have claimed some incredible benefits if standards are fully adopted. But standards alone aren't sufficient to achieve the same savings and efficiencies as in supply chain automation—you also need exceptional supplier relationships coupled with planning, processes, controls, and technologies.

The very name implies a single, integrated view of the entire process with all the participants cheerfully humming together like a well-oiled machine. Not exactly the image that first comes to mind on most trials.