Overview

Counterfeit products can enter the supply chain at any point. Between production and delivery, storage and dispensation, brand owners are at risk of lost revenue and, more importantly, consumer safety and confidence.

 

Background

St. James’s Hospital in Ireland dispenses drugs directly to patients and is already utilizing serialization and track and trace scanning of its medications using data matrix barcodes that are in compliance with the European Serialization Model (ESM). In cooperation with Sharp Packaging (supplier) and Systech International (Solution Provider), St. James’s ran a pilot with Systech UniSecure. The pilot program simulated the flow of pharmaceutical product through a serialized, international supply chain.

 

Test Case

Introduce counterfeit product in the form of cartons with barcodes copied from the originals and distributed alongside authentic products. Analyze the individual effectiveness of the ESM and Pedigree Model (used in the DSCSA) in detecting and preventing counterfeit medication from getting to patients.

 

Process

A. 1350 cartons representing an oncology product were produced in 3 batches (each batch numbered from 1 – 450) and serialized at Sharp Packaging Solutions. All batches were produced through an identical process. Batches were segmented as follows:

  • Batch 1: ESM model scanning serialized numbers at the supply chain end-points (production and dispensation)
  • Batch 2: Pedigree model (DSCSA) scanning serialized numbers at each point in the supply chain (production, storage, wholesaler, dispensation)
  • Batch 3: UniSecure solution capturing original print mark for instant authentication at any point of the supply chain

B. All three batches were shipped to Systech’s office acting as the distributor in the normal supply chain process. An additional 150 cartons were subsequently produced to simulate counterfeit products and 50 were introduced into each of the three original batches, randomly mixing with genuine product.

  • Each of the 150 cartons had genuine serial numbers that had been read from the original cartons and reprinted – mimicking the process of actual counterfeits.
  • For the pure purpose of this case study the counterfeit products were printed with an additional human readable “c” on the label so that they could be visually identified, however, the 2D barcodes were identical to the originals.

C. Each batch now contained 500 cartons, 450 “genuine” products along with 50 “counterfeit” products that were randomly mixed in to simulate a breach in the supply chain.

D. Batches 1 and 3 were then shipped directly to St James’s Hospital in Ireland simulating the end-to-end authentication scenario of the ESM while batch 2 was further split into two separate parts to simulate the distribution and authentication of product to multiple locations (warehouses, repackagers, wholesalers) prior to authentication at dispensing, such as required in the Pedigree model.

 

Authentication

Batch 1 ESM

A. Serial numbers from the cartons were scanned in St. James’s Hospital using a normal ESM scanner (handheld barcode readers) and the serial number was recorded.

B. When a duplicate serial number was recorded the investigator checked the product for the “c” marking given to all counterfeit items in this test.

NOTE: Since this was a case study the counterfeits were marked with a “c” to easily distinguish them from genuine. In the live supply chain there is no marking to clearly identify them and extensive testing must be done to confirm if the product is genuine or not. This is the inherent weakness of the ESM model. While you may be able to detect a duplicate number in the supply chain – if the genuine item is the second item scanned it represents a potential patient safety risk. As this occurs at dispensing you may have already supplied a consumer with potential counterfeit product and you will only be able to test the item in question and wait for the results (sometimes taking days or months) to determine if the one in question is suspect or genuine. 

C. Results were recorded.

Batch 2 Pedigree model

A. Items were evenly split into two subgroups (2A and 2B) with numbers shuffled and counterfeits dispersed throughout both groups. Representing “time", these subgroups would test the effectiveness to detect duplicate serial numbers in the supply chain and react with sufficient speed to stop them from being dispensed to patients.

B. Using a normal hand scanner as required in the Pedigree model, group 2A was scanned on day one and sent to a 2nd premises representing a pharmacy and the serial numbers were recorded. Group 2B was scanned with the same scanner two days later and then sent to the same premises. Again, the serial numbers were recorded.

C. When a duplicate serial number was recorded the investigator checked the product for the “c” marking given to all counterfeit items in this test.

NOTE: Since this was a case study the counterfeits were marked with a “c” to easily distinguish them from genuine. In the live supply chain there is no marking to clearly identify them and extensive testing must be done to confirm if the product is genuine or not. While you may be able to find a duplicate number in the supply chain – if the genuine item is the second item scanned it is unsure which is genuine. If this occurs before dispensing you may have time to recall and examine the suspect items. 

D. Results were recorded.

Batch 3 UniSecure

A. Barcode labels were scanned in St. James’s Hospital using the UniSecure Smartphone application, UniScan®, and the result of the scan was noted.

B. When a suspected counterfeit barcode label was detected the investigator checked the product to confirm that UniScan had correctly identified that the label was not printed and applied at time of product manufacture.

NOTE: In the live supply chain this process remains the same. The application is scanning the code and can determine that the copied code, even with identical numbers, is not an original. The marking of the “c” is not visible in this scan and bears no influence on the results provided – it is only there as a reference point in this example for the tester. 

C. Results were recorded.

 

Results

Batch 1 ESM model

Eighteen of the 50 counterfeit products that were randomly added to the batch were incorrectly verified and dispensed to patients (in simulation only) before their authentic counterparts made it to the point of dispensing and aroused suspicion that there were duplicate serial numbers in the supply chain.

Note: This is the inherent weakness of the ESM model because it is an “End to End” model. In other words the only verification scan is at the point of dispensing.

Batch 2 – Pedigree model

Ten of the 50 counterfeit products that were randomly added to the batch were verified and dispensed to patients (in simulation only) before their authentic counterparts made it to the point of dispensing and aroused suspicion that there were duplicate serial numbers in the supply chain.

Note: The added verification step inherent in this model (authentication at multiple points prior to dispensing) reduced the number of counterfeits reaching the patient to 10 counterfeits. This extra verification step allowed the distributor to recognize that duplicate serial numbers were present in the supply chain and communicate the findings forward before the counterfeit was dispensed to the patient. The counterfeits that got through did so because the duplicate serial number was flagged after the counterfeit product had already been distributed to the patient.

Batch 3 – UniSecure

One hundred percent of the counterfeit products were identified at authentication ensuring no counterfeit product went to patients. This is because the UniSecure solution does not rely on the traditional track and trace of serial numbers but instead, at the time of scanning, compares the scanned barcode against the unique “fingerprint” produced during the label printing process.

Utilization of Systech’s covert security solution UniSecure facilitated a completely secure supply chain without any modification to packaging.

The pilot clearly demonstrates that in both the ESM and Pedigree models, it is possible for a counterfeit product to be dispensed to patients in a serialized supply chain. The pilot also demonstrates how UniSecure addresses the existing security flaws to safeguard patient safety.

These results demonstrate how security flaws in existing STT models can be addressed and patient safety safeguarded.

 

Conclusions

Serialization alone is not adequate to eliminate diversion and counterfeiting risks in the supply chain.

The pharmaceutical industry requires a solution that 1) is secure; 2) works alongside current serialization models;  3) is economically viable to implement relative to the profit per unit of product and 4) offers ubiquitous authentication, as all supply chain parties would need to be able to verify in real time.

St. James’s Hospital was chosen for this demonstration because it has a population of chronic disease patients who currently scan medication in the home using a specific smartphone medication scanning app. In this case study, because UniSecure features a smartphone scanning app, the hospital was able to demonstrate that it would be technically feasible to make the UniSecure app available to patients or embed it into the existing app, providing an additional layer of security.

 

Systech UniSecure is a covert anti-counterfeiting and brand protection technology derived from existing standard printing on a products' packaging.

 

The foundation of the UniSecure technology begins with the printing of a marking or data carrier. During the printing process, environmental and input factors such as line vibration, printer tolerances, etc., combine to produce small scale variations or “noise” in the printed data carrier or symbol. These variations are both random and unique producing a “fingerprint” that is impossible to replicate.

The UniSecure solution works by detecting specific measurable characteristic patterns within this printing noise, harnessing these variations to generate an electronic signature. This electronic signature is unique to a given instance of a product and can be utilized on either a serialized (e.g. serialized GS1 2-D Matrix) or non-serialized data carrier (e.g. linear barcode or another printed symbol).

The combination of four features render Systech’s UniSecure technology unmatched and ideal for the pharmaceutical industry.

1. Low barriers to implementation: Most authentication technologies are additive – in that the application is based on introducing an element into existing packaging – for example a special material, ink or an embedded algorithm. The addition of these features is costly and the business process reengineering to implement them is disruptive. UniSecure is different than other anti-counterfeit solutions in the market. It is a derivative rather than an additive. Because UniSecure leverages the existing printing process and a simple smartphone to verify it, it can deliver robust authentication at a fraction of the cost of competing technologies.

2. Ubiquitous authentication: Because authentication of the signature is facilitated through the use of a simple smartphone, it provides a scalable authentication solution. This allows easy verification by multiple parties within the supply chain – including internal employees, government officials, customs agents, resellers and even consumers. In this respect the e-Fingerprint technology holds a significant advantage over other authentication technologies that require expensive, proprietary field devices to authenticate.

3. Effectiveness: Another advantage is the effectiveness and overall security of the solution. Because the UniSecure solution is based on capturing variation rather than embedding or creating a security measure, there is nothing engineered and therefore nothing for counterfeiters to reverse engineer. As such the e-Fingerprint solution cannot be counterfeited through usual methods.

4. Compatibility: The solution does not interfere with the current serialization track and trace models. There is no doubt that these models (ESM and e-Pedigree) have an important part to play in helping to secure the supply chain process, but also in inventory management in general. It is not the role or intention of UniSecure to replace these models but to act as an additional security feature to help secure the pharma supply chain and ultimately improve patient safety.

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