Background:

The Food and Drug Administration oversees the National Drug Code (NDC) System, a directory of select OTC and prescription drug products. Pharmaceutical manufacturers register unique NDC’s in the directory to identify each of their drug products. Manufacturers are required to update their NDC registrations to remove expired products and register new ones.

Drugs listed in the NDC are identified by an 11-digit number divided into three segments. The first segment, assigned by the FDA, identifies the vendor (or labeler) involved with the manufacturing, packaging, or distribution of the drug. The manufacturer assigns the second and third segments of the code for a given product. Product codes in the second segment describe the generic entity, strength, and dosage form. The third segment, or package code, indicates the package size.

Wholesale distributors order products from manufacturers by NDC.

Wholesale distributors may order similar products such as analgesics, muscle relaxants, and antidepressants from multiple manufacturers, each having unique NDC’s.

Hospitals, clinics, pharmacies and doctors (generally “dispensers”) may order similar analgesics, muscle relaxants, and antidepressants by brand name from multiple wholesale distributors.

The DEA requires CS Registrant manufacturers and distributors to report suspicious orders of controlled substances.

Narcotic analgesics with different NDC’s or brand names can contain the same active ingredient such as hydrocodone, oxycodone or tramadol. Excessive quantities destined for illegal markets are difficult to detect.

If orders are placed by a buyer according to NDC or brand name, it is possible an excessive amount of a CS II-V drug could be ordered unnoticed and be diverted undetected to illegal markets.

Today’s DEA Blog Questions:

• How does your CS II-V order management system monitor suspicious orders of multiple NDC’s within the same drug family?

• Does your system cross reference NDC’s to the Generic Product Identifier for the active ingredient?

• Should the FDA or DEA develop standards for cross referencing NDA’s and active ingredients of concern?

Background:

Traditional “know your customer” due diligence has been at the foundation of pharma supply chain SOP for decades. All reputable pharmaceutical manufacturers and distributors have invested significant resources in developing best practices for maintaining the integrity of their order fulfillment process.

Monthly averaging and thresholds have traditionally provided account managers with the tools necessary to effectively identify orders with characteristics well outside the norm. As the size and complexity of the pharmaceutical industry grew, along with the demand for shorter order-to-cash sales cycles, account managers lacked the time and resources to thoroughly validate unusual orders prior to shipment.

Unfortunately, the criminal element was becoming increasingly bold and creative in their efforts to obtain drugs for illegal markets. In response, the DEA enacted a number of compliance and regulatory measures to increase pharma supply security and reduce illegal activity.

The combination of unabated illegal activity, increased legitimate market demand, and higher compliance and regulatory standards quickly undermined the relevance of traditional order monitoring techniques. The DEA demanded proactive interception of suspicious orders, not reports of suspicious sales after the fact.

Statistically Defensible Computational Analysis:

Those manufacturers and distributors of CS II-V with sufficient resources have responded to DEA mandates for upgrading suspicious order monitoring by developing and applying statistical analysis of every new order for controlled substances coming into their order management system.

Today’s DEA Compliance Blog Question:

Algorithms typically test each new order for significant deviation in order size, frequency and pattern. The tests are compared with the sales order history for a specific line item and specific ship to location. In this example the customer is being compared to itself.

The question is:  Are there benefits to comparing a new order not only to the buyer’s history for that specific item and destination, but also to the history of a group of peers within the supplier’s universe of buyers?

SomLink will support Peer Group Analysis for at least one early adopter. What is your assessment of this test?

How would your company respond to this DEA Notice?

…pursuant to 21 U.S.C. 823(f) and 824(a)(4), it is my preliminary finding that the continued registration of ABC123 Pharmaceutical Wholesale Company is inconsistent with the public interest.

…the Special Agents and Diversion Investigators of the DEA who serve this Order to Show Cause and Immediate Suspension of Registration are authorized to place under seal or to remove for safekeeping all controlled substances that Registrant possess . . .

Last month Harvard Drug Group responded by filing a plea in US District Court seeking relief from their Immediate Suspension Order. Before the week was over, DEA had reinstated Harvard’s CS III-V registration.

How did Harvard mitigate the DEA suspension so quickly? Court records indicate Harvard produced abundant evidence of the extraordinary measures they had taken to comply with DEA anti-diversion mandates, including the design and installation of “a comprehensive, state of the art suspicious order system to monitor orders for controlled substances.”

Does your company have the IT resources to hard code suspicious order analytic tools for your order management system? Are you comfortable with your 21 CFR 1301.74b SOM compliance?

If you have been thinking about an upgrade to your monthly averaging, thresholds, and exceptions reporting system, please consider SOMLink™ automated compliance toolset developed for CS II-V manufacturers and distributors. http://www.e-supplylink.com/som.htm

» Read more: Lessons from Harvard Drug’s Suspension