RFID in Pharmaceuticals

Published: Mar 5, 2025 by Kurt Wolf

RFID Basics For Pharma

• A Primer on What RFID Is and How It Works

• RFID in Pharmaceuticals

• Open RFID Tag Standards and DSCSA Compliance
• GS1 Tag Data Standard (TDS) for Unit-of-Use Pharmaceuticals

Radio Frequency Identification (RFID) technology has become a transformative force in the pharmaceutical industry, enhancing drug traceability, inventory management, and patient safety. However, the effectiveness of RFID tagging in pharmaceuticals heavily depends on how drug information is encoded within the Electronic Product Code (EPC) data on RFID tags. There are three primary methods of RFID-based drug identification: the license plate model, the RAIN standard, and the GS1 standard. Each approach has its own advantages and limitations, influencing interoperability, cost, and data accessibility. In this article, we will explore each of these methods in detail, examining their implementation, benefits, and challenges, while highlighting why open standards like GS1 offer the most long-term value.

License Plate Model

The license plate model is one of the simplest and most cost-effective ways to implement RFID tagging in pharmaceuticals. In this approach, each RFID tag contains an EPC data value that serves as a unique identifier. However, this identifier does not encode any intrinsic drug-related information; instead, it acts as a reference that must be looked up in a proprietary database to retrieve the necessary details about the drug.

One of the primary benefits of this approach is its reliance on low-memory, low-cost RFID tags. This makes it an attractive option for pharmaceutical companies looking to implement RFID technology without significantly increasing the cost per unit. Additionally, since the EPC data remains simple, tag reading and encoding processes are straightforward and efficient.

However, a major drawback of the license plate model is its tendency to create walled gardens. Because drug information is stored in proprietary databases, interoperability between different systems can be challenging. If multiple entities within the supply chain—such as manufacturers, wholesalers, and healthcare providers—use different databases, data access can become fragmented, limiting the efficiency of cross-system tracking. This approach requires a strong commitment to maintaining and securing proprietary lookup systems, which can introduce additional costs and complexities over time.

RAIN Standard

The RAIN standard represents an evolution in RFID drug identification by incorporating a company identification number along with encoded information that facilitates lookup in third-party databases. However, it still requires a third-party system to resolve the complete drug information, meaning that access to an external database is necessary to retrieve details such as dosage, lot number, and expiration date.

With the RAIN standard, the EPC data begins with a globally recognized company identifier, ensuring that the manufacturer can be immediately identified. Additional encoded fields provide enough information to categorize the drug, while lookup values enable third-party systems to retrieve comprehensive details. Unlike the license plate model, which relies on a single proprietary database, RAIN enables access to standardized external repositories, improving data accessibility across multiple stakeholders.

A real-world example of the RAIN standard in action is the Cencora/Amerisource RFID data initiative, which leverages this method to improve pharmaceutical tracking and supply chain efficiency [1]. Their system requires integration with a third-party lookup service that resolves EPC data to detailed drug information. This means that while RAIN provides better interoperability than a purely proprietary model, it still necessitates external database dependencies, which can introduce challenges related to availability, standardization, and security concerns. Despite these limitations, the RAIN standard is widely considered a significant improvement over the license plate model in terms of accessibility and interoperability.

GS1 Standard

The GS1 standard takes RFID-based drug identification a step further by embedding critical drug information directly into the EPC data itself. This includes the Global Trade Item Number (GTIN), expiration date, and lot number, eliminating the need for external database lookups.

A key advantage of this method is its universality. Because all necessary drug details are stored within the EPC data, any system equipped to read GS1-compliant RFID tags can instantly access the relevant information without relying on proprietary or third-party databases. This approach promotes full interoperability across the supply chain, from manufacturers to hospitals and pharmacies.

The GS1 standard is thoroughly documented in the Tag Data Standard (TDS), ensuring consistent implementation worldwide [2]. Pharmaceutical companies implementing this method, such as Fresenius Kabi through its Plus RFID program, have demonstrated how GS1-compliant tagging can streamline inventory management and enhance patient safety [3]. While this approach requires RFID tags with higher memory capacity, the benefits in terms of data accessibility, regulatory compliance, and supply chain efficiency make it a compelling choice for many pharmaceutical companies.

Furthermore, GS1 compliance simplifies adherence to global regulatory frameworks, such as the Drug Supply Chain Security Act (DSCSA) in the U.S. and the Falsified Medicines Directive (FMD) in Europe. By reducing reliance on third-party databases, GS1 standards help ensure seamless supply chain operations, minimizing the risks of counterfeit drugs and improving overall transparency. The scalability of GS1 makes it a future-proof investment, preventing costly migration efforts that companies relying on proprietary systems may face later.

The Case for Open Standards

While proprietary and semi-open models like the license plate method and RAIN standard offer some advantages, GS1’s fully open standard provides the most long-term value for pharmaceutical companies. Here’s why:

• Regulatory Compliance: Open standards like GS1 align with key regulations, simplifying compliance and reducing audit risks.
• Supply Chain Efficiency: Real-time, seamless tracking across multiple stakeholders reduces inefficiencies and enhances security.
• Interoperability: Unlike closed or proprietary systems, GS1 ensures that any authorized system can read and process EPC data without database dependencies.
• Cost Savings Over Time: While GS1 may require slightly higher upfront tag costs, it eliminates costly database maintenance, vendor lock-in, and future migration challenges.
• Future-Proofing: Open standards facilitate integration with emerging technologies like blockchain, IoT, and AI-driven analytics, ensuring continued relevance and adaptability.

Conclusion

The method used to encode drug information on RFID tags plays a critical role in determining the effectiveness of pharmaceutical tracking and traceability. The license plate model offers a low-cost entry point but relies on proprietary databases, leading to interoperability challenges. The RAIN standard improves accessibility by including manufacturer identification and third-party lookup capabilities but still depends on external databases. The GS1 standard, while requiring more memory-intensive tags, provides the most comprehensive approach by embedding complete drug information within the EPC data itself, enabling seamless system integration.

As the pharmaceutical industry continues to adopt RFID technology, the choice of identification method will depend on factors such as cost, regulatory compliance, and the need for system interoperability. Open standards like GS1 offer the best pathway to long-term efficiency, regulatory alignment, and supply chain transparency. Pharmaceutical companies should consider the future impact of their RFID strategy and prioritize approaches that maximize data accessibility, interoperability, and cost-effectiveness over time.

References

1. Cencora/Amerisource RFID Data Initiative. Retrieved from: https://www.amerisourcebergen.com/pharmaceutical-distribution/rfid-data
2. GS1 Tag Data Standard. Retrieved from: https://www.gs1.org/standards/tds
3. Fresenius Kabi Plus RFID. Retrieved from: https://www.plusrfid.com/about/