Counterfeit drug identification and alert system
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Date
2023-07Author
Mwesigwa, Joshua Mudde
Nduhura, Edgar Kamugisha
Muhumuza, Rymon
Kakembo, Collins Mukiibi
Gwanyi, Brian Nelson
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Counterfeit drugs or medicine is defined as a pharmaceutical product that is produced and sold
with an intension to deceive the consumer about the origin, authenticity or value of the product.
Counterfeit drugs cover all drugs made to closely imitate original drugs. In this study, we focus
mostly on the locally made drugs from the pharmaceuticals within the Ugandan geographic
boundaries. Counterfeit drugs are causing a significant negative impact on the organization and
the user’s wellbeing hence; producers are confronting enormous misfortune (Tambe et al.,
2021). This can be brought about by a number of reasons such as limited drug regulatory
agencies in the country or inconsistent legal framework, lack of border control making it easy
for smugglers and poverty forcing people to look for cheap street drugs. According to
Shreekumar et al. (2022), drug manufacturers face the biggest problems and huge losses in
sense of brand damage as well as revenue loss. Therefore, to find out the originality and
preserve the integrity and authenticity of the product, block chain technology can be used to
control the problem.
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The main objective of this study was to develop a counterfeit drug identification and alert
system which was achieved through the different specific aims which included; gathering
requirements for the block chain counterfeit drug detection and alert system, designing the
model for the system, implementing the system, testing and lastly validating the block chain
counterfeit drug detection and alert system.
The methodology involved the use of agile methodology which is an iterative development
methodology enabling customers, regulatory bodies that is to say NDA (National Drug
Authority), Distributors and Raw material suppliers in taking part of the development and
tracing the supply chain of the drug distribution specifically locally made drugs. This report is
a detailed combination of all activities we engaged in while developing the counterfeit
identification and alert system.
During the data collection and analysis phase, the respondents were from various regions of
Wandegeya and Makerere, with ages ranging from 25 to 55 years old. They were
predominantly male (60%) while (40%) were females and held positions ranging from
manufacturing to regulatory and healthcare positions. The majority of respondents had at least
a bachelor's degree (80%), and most of them (70%) were located in urban areas. Out of the
sample of 92 individuals, the full response rate was 89%, while 11% partially responded to our
interviews. The system was developed using agile methods that involved iterative methods of
development. A prototype was developed, tested and validated.