AN ANALYSIS OF PHARMACEUTICAL COUNTERFEITING: ASSESSING SCREENING FACTORS AND THEIR INFLUENCE ON COUNTERFEITING

Abstract

The United States pharmaceutical supply chain is one of the safest and most secure systems in the world. However, in recent years, an increasing number of drug counterfeit products were detected in it. This increase in documented incidents greatly concerns the pharmaceutical industry, and state and federal regulatory bodies. The repercussions of a tainted drug supply chain are potentially economically devastating and detrimental to the health and well-being of the public. Decision makers face a challenge keeping the drug supply chain safe from these influences, specifically assessing the risk of drug counterfeiting. With the problems posed by counterfeit, the identification of the right counterfeit attributes and the development of models to help supply chain managers determine the probability of counterfeit drugs are vital. Known drug counterfeiting research and studies are limited in scope; and despite increasing trends in counterfeiting, empirical research in this area is scarce. This research undertakes an in-depth examination of literature to identify counterfeit attributes and factors as well as to develop a drug counterfeit model to assess the probability of the drug counterfeiting. The identification of drug counterfeiting attributes resulted from a comprehensive review of the literature and a survey of experts. Data were subsequently collected on the attributes identified through literature, case studies, and experts. The findings of this research led to these substantive outcomes:

The identification of 10 key counterfeit attributes: Average Price, Drug Class, Medication Class, Product Type, Volume, Product Complexity, Product Location, Region, Previous Product Counterfeiting, and Product Shortage.

Using exploratory factor analysis, a model emerged with three distinct factors: Market, Product History, and Supply Chain Characteristics.

A process and a model are developed to assess the probability of drug counterfeiting. This is the first known model developed to assess the probability of drug counterfeiting.

Decision makers can assess products in an objective and robust way to determine which products are of greater risk of counterfeiting, and to develop policies and strategies to mitigate or minimize counterfeit drugs in the legitimate supply chain