Simulations can help the pharmaceutical industry implement serialization systems that comply with the US Drug Supply Chain Security Act.
On November 27, 2013, US President Obama signed the Drug Quality Security Act (DQSA) law into effect. Article II of that law, named the Drug Supply Chain Security Act (DSCSA), requires members of the US drug supply chain to make a series of changes over a 10-year period in order to better secure the US supply chain from counterfeit, diverted, stolen, or mishandled drugs. The changes also seek to address the drug recall process.

This new federal law preempted all related state laws and was significant in that it created one federal law that took under consideration aspects of four different concerns:

• California’s pending Pedigree law (requiring serialization and traceability by 2015)
• Certain established business practices of the supply chain, such as inference (e.g., inferring what is in a sealed case based on the manufacturer’s information)
• FDA’s desire to remove bad product and bad actors from the supply chain
• Patient-safety advocates’ desire to protect the patient.

To allow supply-chain partners to budget and prepare for serialization and traceability, the law also sought to spread implementation over a 10-year period. No one party got all of what they wanted, but in the end, everyone got something that could build momentum toward the ultimate goal of removing illegitimate medications and criminals from the supply chain. As with any undertaking of this magnitude, many questions and issues arose and will continue to arise as actual phased implementations take place.

Most phase dates in the DSCSA are based on a certain period of time measured from when the law was enacted. An exception was the initial implementation phase of sharing transaction statements (TS), transaction information (TI), and transaction history (TH) at the lot/batch level, which was set for implementation on Jan. 1, 2015. Because of delays in Congress, by the time the law was officially enacted on Nov. 27, 2013, the supply-chain participants had little time to think as they switched from preparing for California’s requirements to the first implementation phase of DSCSA.

Manufacturers and wholesalers scrambled to cobble together a solution using the systems they had already in place to meet the TS, TI, and TH sharing requirements. The result was that their systems worked with a lot of manual effort and a certain amount of errors—errors that also needed a lot of manual effort to address. It is well recognized by these manufacturers and wholesalers that these manual efforts are unscalable and unsustainable over time as the more demanding requirements of individual item serialization (in 2017) and traceability (in 2023) come into effect. Challenges for implementing serialization are even more magnified considering the growing number of global laws and regulations for serialization, authentication, and traceability.

This challenge doesn’t mean that the task at hand is impossible. We are, after all, talking about a country that put a man on the moon and an industry that daily discovers and invents new ways of extending life in terms of quality and longevity. It is doable, and this industry is up to the task.

So what now? Continue to implement as we go? Some hope not. The law provides enough time for the industry to move from the somewhat rushed implementations of 2015 to a well thought-out, globally integrated system for 2023. The problem is that there are still questions to be addressed to achieve new efficiencies that can help fund serialization and provide real benefits, such as more effective and efficient recalls.

The Big Issues

Today, industry trading partners are actively planning and executing traditional, physical pilots, which involve sending trial packages through the system, to ensure that their systems for handling serialization information function in production. To prepare for mass serialization and traceability, however, pilot programs must be conducted on a broader, more industry-wide scale. Issues such as aggregation, inference, scalability, and the core issues related to supply-chain security and patient safety cannot be solved through traditional pilots.

So, how can these broader issues be addressed? In parallel with the necessary traditional pilots, supply-chain members could undertake a series of “virtual pilots” that would touch on the more difficult, core issues that have yet to be completely resolved. Loosely defined, a virtual pilot is a series of scenarios executed in a simulated environment where alternative courses of action can be experienced, measured, and compared. This concept is easy to understand in terms of extracting TS, TI, TH, or traceability data from one system and devising a method of comparison with other systems. Issues, such as aggregation, however, must consider behavior (resulting in possible changes to standard operating procedures) and measure the seemingly unmeasurable. For example, will this course of action enhance the security of the supply chain and enhance patient safety? To accomplish these tasks, the industry needs to consider the behaviors of its systems and staff; new business rules, laws, and regulations; and the effects of these factors throughout the global supply chain. This complex task requires the cooperation of all participants in the supply chain and an efficient means to track alternative scenarios and their impact on day-to-day events as well as on each other.

Virtual pilots

An early example of using simulation software and techniques is found in the international commercial banking industry. In 1992, a commercial bank was developing an international funds transfer system to move and reconcile cash between international banks. The bank had over 50 designers/developers, fell six months behind schedule, and was $15MM over budget. The bank followed the latest systems and process technique of the time, creating hundreds of data-flow diagrams, data-model diagrams, and structure charts, but the bank wasn’t confident that implementation of the transfer system would actually work if put into practice between the various banks around the world.

The bank finally decided to use simulation software, which was typically used by manufacturing companies to study and measure internal processes and simulate hundreds of diagrams. The software revealed that the funds-transfer system didn’t work. One-hundred six major functional flaws were found in the design, and the bank was able to make corrections and implement the entire system within weeks.

Like the bank pilot program, the pharmaceutical industry could also conduct a simulation for the proposed changes to the global supply chain, adding to the simulation the various worldwide requirements, business processes (local and global), and predicted solutions for the functional flaws that could potentially arise in implementation design. Then, having witnessed how scale and alternative methods impact the safe flow of medication (positively and negatively), key issues such as aggregation, inference, global commerce, local needs, scalability, necessary standards, guidelines, and supply-chain vulnerabilities could be resolved prior to mass implementation—resulting in measurable changes that would positively affect patient safety.

Experiencing a virtual pilot

Consider how supply chain industry players might tackle a “big issue” using a virtual pilot. Take the case of determining the impact of “lot/batch aggregation” (i.e., associating each serialized item to only the lot/batch) versus “packaging aggregation” (i.e., associating each serialized item to each case, pallet, or tote they’ve been in) on identifying a counterfeit. It is assumed that packaging aggregation allows for full supply-chain traceability of each item, but lot/batch aggregation alone could possibly miss a transaction where the outer layer (case) remains intact through a number of trading partner movements. A virtual pilot can be used to compare the two types of aggregation.

Using simulation software, rules of behavior could be expressed for a series of simulated trading partners, and a counterfeiter could be added to the simulation. Then, two versions of the simulation — one where serialized items are aggregated at the lot/batch level and one where they are also aggregated at the case level and at all subsequent outer containers — could be developed.

Each simulation would be analyzed to determine whether any party in the legitimate simulated supply chain had the potential to detect a counterfeit product. A virtual pilot could determine, for example:

• A difference between scenarios
• Whether there is a threshold of counterfeit products that needs to be reached for the proper detection of falsified medications in each scenario
• Whether there is a time difference in detection and alerts between the scenarios.

Final thoughts

Virtual pilots allow deeper analysis of key questions more cost effectively than physical pilots, which could be expensive and could lead the industry to choose an implementation path that may not necessarily lead to the best outcome. Virtual pilots can make good use of the industry’s time between now and 2023 by ferreting out the best and most efficient ways to secure the supply chain while producing a quality blueprint for physical pilots and implementations.